multi-decadal scale variability: Topics by WorldWideScience.org

Sample records for multi-decadal scale variability

Holocene Multi-Decadal to Millennial-Scale Hydrologic Variability on the South American Altiplano

Science.gov (United States)

Fritz, S. C.; Baker, P. A.; Ekdahl, E.; Burns, S.

2006-12-01

On orbital timescales, lacustrine sediment records in the tropical central Andes show massive changes in lake level due to mechanisms related to global-scale drivers, varying at precessional timescales. Here we use stable isotopic and diatom records from two lakes in the Lake Titicaca drainage basin to reconstruct multi- decadal to millennial scale precipitation variability during the last 7000 to 8000 years. The records are tightly coupled at multi-decadal to millennial scales with each other and with lake-level fluctuations in Lake Titicaca, indicating that the lakes are recording a regional climate signal. A quantitative reconstruction of precipitation from stable isotopic data indicates that the central Andes underwent significant wet to dry alternations at multi- centennial frequencies with an amplitude of 30 to 40% of total precipitation. A strong millennial-scale component, similar in duration to periods of increased ice rafted debris flux in the North Atlantic, is observed in both lake records, suggesting that tropical North Atlantic sea-surface temperature (SST) variability may partly control regional precipitation. No clear relationship is evident between these records and the inferred ENSO history from Lago Pallcacocha in the northern tropical Andes. In the instrumental period, regional precipitation variability on inter-annual timescales is clearly influenced by Pacific modes; for example, most El Ninos produce dry and warm conditions in this part of the central Andes. However, on longer timescales, the control of tropical Pacific modes is less clear. Our reconstructions suggest that the cold intervals of the Holocene Bond events are periods of increased precipitation in the central Andes, thus indicating an anti-phasing of precipitation variation in the southern tropics of South America relative to the Northern Hemisphere monsoon region.
Synchronous multi-decadal climate variability of the whole Pacific areas revealed in tree rings since 1567

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Fang, Keyan; Cook, Edward; Guo, Zhengtang; Chen, Deliang; Ou, Tinghai; Zhao, Yan

2018-02-01

Oceanic and atmospheric patterns play a crucial role in modulating climate variability from interannual to multi-decadal timescales by causing large-scale co-varying climate changes. The brevity of the existing instrumental records hinders the ability to recognize climate patterns before the industrial era, which can be alleviated using proxies. Unfortunately, proxy based reconstructions of oceanic and atmospheric modes of the past millennia often have modest agreements with each other before the instrumental period, raising questions about the robustness of the reconstructions. To ensure the stability of climate signals in proxy data through time, we first identified tree-ring datasets from distant regions containing coherent variations in Asia and North America, and then interpreted their climate information. We found that the multi-decadal covarying climate patterns of the middle and high latitudinal regions around the northern Pacific Ocean agreed quite well with the climate reconstructions of the tropical and southern Pacific areas. This indicates a synchronous variability at the multi-decadal timescale of the past 430 years for the entire Pacific Ocean. This pattern is closely linked to the dominant mode of the Pacific sea surface temperature (SST) after removing the warming trend. This Pacific multi-decadal SST variability resembles the Interdecadal Pacific Oscillation.
Tropical rainforests dominate multi-decadal variability of the global carbon cycle

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Zhang, X.; Wang, Y. P.; Peng, S.; Rayner, P. J.; Silver, J.; Ciais, P.; Piao, S.; Zhu, Z.; Lu, X.; Zheng, X.

2017-12-01

Recent studies find that inter-annual variability of global atmosphere-to-land CO2 uptake (NBP) is dominated by semi-arid ecosystems. However, the NBP variations at decadal to multi-decadal timescales are still not known. By developing a basic theory for the role of net primary production (NPP) and heterotrophic respiration (Rh) on NBP and applying it to 100-year simulations of terrestrial ecosystem models forced by observational climate, we find that tropical rainforests dominate the multi-decadal variability of global NBP (48%) rather than the semi-arid lands (35%). The NBP variation at inter-annual timescales is almost 90% contributed by NPP, but across longer timescales is progressively controlled by Rh that constitutes the response from the NPP-derived soil carbon input (40%) and the response of soil carbon turnover rates to climate variability (60%). The NBP variations of tropical rainforests is modulated by the ENSO and the PDO through their significant influences on temperature and precipitation at timescales of 2.5-7 and 25-50 years, respectively. This study highlights the importance of tropical rainforests on the multi-decadal variability of global carbon cycle, suggesting that we need to carefully differentiate the effect of NBP long-term fluctuations associated with ocean-related climate modes on the long-term trend in land sink.
Sources of multi-decadal variability in Arctic sea ice extent

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Day, J J; Hargreaves, J C; Annan, J D; Abe-Ouchi, A

2012-01-01

The observed dramatic decrease in September sea ice extent (SIE) has been widely discussed in the scientific literature. Though there is qualitative agreement between observations and ensemble members of the Third Coupled Model Intercomparison Project (CMIP3), it is concerning that the observed trend (1979–2010) is not captured by any ensemble member. The potential sources of this discrepancy include: observational uncertainty, physical model limitations and vigorous natural climate variability. The latter has received less attention and is difficult to assess using the relatively short observational sea ice records. In this study multi-centennial pre-industrial control simulations with five CMIP3 climate models are used to investigate the role that the Arctic oscillation (AO), the Atlantic multi-decadal oscillation (AMO) and the Atlantic meridional overturning circulation (AMOC) play in decadal sea ice variability. Further, we use the models to determine the impact that these sources of variability have had on SIE over both the era of satellite observation (1979–2010) and an extended observational record (1953–2010). There is little evidence of a relationship between the AO and SIE in the models. However, we find that both the AMO and AMOC indices are significantly correlated with SIE in all the models considered. Using sensitivity statistics derived from the models, assuming a linear relationship, we attribute 0.5–3.1%/decade of the 10.1%/decade decline in September SIE (1979–2010) to AMO driven variability. (letter)
Relationship between the Arctic oscillation and surface air temperature in multi-decadal time-scale

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Tanaka, Hiroshi L.; Tamura, Mina

2016-09-01

In this study, a simple energy balance model (EBM) was integrated in time, considering a hypothetical long-term variability in ice-albedo feedback mimicking the observed multi-decadal temperature variability. A natural variability was superimposed on a linear warming trend due to the increasing radiative forcing of CO2. The result demonstrates that the superposition of the natural variability and the background linear trend can offset with each other to show the warming hiatus for some period. It is also stressed that the rapid warming during 1970-2000 can be explained by the superposition of the natural variability and the background linear trend at least within the simple model. The key process of the fluctuating planetary albedo in multi-decadal time scale is investigated using the JRA-55 reanalysis data. It is found that the planetary albedo increased for 1958-1970, decreased for 1970-2000, and increased for 2000-2012, as expected by the simple EBM experiments. The multi-decadal variability in the planetary albedo is compared with the time series of the AO mode and Barents Sea mode of surface air temperature. It is shown that the recent AO negative pattern showing warm Arctic and cold mid-latitudes is in good agreement with planetary albedo change indicating negative anomaly in high latitudes and positive anomaly in mid-latitudes. Moreover, the Barents Sea mode with the warm Barents Sea and cold mid-latitudes shows long-term variability similar to planetary albedo change. Although further studies are needed, the natural variabilities of both the AO mode and Barents Sea mode indicate some possible link to the planetary albedo as suggested by the simple EBM to cause the warming hiatus in recent years.
The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

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Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.
How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?

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Jiang, Peng; Gautam, Mahesh R.; Zhu, Jianting; Yu, Zhongbo

2013-02-01

SummaryMulti-scale temporal variability of precipitation has an established relationship with floods and droughts. In this paper, we present the diagnostics on the ability of 16 General Circulation Models (GCMs) from Bias Corrected and Downscaled (BCSD) World Climate Research Program's (WCRP's) Coupled Model Inter-comparison Project Phase 3 (CMIP3) projections and 10 Regional Climate Models (RCMs) that participated in the North American Regional Climate Change Assessment Program (NARCCAP) to represent multi-scale temporal variability determined from the observed station data. Four regions (Los Angeles, Las Vegas, Tucson, and Cimarron) in the Southwest United States are selected as they represent four different precipitation regions classified by clustering method. We investigate how storm properties and seasonal, inter-annual, and decadal precipitation variabilities differed between GCMs/RCMs and observed records in these regions. We find that current GCMs/RCMs tend to simulate longer storm duration and lower storm intensity compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Our results show that the studied GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with multi-scale temporal precipitation variability.
Inter-annual to multi-decadal variability in prairie water resources over the past millennium

International Nuclear Information System (INIS)

Sauchyn, D.

2008-01-01

In the Prairie Provinces, declining levels have been recently recorded for various rivers and lakes, and further reductions are projected. These trends reflect human impact in terms of increasing water consumption and possibly anthropogenic climate change. From the coupling of hydrological models and climate change scenarios, researchers have projected lower future summer flows as global warming brings shorter warmer winters and longer and generally drier summers to western Canada. However, the detection and interpretation of trends from gauge records and model outputs are constrained by the relatively short perspective of decades and the uncertainties associated with projecting climate change and its impacts on hydrological regimes. A longer perspective on inter-annual to multi-decadal variability in water resources is available from moisture-sensitive tree-ring chronologies. We have established a dense network of low elevation chronologies spanning the headwaters of the Saskatchewan, Missouri, Churchill and Mackenzie River basins. Standardized tree-ring width for a large sample of trees and sites is a strong regional signal of annual and seasonal hydroclimate, and an especially good proxy of low water levels. Proxy streamflow records, up to 800 years in length, show quasi-periodic variability at inter-annual to multi-decadal scales that correspond to the tempo of sea-surface temperature anomalies. The industrial sponsors of our research, Manitoba Hydro and EPCOR, anticipate the use of our tree-ring reconstructions for informing forecasts of future water supplies and planning adaptation to climate change. Engineers from these companies, and more than 50 other water managers and planners from the Prairie Provinces, attended a workshop in March 2008 to explore potential applications of paleo-hydrological records to water resource management. (author)
Multi-Decadal to Millennial Scale Holocene Hydrologic Variation in the Southern Hemisphere Tropics of South America

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Ekdahl, E. J.; Fritz, S. C.; Baker, P. A.; Burns, S. J.; Coley, K.; Rigsby, C. A.

2005-12-01

Numerous sites in the Northern Hemisphere show multi-decadal to millennial scale climate variation during the Holocene, many of which have been correlated with changes in atmospheric radiocarbon production or with changes in North Atlantic oceanic circulation. The manifestation of such climate variability in the hydrology of the Southern Hemisphere tropics of South America is unclear, because of the limited number of records at suitably high resolution. In the Lake Titicaca drainage basin of Bolivia and Peru, high-resolution lacustrine records reveal the overall pattern of Holocene lake-level change, the influence of precessional forcing of the South American Summer Monsoon, and the effects of high-frequency climate variability in records of lake productivity and lake ecology. Precessional forcing of regional precipitation is evident in the Lake Titicaca basin as a massive (ca. 85 m) mid-Holocene decline in lake level beginning about 7800 cal yr BP and a subsequent rise in lake level after 4000 cal yr BP. Here we show that multi-decadal to millennial-scale climate variability, superimposed upon the envelope of change at orbital time scales, is similar in timing and pattern to the ice-rafted debris record of Holocene Bond events in the North Atlantic. A high-resolution carbon isotopic record from Lake Titicaca that spans the entire Holocene suggests that cold intervals of Holocene Bond events are periods of increased precipitation, thus indicating an anti-phasing of precipitation variation on the Altiplano relative to the Northern Hemisphere tropics. A similar pattern of variation is also evident in high-resolution (2-30 yr spacing) diatom and geochemical records that span the last 7000 yr from two smaller lakes, Lagos Umayo and Lagunillas, in the Lake Titicaca drainage basin.
Atmospheric River Characteristics under Decadal Climate Variability

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Done, J.; Ge, M.

2017-12-01

How does decadal climate variability change the nature and predictability of atmospheric river events? Decadal swings in atmospheric river frequency, or shifts in the proportion of precipitation falling as rain, could challenge current water resource and flood risk management practice. Physical multi-scale processes operating between Pacific sea surface temperatures (SSTs) and atmospheric rivers over the Western U.S. are explored using the global Model for Prediction Across Scales (MPAS). A 45km global mesh is refined over the Western U.S. to 12km to capture the major terrain effects on precipitation. The performance of the MPAS is first evaluated for a case study atmospheric river event over California. Atmospheric river characteristics are then compared in a pair of idealized simulations, each driven by Pacific SST patterns characteristic of opposite phases of the Interdecadal Pacific Oscillation (IPO). Given recent evidence that we have entered a positive phase of the IPO, implications for current reservoir management practice over the next decade will be discussed. This work contributes to the NSF-funded project UDECIDE (Understanding Decision-Climate Interactions on Decadal Scales). UDECIDE brings together practitioners, engineers, statisticians, and climate scientists to understand the role of decadal climate information for water management and decisions.
Causes of decadal climate variability over the North Pacific and North America

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Latif, M.; Barnett, T.P.

1994-01-01

The cause of decadal climate variability over the North Pacific and North America is investigated by analyzing data from a multi-decadal integration with a state of the art coupled ocean-atmosphere model and observations. About one third of the low-frequency climate variability in the region of interest can be attributed to a cycle involving unstable air-sea interactions between the subtropical gyre circulation in the North Pacific and the Aleutian low pressure system. The existence of this cycle provides a basis for long-range climate forecasting over the western United States at decadal time scales. (orig.)
Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

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Kreibich, Heidi; Schröter, Kai; Merz, Bruno

2016-05-01

Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB).In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.
Dynamical and biogeochemical control on the decadal variability of ocean carbon fluxes

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R. Séférian

2013-04-01

Full Text Available Several recent observation-based studies suggest that ocean anthropogenic carbon uptake has slowed down due to the impact of anthropogenic forced climate change. However, it remains unclear whether detected changes over the recent time period can be attributed to anthropogenic climate change or rather to natural climate variability (internal plus naturally forced variability alone. One large uncertainty arises from the lack of knowledge on ocean carbon flux natural variability at the decadal time scales. To gain more insights into decadal time scales, we have examined the internal variability of ocean carbon fluxes in a 1000 yr long preindustrial simulation performed with the Earth System Model IPSL-CM5A-LR. Our analysis shows that ocean carbon fluxes exhibit low-frequency oscillations that emerge from their year-to-year variability in the North Atlantic, the North Pacific, and the Southern Ocean. In our model, a 20 yr mode of variability in the North Atlantic air-sea carbon flux is driven by sea surface temperature variability and accounts for ~40% of the interannual regional variance. The North Pacific and the Southern Ocean carbon fluxes are also characterised by decadal to multi-decadal modes of variability (10 to 50 yr that account for 20–40% of the interannual regional variance. These modes are driven by the vertical supply of dissolved inorganic carbon through the variability of Ekman-induced upwelling and deep-mixing events. Differences in drivers of regional modes of variability stem from the coupling between ocean dynamics variability and the ocean carbon distribution, which is set by large-scale secular ocean circulation.
Global multi-decadal ocean climate and small-pelagic fish population

International Nuclear Information System (INIS)

Tourre, Yves M; Lluch-Cota, Salvador E; White, Warren B

2007-01-01

Ocean climate, environmental and biological conditions vary on several spatio-temporal scales. Besides climate change associated with anthropogenic activity, there is growing evidence of a natural global multi-decadal climate signal in the ocean-atmosphere-biosphere climate system. The spatio-temporal evolution of this signal is thus analyzed during the 20th century and compared to the variability of small-pelagic fish landings. It is argued that the low-frequency global ocean environment and plankton ecosystems must be modified such that small-pelagic populations vary accordingly. A small-pelagic global index or fishing 'regime indicator series' (RIS) (i.e. a small-pelagic abundance indicator) is used. RIS is derived from fish landings data in the four main fishing areas in the Pacific and Atlantic oceans. Global RIS changes phase (from positive to negative values) when SST multi-decadal anomalies are out-of-phase between the eastern Pacific and southern Atlantic. RIS also displays maxima during the mid-30s to early-40s and the late-70s to early-80s when the multi-decadal signal was approximately changing phases (Tourre and White 2006 Geophys. Res. Lett. 33 L06716). It is recognized that other factors may modulate fish stocks, including anthropogenic predation. Nevertheless it is proposed that variable climate and environment, and the low-frequency 'global synchrony' of small-pelagic landings (Schwartzlose et al 1999 S. Afr. J. Mar. Sci. 21 289-347), could be associated with the multi-decadal changes in global ocean climate conditions
Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

Directory of Open Access Journals (Sweden)

H. Kreibich

2016-05-01

Full Text Available Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB.In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.
Multi-decadal Variability of the Wind Power Output

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Kirchner Bossi, Nicolas; García-Herrera, Ricardo; Prieto, Luis; Trigo, Ricardo M.

2014-05-01

The knowledge of the long-term wind power variability is essential to provide a realistic outlook on the power output during the lifetime of a planned wind power project. In this work, the Power Output (Po) of a market wind turbine is simulated with a daily resolution for the period 1871-2009 at two different locations in Spain, one at the Central Iberian Plateau and another at the Gibraltar Strait Area. This is attained through a statistical downscaling of the daily wind conditions. It implements a Greedy Algorithm as classificator of a geostrophic-based wind predictor, which is derived by considering the SLP daily field from the 56 ensemble members of the longest homogeneous reanalysis available (20CR, 1871-2009). For calibration and validation purposes we use 10 years of wind observations (the predictand) at both sites. As a result, a series of 139 annual wind speed Probability Density Functions (PDF) are obtained, with a good performance in terms of wind speed uncertainty reduction (average daily wind speed MAE=1.48 m/s). The obtained centennial series allow to investigate the multi-decadal variability of wind power from different points of view. Significant periodicities around the 25-yr frequency band, as well as long-term linear trends are detected at both locations. In addition, a negative correlation is found between annual Po at both locations, evidencing the differences in the dynamical mechanisms ruling them (and possible complementary behavior). Furthermore, the impact that the three leading large-scale circulation patterns over Iberia (NAO, EA and SCAND) exert over wind power output is evaluated. Results show distinct (and non-stationary) couplings to these forcings depending on the geographical position and season or month. Moreover, significant non-stationary correlations are observed with the slow varying Atlantic Multidecadal Oscillation (AMO) index for both case studies. Finally, an empirical relationship is explored between the annual Po and the
Stochastically-forced Decadal Variability in Australian Rainfall

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Taschetto, A.

2015-12-01

Iconic Australian dry and wet periods were driven by anomalous conditions in the tropical oceans, such as the worst short-term drought in the southeast in 1982 associated with the strong El Niño and the widespread "Big Wet" in 1974 linked with a La Niña event. The association with oceanic conditions makes droughts predictable to some extent. However, prediction can be difficult when there is no clear external forcing such as El Niños. Can dry spells be triggered and maintained with no ocean memory? In this study, we investigate the potential role of internal multi-century atmospheric variability in controlling the frequency, duration and intensity of long-term dry and wet spells over Australia. Two multi-century-scale simulations were performed with the NCAR CESM: (1) a fully-coupled simulation (CPLD) and (2) an atmospheric simulation forced by a seasonal SST climatology derived from the coupled experiment (ACGM). Results reveal that droughts and wet spells can indeed be generated by internal variability of the atmosphere. Those internally generated events are less severe than those forced by oceanic variability, however the duration of dry and wet spells longer than 3 years is comparable with and without the ocean memory. Large-scale ocean modes of variability seem to play an important role in producing continental-scale rainfall impacts over Australia. While the Pacific Decadal Oscillation plays an important role in generating droughts in the fully coupled model, perturbations of monsoonal winds seem to be the main trigger of dry spells in the AGCM case. Droughts in the mid-latitude regions such as Tasmania can be driven by perturbations in the Southern Annular Mode, not necessarily linked to oceanic conditions even in the fully-coupled model. The mechanisms behind internally-driven mega-droughts and mega-wets will be discussed.
Multi-scale climate modelling over Southern Africa using a variable-resolution global model

CSIR Research Space (South Africa)

Engelbrecht, FA

2011-12-01

Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...
Decadal and long-term sea level variability in the tropical Indo-Pacific Ocean

Digital Repository Service at National Institute of Oceanography (India)

Nidheesh, A.G.; Lengaigne, M.; Vialard, J.; Unnikrishnan, A.S.; Dayan, H.

(Shankar and Shetye 1999, Unnikrishnan and Shankar 2007) as well as in the basin scale (Lee and McPhaden 2008, Cheng et al. 2008, Han et al. 2010) have been previously investigated, the picture of decadal/multi-decadal variability in the tropical Indo... dynamics along the rim of the northern Indian Ocean (McCreary et al. 1993, McCreary et al. 1996). At intra- seasonal timescales, the Indo-Pacific warm pool region is home to the Madden-Julian Oscillation, an eastward moving energetic fluctuation of deep...
North American Rocky Mountain Hydroclimate: Holocene patterns and variability at multi-decadal to millennial time scales

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Finney, B.; Anderson, L.; Berkelhammer, M. B.; Barron, J. A.; Steinman, B. A.; Abbott, M. B.

2015-12-01

A network of western North American lake sediment isotope records (calcium carbonate-δ18O) developed during the past decade provides substantial evidence of Pacific ocean-atmosphere forcing of precipitation variability during the Holocene. We present an overview of the eighteen lake carbonate-δ18O records located in the North American Rocky Mountains with a new compilation of modern lake water isotope measurements to characterize their sensitivity to variations in precipitation-δ18O and fractionation effects by evaporation. Comparative analysis of the carbonate-δ18O records that reflect precipitation isotope (δ18O) values (i.e., precipitation "isometers") indicates a sequence of time-varying in-phase and antiphase patterns between northern and southern regions during the Holocene that provide evidence for a highly non-stationary influence of Pacific ocean-atmosphere processes on the hydroclimate of western North America. We identify a prominent precipitation-δ18O dipole, which was sustained for ~2000 years between ~3.5 and 1.5 ka. The dipole contrasts with divergent earlier Holocene patterns and appears to indicate the onset of linkages between northern and tropical Pacific ocean-atmosphere dynamics as we know them today. These observations are informed by previous research on North Pacific precipitation-δ18O. Further investigation of short (observational) and long (Holocene) time scale patterns are needed to improve our understanding of the processes that 1) drive regional precipitation-δ18O responses to Pacific Ocean-atmosphere variability, and 2) cause varying internal ocean-atmosphere responses to external climate forcing.

A Robust Decision-Making Technique for Water Management under Decadal Scale Climate Variability

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Callihan, L.; Zagona, E. A.; Rajagopalan, B.

2013-12-01

Robust decision making, a flexible and dynamic approach to managing water resources in light of deep uncertainties associated with climate variability at inter-annual to decadal time scales, is an analytical framework that detects when a system is in or approaching a vulnerable state. It provides decision makers the opportunity to implement strategies that both address the vulnerabilities and perform well over a wide range of plausible future scenarios. A strategy that performs acceptably over a wide range of possible future states is not likely to be optimal with respect to the actual future state. The degree of success--the ability to avoid vulnerable states and operate efficiently--thus depends on the skill in projecting future states and the ability to select the most efficient strategies to address vulnerabilities. This research develops a robust decision making framework that incorporates new methods of decadal scale projections with selection of efficient strategies. Previous approaches to water resources planning under inter-annual climate variability combining skillful seasonal flow forecasts with climatology for subsequent years are not skillful for medium term (i.e. decadal scale) projections as decision makers are not able to plan adequately to avoid vulnerabilities. We address this need by integrating skillful decadal scale streamflow projections into the robust decision making framework and making the probability distribution of this projection available to the decision making logic. The range of possible future hydrologic scenarios can be defined using a variety of nonparametric methods. Once defined, an ensemble projection of decadal flow scenarios are generated from a wavelet-based spectral K-nearest-neighbor resampling approach using historical and paleo-reconstructed data. This method has been shown to generate skillful medium term projections with a rich variety of natural variability. The current state of the system in combination with the
Mechanisms for decadal scale variability in a simulated Atlantic meridional overturning circulation

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Medhaug, I.; Eldevik, T.; Furevik, T. [University of Bergen, Geophysical Institute, Bergen (Norway); Bjerknes Centre for Climate Research, Bergen (Norway); Langehaug, H.R. [Nansen Environmental and Remote Sensing Center, Bergen (Norway); Bjerknes Centre for Climate Research, Bergen (Norway); Bentsen, M. [Uni Bjerknes Centre, Uni Research, Bergen (Norway); Bjerknes Centre for Climate Research, Bergen (Norway)

2012-07-15

Variability in the Atlantic Meridional Overturning Circulation (AMOC) has been analysed using a 600-year pre-industrial control simulation with the Bergen Climate Model. The typical AMOC variability has amplitudes of 1 Sverdrup (1 Sv = 10{sup 6} m{sup 3} s{sup -1}) and time scales of 40-70 years. The model is reproducing the observed dense water formation regions and has very realistic ocean transports and water mass distributions. The dense water produced in the Labrador Sea (1/3) and in the Nordic Seas, including the water entrained into the dense overflows across the Greenland-Scotland Ridge (GSR; 2/3), are the sources of North Atlantic Deep Water (NADW) forming the lower limb of the AMOC's northern overturning. The variability in the Labrador Sea and the Nordic Seas convection is driven by decadal scale air-sea fluxes in the convective region that can be related to opposite phases of the North Atlantic Oscillation. The Labrador Sea convection is directly linked to the variability in AMOC. Linkages between convection and water mass transformation in the Nordic Seas are more indirect. The Scandinavian Pattern, the third mode of atmospheric variability in the North Atlantic, is a driver of the ocean's poleward heat transport (PHT), the overall constraint on northern water mass transformation. Increased PHT is both associated with an increased water mass exchange across the GSR, and a stronger AMOC. (orig.)
Large-Scale Processes Associated with Inter-Decadal and Inter-Annual Early Spring Rainfall Variability in Taiwan

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Jau-Ming Chen

2016-02-01

Full Text Available Early spring (March - April rainfall in Taiwan exhibits evident and distinct inter-annual and inter-decadal variability. The inter-annual varibility has a positive correlation with the El Niño/Southern Oscillation while the inter-decadal variability features a phase change beginning in the late 1970s, coherent with the major phase change in the Pacific decadal oscillation. Rainfall variability in both timescales is regulated by large-scale processes showing consistent dynamic features. Rainfall increases are associated with positive sea surface temperature (SST anomalies in the tropical eastern Pacific and negative SST anomalies in the tropical central Pacific. An anomalous lower-level divergent center appears in the tropical central Pacific. Via a Rossby-wave-like response, an anomalous lower-level anticyclone appears to the southeast of Taiwan over the Philippine Sea-tropical western Pacific region, which is accompanied by an anomalous cyclone to the north-northeast of Taiwan. Both circulation anomalies induce anomalous southwesterly flows to enhance moisture flux from the South China Sea onto Taiwan, resulting in significant moisture convergence nearby Taiwan. With enhanced moisture supplied by anomalous southwesterly flows, significant rainfall increases occur in both inter-annual and inter-decadal timescales in early spring rainfall on Taiwan.
Analysis of Decadal Vegetation Dynamics Using Multi-Scale Satellite Images

Science.gov (United States)

Chiang, Y.; Chen, K.

2013-12-01

This study aims at quantifying vegetation fractional cover (VFC) by incorporating multi-resolution satellite images, including Formosat-2(RSI), SPOT(HRV/HRG), Landsat (MSS/TM) and Terra/Aqua(MODIS), to investigate long-term and seasonal vegetation dynamics in Taiwan. We used 40-year NDVI records for derivation of VFC, with field campaigns routinely conducted to calibrate the critical NDVI threshold. Given different sensor capabilities in terms of their spatial and spectral properties, translation and infusion of NDVIs was used to assure NDVI coherence and to determine the fraction of vegetation cover at different spatio-temporal scales. Based on the proposed method, a bimodal sequence of intra-annual VFC which corresponds to the dual-cropping agriculture pattern was observed. Compared to seasonal VFC variation (78~90%), decadal VFC reveals moderate oscillations (81~86%), which were strongly linked with landuse changes and several major disturbances. This time-series mapping of VFC can be used to examine vegetation dynamics and its response associated with short-term and long-term anthropogenic/natural events.
AMOC decadal variability in Earth system models: Mechanisms and climate impacts

Energy Technology Data Exchange (ETDEWEB)

Fedorov, Alexey [Yale Univ., New Haven, CT (United States)

2017-09-06

This is the final report for the project titled "AMOC decadal variability in Earth system models: Mechanisms and climate impacts". The central goal of this one-year research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) within a hierarchy of climate models ranging from realistic ocean GCMs to Earth system models. The AMOC is a key element of ocean circulation responsible for oceanic transport of heat from low to high latitudes and controlling, to a large extent, climate variations in the North Atlantic. The questions of the AMOC stability, variability and predictability, directly relevant to the questions of climate predictability, were at the center of the research work.
An 1800-yr record of decadal-scale hydroclimatic variability in the upper Arkansas River basin from bristlecone pine

Science.gov (United States)

Woodhouse, C.A.; Pederson, G.T.; Gray, S.T.

2011-01-01

Bristlecone pine trees are exceptionally long-lived, and with the incorporation of remnant material have been used to construct multi-millennial length ring-width chronologies. These chronologies can provide valuable information about past temperature and moisture variability. In this study, we outline a method to build a moisture-sensitive bristlecone chronology and assess the robustness and consistency of this sensitivity over the past 1200. yr using new reconstructions of Arkansas River flow (AD 1275-2002 and 1577-2002) and the summer Palmer Drought Sensitivity Index. The chronology, a composite built from parts of three collections in the central Rocky Mountains, is a proxy for decadal-scale moisture variability for the past 18 centuries. Since the sample size is small in some portions of the time series, the chronology should be considered preliminary; the timing and duration of drought events are likely the most robust characteristics. This chronology suggests that the region experienced increased aridity during the medieval period, as did much of western North America, but that the timing and duration of drought episodes within this period were somewhat different from those in other western locations, such as the upper Colorado River basin. ?? 2010 University of Washington.
The sensitivity of the atmospheric branch of the global water cycle to temperature fluctuations at synoptic to decadal time-scales in different satellite- and model-based products

Science.gov (United States)

Nogueira, Miguel

2018-02-01

Spectral analysis of global-mean precipitation, P, evaporation, E, precipitable water, W, and surface temperature, Ts, revealed significant variability from sub-daily to multi-decadal time-scales, superposed on high-amplitude diurnal and yearly peaks. Two distinct regimes emerged from a transition in the spectral exponents, β. The weather regime covering time-scales 1-2 years, while at time-scales global-ocean and full-globe averages, ρDCCA showed large spread of the C-C importance for P and E variability amongst different datasets at multi-year time-scales, ranging from negligible (governing mechanisms.
Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

Science.gov (United States)

Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2017-12-01

Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in
Multi-decadal responses of a cod (Gadus morhua) population to human-induced trophic changes, fishing, and climate

DEFF Research Database (Denmark)

Eero, Margit; MacKenzie, Brian; Köster, Fritz

2011-01-01

to changes in fish populations can be analyzed with empirical data. In this study we investigate how climate variability and multiple human impacts (fishing, marine mammal hunting, eutrophication) have affected multi-decadal scale dynamics of cod in the Baltic Sea during the 20th century.We document...... significant climate-driven variations in cod recruitment production at multi-annual timescales, which had major impacts on population dynamics and the yields to commercial fisheries. We also quantify the roles of marine mammal predation, eutrophication, and exploitation on the development of the cod...
Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

Science.gov (United States)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-08-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over
Multi-scale glycemic variability: a link to gray matter atrophy and cognitive decline in type 2 diabetes.

Directory of Open Access Journals (Sweden)

Xingran Cui

Full Text Available Type 2 diabetes mellitus (DM accelerates brain aging and cognitive decline. Complex interactions between hyperglycemia, glycemic variability and brain aging remain unresolved. This study investigated the relationship between glycemic variability at multiple time scales, brain volumes and cognition in type 2 DM.Forty-three older adults with and 26 without type 2 DM completed 72-hour continuous glucose monitoring, cognitive tests and anatomical MRI. We described a new analysis of continuous glucose monitoring, termed Multi-Scale glycemic variability (Multi-Scale GV, to examine glycemic variability at multiple time scales. Specifically, Ensemble Empirical Mode Decomposition was used to identify five unique ultradian glycemic variability cycles (GVC1-5 that modulate serum glucose with periods ranging from 0.5-12 hrs.Type 2 DM subjects demonstrated greater variability in GVC3-5 (period 2.0-12 hrs than controls (P<0.0001, during the day as well as during the night. Multi-Scale GV was related to conventional markers of glycemic variability (e.g. standard deviation and mean glycemic excursions, but demonstrated greater sensitivity and specificity to conventional markers, and was associated with worse long-term glycemic control (e.g. fasting glucose and HbA1c. Across all subjects, those with greater glycemic variability within higher frequency cycles (GVC1-3; 0.5-2.0 hrs had less gray matter within the limbic system and temporo-parietal lobes (e.g. cingulum, insular, hippocampus, and exhibited worse cognitive performance. Specifically within those with type 2 DM, greater glycemic variability in GVC2-3 was associated with worse learning and memory scores. Greater variability in GVC5 was associated with longer DM duration and more depression. These relationships were independent of HbA1c and hypoglycemic episodes.Type 2 DM is associated with dysregulation of glycemic variability over multiple scales of time. These time-scale-dependent glycemic fluctuations
Variability and predictability of decadal mean temperature and precipitation over China in the CCSM4 last millennium simulation

Science.gov (United States)

Ying, Kairan; Frederiksen, Carsten S.; Zheng, Xiaogu; Lou, Jiale; Zhao, Tianbao

2018-02-01

The modes of variability that arise from the slow-decadal (potentially predictable) and intra-decadal (unpredictable) components of decadal mean temperature and precipitation over China are examined, in a 1000 year (850-1850 AD) experiment using the CCSM4 model. Solar variations, volcanic aerosols, orbital forcing, land use, and greenhouse gas concentrations provide the main forcing and boundary conditions. The analysis is done using a decadal variance decomposition method that identifies sources of potential decadal predictability and uncertainty. The average potential decadal predictabilities (ratio of slow-to-total decadal variance) are 0.62 and 0.37 for the temperature and rainfall over China, respectively, indicating that the (multi-)decadal variations of temperature are dominated by slow-decadal variability, while precipitation is dominated by unpredictable decadal noise. Possible sources of decadal predictability for the two leading predictable modes of temperature are the external radiative forcing, and the combined effects of slow-decadal variability of the Arctic oscillation (AO) and the Pacific decadal oscillation (PDO), respectively. Combined AO and PDO slow-decadal variability is associated also with the leading predictable mode of precipitation. External radiative forcing as well as the slow-decadal variability of PDO are associated with the second predictable rainfall mode; the slow-decadal variability of Atlantic multi-decadal oscillation (AMO) is associated with the third predictable precipitation mode. The dominant unpredictable decadal modes are associated with intra-decadal/inter-annual phenomena. In particular, the El Niño-Southern Oscillation and the intra-decadal variability of the AMO, PDO and AO are the most important sources of prediction uncertainty.
Decadal-Scale Forecasting of Climate Drivers for Marine Applications.

Science.gov (United States)

Salinger, J; Hobday, A J; Matear, R J; O'Kane, T J; Risbey, J S; Dunstan, P; Eveson, J P; Fulton, E A; Feng, M; Plagányi, É E; Poloczanska, E S; Marshall, A G; Thompson, P A

Climate influences marine ecosystems on a range of time scales, from weather-scale (days) through to climate-scale (hundreds of years). Understanding of interannual to decadal climate variability and impacts on marine industries has received less attention. Predictability up to 10 years ahead may come from large-scale climate modes in the ocean that can persist over these time scales. In Australia the key drivers of climate variability affecting the marine environment are the Southern Annular Mode, the Indian Ocean Dipole, the El Niño/Southern Oscillation, and the Interdecadal Pacific Oscillation, each has phases that are associated with different ocean circulation patterns and regional environmental variables. The roles of these drivers are illustrated with three case studies of extreme events-a marine heatwave in Western Australia, a coral bleaching of the Great Barrier Reef, and flooding in Queensland. Statistical and dynamical approaches are described to generate forecasts of climate drivers that can subsequently be translated to useful information for marine end users making decisions at these time scales. Considerable investment is still needed to support decadal forecasting including improvement of ocean-atmosphere models, enhancement of observing systems on all scales to support initiation of forecasting models, collection of important biological data, and integration of forecasts into decision support tools. Collaboration between forecast developers and marine resource sectors-fisheries, aquaculture, tourism, biodiversity management, infrastructure-is needed to support forecast-based tactical and strategic decisions that reduce environmental risk over annual to decadal time scales. © 2016 Elsevier Ltd. All rights reserved.
Multi-Decadal Oscillations of the Ocean Active Upper-Layer Heat Content

Science.gov (United States)

Byshev, Vladimir I.; Neiman, Victor G.; Anisimov, Mikhail V.; Gusev, Anatoly V.; Serykh, Ilya V.; Sidorova, Alexandra N.; Figurkin, Alexander L.; Anisimov, Ivan M.

2017-07-01

Spatial patterns in multi-decadal variability in upper ocean heat content for the last 60 years are examined using a numerical model developed at the Institute of Numerical Mathematics of Russia (INM Model) and sea water temperature-salinity data from the World Ocean Database (in: Levitus, NOAA Atlas NESDIS 66, U.S. Wash.: Gov. Printing Office, 2009). Both the model and the observational data show that the heat content of the Active Upper Layer (AUL) in particular regions of the Atlantic, Pacific and Southern oceans have experienced prominent simultaneous variations on multi-decadal (25-35 years) time scales. These variations are compared earlier revealed climatic alternations in the Northern Atlantic region during the last century (Byshev et al. in Doklady Earth Sci 438(2):887-892, 2011). We found that from the middle of 1970s to the end of 1990s the AUL heat content decreased in several oceanic regions, while the mean surface temperature increased on Northern Hemisphere continents according to IPCC (in: Stocker et al. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change, Cambridge University Press, Cambridge, 2013). This means that the climate-forcing effect of the ocean-atmosphere interaction in certain energy-active areas determines not only local climatic processes, but also have an influence on global-scale climate phenomena. Here we show that specific regional features of the AUL thermal structure are in a good agreement with climatic conditions on the adjacent continents. Further, the ocean AUL in the five distinctive regions identified in our study have resumed warming in the first decade of this century. By analogy inference from previous climate scenarios, this may signal the onset of more continental climate over mainlands.
Decadal scale droughts over northwestern Thailand over the past 448 years: links to the tropical Pacific and Indian Ocean sectors

Energy Technology Data Exchange (ETDEWEB)

Buckley, Brendan M. [Lamont-Doherty Earth Observatory, Tree-Ring Laboratory, Palisades, NY (United States); Palakit, Kritsadapan; Duangsathaporn, Khwanchai [Kasetsart University Faculty of Forestry, Laboratory of Tropical Dendrochronology, Bangkok (Thailand); Sanguantham, Prasong; Prasomsin, Patsi [Kasetsart University Faculty of Forestry, Department of Forest Management, Bangkok (Thailand)

2007-07-15

A 448-year teak chronology from northwestern Thailand is used to assess past changes in the strength of the summer monsoon. The chronology is based on 30 living trees that extend from 1604 to 2005, and a 47-stump chronology that spans from 1558 to 1903. We used methods of cross dating and chronology building that address problems specifically found in teak. The result is a robust chronology with strong signal strength back to 1600 ad, and with variability retained at the multi-decadal scale. Variability in annual growth in teak from this area is dependent on rainfall and soil moisture availability at both the beginning and end of the monsoon season as confirmed by comparisons with temperature, rainfall and PDSI data. These correlation analyses confirm that our record is a proxy for summer monsoon strength and/or duration, and highlight the importance of soil moisture availability in the seasons of transition. The chronology reveals two prominent periods of decadal-scale drought in the early and mid 1700s that correspond to persistently warm sea surface temperature anomalies in the tropical Pacific as derived from Galapagos Island coral records. Speleothem data from central India also indicate protracted periods of drought for the 1700s. While these broad-scale eighteenth-century persistent droughts may be related to protracted El Nino-like conditions in the tropical Pacific, regional climate forcing over the Indian Ocean and western Pacific sectors appears to be a strong contributor as well. Spectral analyses reveal power in the ENSO range of variability from 2.2 to 4 years, and at the multi-decadal scale at 48.5 years. (orig.)
Multi-scale variability and long-range memory in indoor Radon concentrations from Coimbra, Portugal

Science.gov (United States)

Donner, Reik V.; Potirakis, Stelios; Barbosa, Susana

2014-05-01

The presence or absence of long-range correlations in the variations of indoor Radon concentrations has recently attracted considerable interest. As a radioactive gas naturally emitted from the ground in certain geological settings, understanding environmental factors controlling Radon concentrations and their dynamics is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we re-analyze two high-resolution records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements. In order to evaluate the presence of long-range correlations and fractal scaling, we utilize a multiplicity of complementary methods, including power spectral analysis, ARFIMA modeling, classical and multi-fractal detrended fluctuation analysis, and two different estimators of the signals' fractal dimensions. Power spectra and fluctuation functions reveal some complex behavior with qualitatively different properties on different time-scales: white noise in the high-frequency part, indications of some long-range correlated process dominating time scales of several hours to days, and pronounced low-frequency variability associated with tidal and/or meteorological forcing. In order to further decompose these different scales of variability, we apply two different approaches. On the one hand, applying multi-resolution analysis based on the discrete wavelet transform allows separately studying contributions on different time scales and characterize their specific correlation and scaling properties. On the other hand, singular system analysis (SSA) provides a reconstruction of the essential modes of variability. Specifically, by considering only the first leading SSA modes, we achieve an efficient de-noising of our environmental signals, highlighting the low-frequency variations together with some distinct scaling on sub-daily time-scales resembling
Decadal variability on the Northwest European continental shelf

Science.gov (United States)

Jones, Sam; Cottier, Finlo; Inall, Mark; Griffiths, Colin

2018-02-01

Decadal scale time series of the shelf seas are important for understanding both climate and process studies. Despite numerous investigations of long-term temperature variability in the shelf seas, studies of salinity variability are few. Salt is a more conservative tracer than temperature in shallow seas, and it can reveal changes in local hydrographic conditions as well as transmitted basin-scale changes. Here, new inter-annual salinity time series on the northwest European shelf are developed and a 13 year high resolution salinity record from a coastal mooring in western Scotland is presented and analysed. We find strong temporal variability in coastal salinity on timescales ranging from tidal to inter-annual, with the magnitude of variability greatest during winter months. There is little seasonality and no significant decadal trend in the coastal time series of salinity. We propose 4 hydrographic states to explain salinity variance in the shelf area west of Scotland based on the interaction between a baroclinic coastal current and wind-forced barotropic flow: while wind forcing is important, we find that changes in the buoyancy-driven flow are more likely to influence long-term salinity observations. We calculate that during prevailing westerly wind conditions, surface waters in the Sea of the Hebrides receive a mix of 62% Atlantic origin water to 38% coastal sources. This contrasts with easterly wind conditions, during which the mix is 6% Atlantic to 94% coastal sources on average. This 'switching' between hydrographic states is expected to impact nutrient transport and therefore modify the level of primary productivity on the shelf. This strong local variability in salinity is roughly an order of magnitude greater than changes in the adjacent ocean basin, and we infer from this that Scottish coastal waters are likely to be resilient to decadal changes in ocean climate.
Multi-scale response of runoff to climate fluctuation in the headwater region of Kaidu River in Xinjiang of China

Science.gov (United States)

Bai, Ling; Chen, Zhongsheng; Xu, Jianhua; Li, Weihong

2016-08-01

Based on the hydrological and meteorological data in the headwater region of the Kaidu River during 1960-2009, the multi-scale characteristics of runoff variability were analyzed using the ensemble empirical mode decomposition method (EEMD), and the aim is to investigate the oscillation mode structure characteristics of runoff change and its response to climate fluctuation at different time scales. Results indicated that in the past 50 years, the overall runoff of Kaidu River in Xinjiang has showed a significant nonlinear upward trend, and its changes have obviously exhibited an inter-annual scale (quasi-3 and quasi-6-year) and inter-decadal scale (quasi-10 and quasi-25-year). Variance contribution rates of each component manifested that the inter-decadal change had been playing a more important role in the overall runoff change for Kaidu River, and the reconstructed inter-annual variation trend could describe the fluctuation state of the original runoff anomaly during the study period. The reconstructed inter-decadal variability effectively revealed that the runoff for Kaidu River changed over the years, namely the states of abundance and low water period appear alternately. In addition, we found that runoff has a positive correlation to precipitation and temperature at different time scales, but they are most significant and relevant at inter-decadal scale, indicating the inter-decadal scale is most suitable for investigating the responses of runoff dynamics to climate fluctuation. At the same time, the results also suggested that EEMD is an effective method to analyze the multi-scale characteristics of nonlinear and non-stationary signal.
Decadal-scale thermohaline variability in the Atlantic sector of the Southern Ocean

CSIR Research Space (South Africa)

Hutchinson, K

2016-05-01

Full Text Available . This AGEM has improved accuracy compared to traditional climatologies and other proxy methods. The AGEM for the Atlantic Southern Ocean offers an ideal technique to investigate the thermohaline variability over the past two decades in a key region for water...
Lake oxygen isotopes as recorders of North American Rocky Mountain hydroclimate: Holocene patterns and variability at multi-decadal to millennial time scales

Science.gov (United States)

Anderson, Lesleigh; Berkelhammer, Max; Barron, John A.; Steinman, Byron A.; Finney, Bruce P.; Abbott, Mark B.

2016-02-01

Lake sediment oxygen isotope records (calcium carbonate-δ18O) in the western North American Cordillera developed during the past decade provide substantial evidence of Pacific ocean-atmosphere forcing of hydroclimatic variability during the Holocene. Here we present an overview of 18 lake sediment δ18O records along with a new compilation of lake water δ18O and δ2H that are used to characterize lake sediment sensitivity to precipitation-δ18O in contrast to fractionation by evaporation. Of the 18 records, 14 have substantial sensitivity to evaporation. Two records reflect precipitation-δ18O since the middle Holocene, Jellybean and Bison Lakes, and are geographically positioned in the northern and southern regions of the study area. Their comparative analysis indicates a sequence of time-varying north-south precipitation-δ18O patterns that is evidence for a highly non-stationary influence by Pacific ocean-atmosphere processes on the hydroclimate of western North America. These observations are discussed within the context of previous research on North Pacific precipitation-δ18O based on empirical and modeling methods. The Jellybean and Bison Lake records indicate that a prominent precipitation-δ18O dipole (enriched-north and depleted-south) was sustained between ~ 3.5 and 1.5 ka, which contrasts with earlier Holocene patterns, and appears to indicate the onset of a dominant tropical control on North Pacific ocean-atmosphere dynamics. This remains the state of the system today. Higher frequency reversals of the north-south precipitation-δ18O dipole between ~ 2.5 and 1.5 ka, and during the Medieval Climate Anomaly and the Little Ice Age, also suggest more varieties of Pacific ocean-atmosphere modes than a single Pacific Decadal Oscillation (PDO) type analogue. Results indicate that further investigation of precipitation-δ18O patterns on short (observational) and long (Holocene) time scales is needed to improve our understanding of the processes that drive

Lake oxygen isotopes as recorders of North American Rocky Mountain hydroclimate: Holocene patterns and variability at multi-decadal to millennial time scales

Science.gov (United States)

Anderson, Lesleigh; Max Berkelhammer,; Barron, John A.; Steinman, Byron A.; Finney, Bruce P.; Abbott, Mark B.

2016-01-01

Lake sediment oxygen isotope records (calcium carbonate-δ18O) in the western North American Cordillera developed during the past decade provide substantial evidence of Pacific ocean–atmosphere forcing of hydroclimatic variability during the Holocene. Here we present an overview of 18 lake sediment δ18O records along with a new compilation of lake water δ18O and δ2H that are used to characterize lake sediment sensitivity to precipitation-δ18O in contrast to fractionation by evaporation. Of the 18 records, 14 have substantial sensitivity to evaporation. Two records reflect precipitation-δ18O since the middle Holocene, Jellybean and Bison Lakes, and are geographically positioned in the northern and southern regions of the study area. Their comparative analysis indicates a sequence of time-varying north–south precipitation-δ18O patterns that is evidence for a highly non-stationary influence by Pacific ocean–atmosphere processes on the hydroclimate of western North America. These observations are discussed within the context of previous research on North Pacific precipitation-δ18O based on empirical and modeling methods. The Jellybean and Bison Lake records indicate that a prominent precipitation-δ18O dipole (enriched-north and depleted-south) was sustained between ~ 3.5 and 1.5 ka, which contrasts with earlier Holocene patterns, and appears to indicate the onset of a dominant tropical control on North Pacific ocean–atmosphere dynamics. This remains the state of the system today. Higher frequency reversals of the north–south precipitation-δ18O dipole between ~ 2.5 and 1.5 ka, and during the Medieval Climate Anomaly and the Little Ice Age, also suggest more varieties of Pacific ocean–atmosphere modes than a single Pacific Decadal Oscillation (PDO) type analogue. Results indicate that further investigation of precipitation-δ18O patterns on short (observational) and long (Holocene) time scales is needed to improve our understanding of the
Tropical Pacific forcing on decadal-to-centennial NAO-dominated precipitation variability in northern Mediterranean over the past 6500 years

Science.gov (United States)

Hu, H. M.; Shen, C. C.; Michel, V.; Jiang, X.; Mii, H. S.; Wang, Y.; Valensi, P.

2017-12-01

We present a multi-annual-resolved absolute-dated stalagmite-inferred precipitation record, with age precision as good as ±2 years, from northern Italy, to reflect North Atlantic Oscillation (NAO) dynamics since 6.5 ka (thousand years ago, before 1950 C.E.). Our record features millennial precipitation fluctuations punctuated by several centennial-scale drought periods centered at 5.6, 6.2, 4.2, 3.0 and 2.3 ka. The phase relationship with previous NAO-sensitive records suggests a multi-millennial southward migration of the northern Westerlies and enhanced NAO variability from the middle- to late-Holocene. We also found the multi-decadal to centennial rainfall amount could dramatically vary within few decades, possibly affecting ancient Mediterranean civilizations. Concurrence between northern Mediterranean precipitation and western tropical Pacific sea surface temperature records suggests the remote forcing on this NAO-dominated rainfall. We argue that the irregular NAO change nowadays could be related to high frequency of El Niño-Southern Oscillation events and might cause an inevitable abrupt hydroclimate change and irreparable impacts on the regional human society in the near future.
Decadal- to Centennial-Scale Variations in Anchovy Biomass in the Last 250 Years Inferred From Scales Preserved in Laminated Sediments off the Coast of Pisco, Peru

Science.gov (United States)

Salvatteci, R.; Field, D.; Gutierrez, D.; Baumgartner, T.; Ferreira, V.; Velazco, F.; Niquen, M.; Guevara, R.; Sifeddine, A.; Ortlieb, L.

2005-12-01

The highly productive upwelling environment off the coast of Peru sustains one of the world's largest fisheries, the Peruvian anchoveta ( Engraulis ringens), but variability on interannual to decadal timescales results in dramatic variations in catch. We quantified variations in anchovy scale abundance preserved in laminated sediments collected at 300 m depth of the Peruvian margin (near Pisco, central Peru) to infer decadal- to centennial-scale population variability prior to the development of the fishery. High-resolution subsampling of 2.5 - 8.2 mm was done following the laminated structure of the core. A chronology based on downcore excess 210Pb activities and 14C-AMS ages indicate that samples represent an estimated 1-7 years in time. Anchovy scale deposition is correlated with anchovy landings at Pisco, indicating that scale deposition can be used as a proxy of (at least) local biomass. A small, but significant, reduction in anchovy scale width (0.2 mm) after the development of the fishery suggests a small effect of the fishery on anchovy size distributions. While decadal-scale variability in anchovy scale deposition is persistent throughout the record, a dramatic increase in scale flux occurred around 1860 A.D. and persists for approximately a century. Our results indicate that centennial-scale variability composes a large portion of the variability. However, decadal-scale variability associated with the Pacific Decadal Oscillation is not correlated with the inferred biomass variability prior to the development of the fishery. Shifts in the distribution of the population may account for an additional component of the variability in scale deposition.
Societal Impacts of Natural Decadal Climate Variability - The Pacemakers of Civilizations

Science.gov (United States)

Mehta, V. M.

2017-12-01

Natural decadal climate variability (DCV) is one of the oldest areas of climate research. Building on centuries-long literature, a substantial body of research has emerged in the last two to three decades, focused on understanding causes, mechanisms, and impacts of DCV. Several DCV phenomena - the Pacific Decadal Oscillation (PDO) or the Interdecadal Pacific Oscillation (IPO), tropical Atlantic sea-surface temperature gradient variability (TAG for brevity), West Pacific Warm Pool variability, and decadal variability of El Niño-La Niña events - have been identified in observational records; and are associated with variability of worldwide atmospheric circulations, water vapor transport, precipitation, and temperatures; and oceanic circulations, salinity, and temperatures. Tree-ring based drought index data going back more than 700 years show presence of decadal hydrologic cycles (DHCs) in North America, Europe, and South Asia. Some of these cycles were associated with the rise and fall of civilizations, large-scale famines which killed millions of people, and acted as catalysts for socio-political revolutions. Instrument-measured data confirm presence of such worldwide DHCs associated with DCV phenomena; and show these DCV phenomena's worldwide impacts on river flows, crop productions, inland water-borne transportation, hydro-electricity generation, and agricultural irrigation. Fish catch data also show multiyear to decadal catch variability associated with these DCV phenomena in all oceans. This talk, drawn from my recently-published book (Mehta, V.M., 2017: Natural Decadal Climate Variability: Societal Impacts. CRC Press, Boca Raton, Florida, 326 pp.), will give an overview of worldwide impacts of DCV phenomena, with specific examples of socio-economic-political impacts. This talk will also describe national and international security implications of such societal impacts, and worldwide food security implications. The talk will end with an outline of needed
Decadal summer drought frequency in China: the increasing influence of the Atlantic Multi-decadal Oscillation

International Nuclear Information System (INIS)

Qian, Chengcheng; Yu, Jin-Yi; Chen, Ge

2014-01-01

Decadal variations in summer drought events during 1956–2005 are examined over Eastern China to identify their leading variability modes and their linkages to the Pacific Decadal Oscillation (PDO), Atlantic Multi-decadal Oscillation (AMO), and global warming. The PDO influence is found to dominate China drought frequency from the 1960s to early 1990s via modulating the Western Pacific Subtropical High and the Mongolian High. The four-pole drought pattern produced by the PDO diminished after the early 1990s, being replaced by a dipolar drought pattern that is produced by the AMO via a Eurasian wave train emanating from North Atlantic to China. The increasing influence of the AMO on China drought since the early 1990s is further shown to be a consequence of global warming. This study indicates that the early 1990s is a time when the Atlantic began to exert a stronger influence on climate over China and even larger part of Asia. (letter)
Mesoscale to Synoptic Scale Cloud Variability

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Rossow, William B.

1998-01-01

The atmospheric circulation and its interaction with the oceanic circulation involve non-linear and non-local exchanges of energy and water over a very large range of space and time scales. These exchanges are revealed, in part, by the related variations of clouds, which occur on a similar range of scales as the atmospheric motions that produce them. Collection of comprehensive measurements of the properties of the atmosphere, clouds and surface allows for diagnosis of some of these exchanges. The use of a multi-satellite-network approach by the International Satellite Cloud Climatology Project (ISCCP) comes closest to providing complete coverage of the relevant range space and time scales over which the clouds, atmosphere and ocean vary. A nearly 15-yr dataset is now available that covers the range from 3 hr and 30 km to decade and planetary. This paper considers three topics: (1) cloud variations at the smallest scales and how they may influence radiation-cloud interactions, and (2) cloud variations at "moderate" scales and how they may cause natural climate variability, and (3) cloud variations at the largest scales and how they affect the climate. The emphasis in this discussion is on the more mature subject of cloud-radiation interactions. There is now a need to begin similar detailed diagnostic studies of water exchange processes.
The influence of anthropogenic aerosol on multi-decadal variations of historical global climate

International Nuclear Information System (INIS)

Wilcox, L J; Highwood, E J; Dunstone, N J

2013-01-01

Analysis of single forcing runs from CMIP5 (the fifth Coupled Model Intercomparison Project) simulations shows that the mid-twentieth century temperature hiatus, and the coincident decrease in precipitation, is likely to have been influenced strongly by anthropogenic aerosol forcing. Models that include a representation of the indirect effect of aerosol better reproduce inter-decadal variability in historical global-mean near-surface temperatures, particularly the cooling in the 1950s and 1960s, compared to models with representation of the aerosol direct effect only. Models with the indirect effect also show a more pronounced decrease in precipitation during this period, which is in better agreement with observations, and greater inter-decadal variability in the inter-hemispheric temperature difference. This study demonstrates the importance of representing aerosols, and their indirect effects, in general circulation models, and suggests that inter-model diversity in aerosol burden and representation of aerosol–cloud interaction can produce substantial variation in simulations of climate variability on multi-decadal timescales. (letter)
A novel way to detect correlations on multi-time scales, with temporal evolution and for multi-variables

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Yuan, Naiming; Xoplaki, Elena; Zhu, Congwen; Luterbacher, Juerg

2016-06-01

In this paper, two new methods, Temporal evolution of Detrended Cross-Correlation Analysis (TDCCA) and Temporal evolution of Detrended Partial-Cross-Correlation Analysis (TDPCCA), are proposed by generalizing DCCA and DPCCA. Applying TDCCA/TDPCCA, it is possible to study correlations on multi-time scales and over different periods. To illustrate their properties, we used two climatological examples: i) Global Sea Level (GSL) versus North Atlantic Oscillation (NAO); and ii) Summer Rainfall over Yangtze River (SRYR) versus previous winter Pacific Decadal Oscillation (PDO). We find significant correlations between GSL and NAO on time scales of 60 to 140 years, but the correlations are non-significant between 1865-1875. As for SRYR and PDO, significant correlations are found on time scales of 30 to 35 years, but the correlations are more pronounced during the recent 30 years. By combining TDCCA/TDPCCA and DCCA/DPCCA, we proposed a new correlation-detection system, which compared to traditional methods, can objectively show how two time series are related (on which time scale, during which time period). These are important not only for diagnosis of complex system, but also for better designs of prediction models. Therefore, the new methods offer new opportunities for applications in natural sciences, such as ecology, economy, sociology and other research fields.
Impact of climatic change on ocean carbon fluxes. Role of the decadal variability

International Nuclear Information System (INIS)

Seferian, Roland

2013-01-01

Since the industrial revolution, oceans have absorbed roughly one quarter of the anthropogenic emissions of CO 2 , slowing down climate change. The evolution of the ocean carbon sink, paralleled to the anthropogenic CO 2 emissions, is ruled by the CO 2 as well as climate. Influence of atmospheric CO 2 in the recent evolution of the ocean carbon sink is well understood whilst this is not the case for the climate's one. Indeed, some authors claim that the recent variations of the ocean CO 2 sink can be attributed to climate change, whereas some others suggest that these latter are controlled by a decadal variability, which is poorly understood. In this thesis, we address question relative to the role of the decadal variability of the ocean carbon fluxes through the mean of numerical modeling. On one hand, we have demonstrated that ocean carbon fluxes exhibit decadal fluctuations within the high latitudes oceans. These fluctuations displays modes of 10 to 50-year long which account for 20 to 40% of the year-to-year variability. Thanks to Detection and Attribution methods applied to RECCAP project's reconstructions (1960-2005), we have then assessed whether the occurrence of fluctuations at decadal time scale could hamper the detection of the climate contribution to the recent evolution of ocean carbon fluxes. We have shown that the climate contribution is indeed not detected in the high latitude oceans due to the presence of decadal mode of variability. In the low latitude oceans instead, the weaker fluctuations of ocean carbon fluxes at decadal time scale favor the detection of climate influence in the recent variations of the CO 2 fluxes. (author) [fr
Multi-Decadal Coastal Behavioural States From A Fusion Of Geohistorical Conceptual Modelling With 2-D Morphodynamic Modelling

Science.gov (United States)

Goodwin, I. D.; Mortlock, T.

2016-02-01

Geohistorical archives of shoreline and foredune planform geometry provides a unique evidence-based record of the time integral response to coupled directional wave climate and sediment supply variability on annual to multi-decadal time scales. We develop conceptual shoreline modelling from the geohistorical shoreline archive using a novel combination of methods, including: LIDAR DEM and field mapping of coastal geology; a decadal-scale climate reconstruction of sea-level pressure, marine windfields, and paleo-storm synoptic type and frequency, and historical bathymetry. The conceptual modelling allows for the discrimination of directional wave climate shifts and the relative contributions of cross-shore and along-shore sand supply rates at multi-decadal resolution. We present regional examples from south-eastern Australia over a large latitudinal gradient from subtropical Queensland (S 25°) to mid-latitude Bass Strait (S 40°) that illustrate the morphodynamic evolution and reorganization to wave climate change. We then use the conceptual modeling to inform a two-dimensional coupled spectral wave-hydrodynamic-morphodynamic model to investigate the shoreface response to paleo-directional wind and wave climates. Unlike one-line shoreline modelling, this fully dynamical approach allows for the investigation of cumulative and spatial bathymetric change due to wave-induced currents, as well as proxy-shoreline change. The fusion of the two modeling approaches allows for: (i) the identification of the natural range of coastal planform geometries in response to wave climate shifts; and, (ii) the decomposition of the multidecadal coastal change into the cross-shore and along-shore sand supply drivers, according to the best-matching planforms.
Drivers of annual to decadal streamflow variability in the lower Colorado River Basin

Science.gov (United States)

Lambeth-Beagles, R. S.; Troch, P. A.

2010-12-01

increasing evaporation and transpiration processes. Second, annual variability in streamflow is not statistically correlated with annual temperature variability but appears to be highly correlated with annual precipitation variability. This implies that on a year-to-year basis, changes in streamflow volumes are directly affected by precipitation and not temperature. Future development of a predictive streamflow model will need to take into consideration these two processes to obtain accurate results. In order to extend predictive skill to the multi-year scale relationships between precipitation, temperature and persistent climate indices such as the Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation and El Nino/Southern Oscillation will need to be examined.
Current and Future Decadal Trends in the Oceanic Carbon Uptake Are Dominated by Internal Variability

Science.gov (United States)

Li, Hongmei; Ilyina, Tatiana

2018-01-01

We investigate the internal decadal variability of the ocean carbon uptake using 100 ensemble simulations based on the Max Planck Institute Earth system model (MPI-ESM). We find that on decadal time scales, internal variability (ensemble spread) is as large as the forced temporal variability (ensemble mean), and the largest internal variability is found in major carbon sink regions, that is, the 50-65°S band of the Southern Ocean, the North Pacific, and the North Atlantic. The MPI-ESM ensemble produces both positive and negative 10 year trends in the ocean carbon uptake in agreement with observational estimates. Negative decadal trends are projected to occur in the future under RCP4.5 scenario. Due to the large internal variability, the Southern Ocean and the North Pacific require the most ensemble members (more than 53 and 46, respectively) to reproduce the forced decadal trends. This number increases up to 79 in future decades as CO2 emission trajectory changes.
Indo-Pacific sea level variability during recent decades

Science.gov (United States)

Yamanaka, G.; Tsujino, H.; Nakano, H.; Urakawa, S. L.; Sakamoto, K.

2016-12-01

Decadal variability of sea level in the Indo-Pacific region is investigated using a historical OGCM simulation. The OGCM driven by the atmospheric forcing removing long-term trends clearly exhibits decadal sea level variability in the Pacific Ocean, which is associated with eastern tropical Pacific thermal anomalies. During the period of 1977-1987, the sea level anomalies are positive in the eastern equatorial Pacific and show deviations from a north-south symmetric distribution, with strongly negative anomalies in the western tropical South Pacific. During the period of 1996-2006, in contrast, the sea level anomalies are negative in the eastern equatorial Pacific and show a nearly north-south symmetric pattern, with positive anomalies in both hemispheres. Concurrently, sea level anomalies in the south-eastern Indian Ocean vary with those in the western tropical Pacific. These sea level variations are closely related to large-scale wind fields. Indo-Pacific sea level distributions are basically determined by wind anomalies over the equatorial region as well as wind stress curl anomalies over the off-equatorial region.
Multi-scale linkages of winter drought variability to ENSO and the Arctic Oscillation: A case study in Shaanxi, North China

Science.gov (United States)

Liu, Zhiyong; Zhang, Xin; Fang, Ruihong

2018-02-01

Understanding the potential connections between climate indices such as the El Niño-Southern Oscillation (ENSO) and Arctic Oscillation (AO) and drought variability will be beneficial for making reasonable predictions or assumptions about future regional droughts, and provide valuable information to improve water resources planning and design for specific regions of interest. This study is to examine the multi-scale relationships between winter drought variability over Shaanxi (North China) and both ENSO and AO during the period 1960-2009. To accomplish this, we first estimated winter dryness/wetness conditions over Shaanxi based on the self-calibrating Palmer drought severity index (PDSI). Then, we identified the spatiotemporal variability of winter dryness/wetness conditions in the study area by using the empirical orthogonal function (EOF). Two primary sub-regions of winter dryness/wetness conditions across Shaanxi were identified. We further examined the periodical oscillations of dryness/wetness conditions and the multi-scale relationships between dryness/wetness conditions and both ENSO and AO in winter using wavelet analysis. The results indicate that there are inverse multi-scale relations between winter dryness/wetness conditions and ENSO (according to the wavelet coherence) for most of the study area. Moreover, positive multi-scale relations between winter dryness/wetness conditions and AO are mainly observed. The results could be beneficial for making reasonable predictions or assumptions about future regional droughts and provide valuable information to improve water resources planning and design within this study area. In addition to the current study area, this study may also offer a useful reference for other regions worldwide with similar climate conditions.
Relação dos sistemas de monção com as variabilidades tropical interanual e multi-decenal Relations of the monsoon systems to the tropical multi-decadal and interannual variabilities

Directory of Open Access Journals (Sweden)

Sâmia Regina Garcia

2009-03-01

Full Text Available A variabilidade da circulação tropical, com ênfase nos sistemas monçônicos, é examinada usando diversas variáveis para o período de 1948-1999. A componente monçônica do potencial de velocidade em 200 hPa (χ-transiente, o desvio da média anual do desvio da média zonal, é o parâmetro chave usado para obter os modos monçônicos. A análise de Funções Ortogonais Empíricas (EOF do χ-transiente fornece dois modos separados. O primeiro modo descreve a variabilidade multi-decenal dos sistemas monçônicos da América do Sul e do Pacífico oeste. Esse modo, chamado monçônico multi-decenal (MMD, ocorre por todo o ano e contém a variabilidade multi-decenal relacionada à dinâmica da Oscilação Decenal do Pacífico (ODP. O segundo modo descreve as variações interanuais opostas entre a Ásia, África e oceano Índico e a região do oeste dos Estados Unidos, México e Pacífico leste. Esse modo, chamado modo interanual (MIA apresenta algumas similaridades com o modo tropical interanual El Niño - Oscilação Sul. Alguns aspectos desses modos, incluindo sua circulação e características termodinâmicas são discutidas aqui. Finalmente, índices baseados nos padrões das configurações espaciais desses modos são construídos. A eficiência desses índices para fins de monitoramento é analisada. Logo, trata-se de um novo aspecto não proposto em trabalhos anteriores.Tropical circulation variability, with emphasis on the monsoon systems is examined using several variables for the 1948-1999 period. The monsoon component in the 200 hPa velocity potential (transient-χ, the deviation from the annual mean of the zonal deviation field, is the key parameter used here to obtain the monsoon modes. The Empirical Orthogonal Function (EOF analysis of the transient-χ yields two separate modes. The first mode describes the multi-decadal variability of the monsoon systems in South America and in the western Pacific. This mode, called the multi-decadal
Separating decadal global water cycle variability from sea level rise.

Science.gov (United States)

Hamlington, B D; Reager, J T; Lo, M-H; Karnauskas, K B; Leben, R R

2017-04-20

Under a warming climate, amplification of the water cycle and changes in precipitation patterns over land are expected to occur, subsequently impacting the terrestrial water balance. On global scales, such changes in terrestrial water storage (TWS) will be reflected in the water contained in the ocean and can manifest as global sea level variations. Naturally occurring climate-driven TWS variability can temporarily obscure the long-term trend in sea level rise, in addition to modulating the impacts of sea level rise through natural periodic undulation in regional and global sea level. The internal variability of the global water cycle, therefore, confounds both the detection and attribution of sea level rise. Here, we use a suite of observations to quantify and map the contribution of TWS variability to sea level variability on decadal timescales. In particular, we find that decadal sea level variability centered in the Pacific Ocean is closely tied to low frequency variability of TWS in key areas across the globe. The unambiguous identification and clean separation of this component of variability is the missing step in uncovering the anthropogenic trend in sea level and understanding the potential for low-frequency modulation of future TWS impacts including flooding and drought.
Contribution to the discussion of P.M. Fayers and David J. Hand: Causal variables, indicator variables and measurement scales: an example from quality of life

DEFF Research Database (Denmark)

Keiding, Niels

2002-01-01

Causal variables; Clinimetric scales; Composite scales; Construct validity; Measurement scales; Multi-item scales; Quality-of-life instruments......Causal variables; Clinimetric scales; Composite scales; Construct validity; Measurement scales; Multi-item scales; Quality-of-life instruments...
Multi-year Droughts in California in the Last Two Decades

Science.gov (United States)

Myoung, B.; Kafatos, M.

2016-12-01

Multi-year droughts in California including the notorious 2013-2014 drought became serious problems recently, causing significant socio-economic damages. In the present study, focusing on the three multi-year droughts in California, i.e., 1999-2002, 2007-2009, and 2012-2014, during the recent two decades (1995-2014), we compared and investigated their characteristics of the atmosphere and the oceans. By positioning abnormally strong anticyclonic circulations at 500 hPa over the North Pacific, the droughts seem to start around strong La Niña years and continued or intensified until the year prior to an El Niño. While precipitation decreases in La Niña years have been well documented previously, the intensification of droughts in the later period has not. The Empirical Orthogonal Function (EOF) and correlation analyses suggest that, around strong La Niña years, the first EOF mode (EOF1) of the 500 hPa height is active, while the second EOF mode (EOF2) becomes active in moderate/weak La Nina years. It is also found that while EOF1 is sensitive to SST variability in the central Pacific which is associated with the major ENSO events, EOF2 is sensitive to that in the western/South Pacific. Relations to various climate variability other than ENSO, e.g., Pacific Decadal Oscillation (PDO), Tropical/Northern Hemisphere (TNH), Pacific/North American (PNA), and North Atlantic Oscillation (NAO), are also examined.
Pacific Decadal Variability and Central Pacific Warming El Niño in a Changing Climate

Energy Technology Data Exchange (ETDEWEB)

Di Lorenzo, Emanuele [Georgia Inst. of Technology, Atlanta, GA (United States)

2015-02-27

This research aimed at understanding the dynamics controlling decadal variability in the Pacific Ocean and its interactions with global-scale climate change. The first goal was to assess how the dynamics and statistics of the El Niño Southern Oscillation and the modes of Pacific decadal variability are represented in global climate models used in the IPCC. The second goal was to quantify how decadal dynamics are projected to change under continued greenhouse forcing, and determine their significance in the context of paleo-proxy reconstruction of long-term climate.
Multi-Scale Models for the Scale Interaction of Organized Tropical Convection

Science.gov (United States)

Yang, Qiu

Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.

Marine proxy evidence linking decadal North Pacific and Atlantic climate

Energy Technology Data Exchange (ETDEWEB)

Hetzinger, S. [University of Toronto Mississauga, CPS-Department, Mississauga, ON (Canada); Leibniz Institute of Marine Sciences, IFM-GEOMAR, Kiel (Germany); Halfar, J. [University of Toronto Mississauga, CPS-Department, Mississauga, ON (Canada); Mecking, J.V.; Keenlyside, N.S. [Leibniz Institute of Marine Sciences, IFM-GEOMAR, Kiel (Germany); University of Bergen, Geophysical Institute and Bjerknes Centre for Climate Research, Bergen (Norway); Kronz, A. [University of Goettingen, Geowissenschaftliches Zentrum, Goettingen (Germany); Steneck, R.S. [University of Maine, Darling Marine Center, Walpole, ME (United States); Adey, W.H. [Smithsonian Institution, Department of Botany, Washington, DC (United States); Lebednik, P.A. [ARCADIS U.S. Inc., Walnut Creek, CA (United States)

2012-09-15

Decadal- to multidecadal variability in the extra-tropical North Pacific is evident in 20th century instrumental records and has significant impacts on Northern Hemisphere climate and marine ecosystems. Several studies have discussed a potential linkage between North Pacific and Atlantic climate on various time scales. On decadal time scales no relationship could be confirmed, potentially due to sparse instrumental observations before 1950. Proxy data are limited and no multi-centennial high-resolution marine geochemical proxy records are available from the subarctic North Pacific. Here we present an annually-resolved record (1818-1967) of Mg/Ca variations from a North Pacific/Bering Sea coralline alga that extends our knowledge in this region beyond available data. It shows for the first time a statistically significant link between decadal fluctuations in sea-level pressure in the North Pacific and North Atlantic. The record is a lagged proxy for decadal-scale variations of the Aleutian Low. It is significantly related to regional sea surface temperature and the North Atlantic Oscillation (NAO) index in late boreal winter on these time scales. Our data show that on decadal time scales a weaker Aleutian Low precedes a negative NAO by several years. This atmospheric link can explain the coherence of decadal North Pacific and Atlantic Multidecadal Variability, as suggested by earlier studies using climate models and limited instrumental data. (orig.)
Multi-decadal modulations in the Aleutian-Icelandic Low seesaw and the axial symmetry of the Arctic Oscillation signature, as revealed in the 20th century reanalysis

Directory of Open Access Journals (Sweden)

Ning Shi

2014-08-01

Full Text Available Seesaw relationship in intensity between the surface Aleutian and Icelandic Lows (AIS is a manifestation of atmospheric teleconnection that bridges the interannual variability over the Pacific and Atlantic in particular winter months. Analysis of the 20th Century Reanalysis data reveals that the strength and timing of AIS have undergone multi-decadal modulations in conjunction with those in structure of the Arctic Oscillation (AO signature, extracted in the leading mode of interannual sea-level pressure (SLP variability over the extratropical Northern Hemisphere. Specifically, events of what may be called ‘pure AO’, in which SLP anomalies exhibit a high degree of axial symmetry in association with in-phase SLP variability between the midlatitude Atlantic and Pacific, tended to occur during multi-decadal periods in which the inter-basin teleconnection through AIS was active under the enhanced interannual variability of the Aleutian Low. In contrast, the axial symmetry of the AO pattern was apparently reduced during a multi-decadal period in which the AIS teleconnection was inactive under the weakened interannual variability of the Aleutian Low. In this period, the leading mode of interannual SLP variability represented a meridional seesaw between the Atlantic and Arctic, which resembles SLP anomaly pattern associated with the cold-ocean/warm-land (COWL temperature pattern. These multi-decadal modulations in interannual AIS signal and the axial symmetry of the interannual AO pattern occurred under multi-decadal changes in the background state that also represented the polarity changes of the COWL-like anomaly pattern.
A conditional stochastic weather generator for seasonal to multi-decadal simulations

Science.gov (United States)

Verdin, Andrew; Rajagopalan, Balaji; Kleiber, William; Podestá, Guillermo; Bert, Federico

2018-01-01

We present the application of a parametric stochastic weather generator within a nonstationary context, enabling simulations of weather sequences conditioned on interannual and multi-decadal trends. The generalized linear model framework of the weather generator allows any number of covariates to be included, such as large-scale climate indices, local climate information, seasonal precipitation and temperature, among others. Here we focus on the Salado A basin of the Argentine Pampas as a case study, but the methodology is portable to any region. We include domain-averaged (e.g., areal) seasonal total precipitation and mean maximum and minimum temperatures as covariates for conditional simulation. Areal covariates are motivated by a principal component analysis that indicates the seasonal spatial average is the dominant mode of variability across the domain. We find this modification to be effective in capturing the nonstationarity prevalent in interseasonal precipitation and temperature data. We further illustrate the ability of this weather generator to act as a spatiotemporal downscaler of seasonal forecasts and multidecadal projections, both of which are generally of coarse resolution.
Tides and Decadal Variability

Science.gov (United States)

Ray, Richard D.

2003-01-01

This paper reviews the mechanisms by which oceanic tides and decadal variability in the oceans are connected. We distinguish between variability caused by tides and variability observed in the tides themselves. Both effects have been detected at some level. The most obvious connection with decadal timescales is through the 18.6-year precession of the moon's orbit plane. This precession gives rise to a small tide of the same period and to 18.6-year modulations in the phase and amplitudes of short-period tides. The 18.6-year "node tide" is very small, no more than 2 cm anywhere, and in sea level data it is dominated by the ocean's natural Variability. Some authors have naively attributed climate variations with periods near 19 years directly to the node tide, but the amplitude of the tide is too small for this mechanism to be operative. The more likely explanation (Loder and Garrett, JGR, 83, 1967-70, 1978) is that the 18.6-y modulations in short-period tides, especially h e principal tide M2, cause variations in ocean mixing, which is then observed in temperature and other climatic indicators. Tidally forced variability has also been proposed by some authors, either in response to occasional (and highly predictable) tidal extremes or as a nonlinear low-frequency oscillation caused by interactions between short-period tides. The former mechanism can produce only short-duration events hardly more significant than normal tidal ranges, but the latter mechanism can in principle induce low-frequency oscillations. The most recent proposal of this type is by Keeling and Whorf, who highlight the 1800-year spectral peak discovered by Bond et al. (1997). But the proposal appears contrived and should be considered, in the words of Munk et al. (2002), "as the most likely among unlikely candidates."
Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

Science.gov (United States)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

2015-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, MODIS, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. HySDS is a Hybrid-Cloud Science Data System that has been developed and applied under NASA AIST, MEaSUREs, and ACCESS grants. HySDS uses the SciFlow workflow engine to partition analysis workflows into parallel tasks (e.g. segmenting by time or space) that are pushed into a durable job queue. The tasks are "pulled" from the queue by worker Virtual Machines (VM's) and executed in an on-premise Cloud (Eucalyptus or OpenStack) or at Amazon in the public Cloud or govCloud. In this way, years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the transferred data. We are using HySDS to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a MEASURES grant. We will present the architecture of HySDS, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. Our system demonstrates how one can pull A-Train variables (Levels 2 & 3) on-demand into the Amazon Cloud, and cache only those variables that are heavily used, so that any number of compute jobs can be
Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

Science.gov (United States)

Lu, M.; Lall, U.

2013-12-01

In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The
A Generalized Stability Analysis of the AMOC in Earth System Models: Implication for Decadal Variability and Abrupt Climate Change

Energy Technology Data Exchange (ETDEWEB)

Fedorov, Alexey V. [Yale Univ., New Haven, CT (United States)

2015-01-14

The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth system models, to the stability and variability of the AMOC in past climates.
Influence of climate variability versus change at multi-decadal time scales on hydrological extremes

Science.gov (United States)

Willems, Patrick

2014-05-01

Recent studies have shown that rainfall and hydrological extremes do not randomly occur in time, but are subject to multidecadal oscillations. In addition to these oscillations, there are temporal trends due to climate change. Design statistics, such as intensity-duration-frequency (IDF) for extreme rainfall or flow-duration-frequency (QDF) relationships, are affected by both types of temporal changes (short term and long term). This presentation discusses these changes, how they influence water engineering design and decision making, and how this influence can be assessed and taken into account in practice. The multidecadal oscillations in rainfall and hydrological extremes were studied based on a technique for the identification and analysis of changes in extreme quantiles. The statistical significance of the oscillations was evaluated by means of a non-parametric bootstrapping method. Oscillations in large scale atmospheric circulation were identified as the main drivers for the temporal oscillations in rainfall and hydrological extremes. They also explain why spatial phase shifts (e.g. north-south variations in Europe) exist between the oscillation highs and lows. Next to the multidecadal climate oscillations, several stations show trends during the most recent decades, which may be attributed to climate change as a result of anthropogenic global warming. Such attribution to anthropogenic global warming is, however, uncertain. It can be done based on simulation results with climate models, but it is shown that the climate model results are too uncertain to enable a clear attribution. Water engineering design statistics, such as extreme rainfall IDF or peak or low flow QDF statistics, obviously are influenced by these temporal variations (oscillations, trends). It is shown in the paper, based on the Brussels 10-minutes rainfall data, that rainfall design values may be about 20% biased or different when based on short rainfall series of 10 to 15 years length, and
Decadal Western Pacific Warm Pool Variability: A Centroid and Heat Content Study.

Science.gov (United States)

Kidwell, Autumn; Han, Lu; Jo, Young-Heon; Yan, Xiao-Hai

2017-10-13

We examine several characteristics of the Western Pacific Warm Pool (WP) in the past thirty years of mixed interannual variability and climate change. Our study presents the three-dimensional WP centroid (WPC) movement, WP heat content anomaly (HC) and WP volume (WPV) on interannual to decadal time scales. We show the statistically significant correlation between each parameter's interannual anomaly and the NINO 3, NINO 3.4, NINO 4, SOI, and PDO indices. The longitudinal component of the WPC is most strongly correlated with NINO 4 (R = 0.78). The depth component of the WPC has the highest correlation (R = -0.6) with NINO3.4. The WPV and NINO4 have an R-Value of -0.65. HC has the highest correlation with NINO3.4 (R = -0.52). During the study period of 1982-2014, the non-linear trends, derived from ensemble empirical mode decomposition (EEMD), show that the WPV, WP depth and HC have all increased. The WPV has increased by 14% since 1982 and the HC has increased from -1 × 10 8 J/m 2 in 1993 to 10 × 10 8 J/m 2 in 2014. While the largest variances in the latitudinal and longitudinal WPC locations are associated with annual and seasonal timescales, the largest variances in the WPV and HC are due to the multi-decadal non-linear trend.
Atmospheric forcing of decadal Baltic Sea level variability in the last 200 years. A statistical analysis

Energy Technology Data Exchange (ETDEWEB)

Huenicke, B. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Kuestenforschung

2008-11-06

This study aims at the estimation of the impact of different atmospheric factors on the past sealevel variations (up to 200 years) in the Baltic Sea by statistically analysing the relationship between Baltic Sea level records and observational and proxy-based reconstructed climatic data sets. The focus lies on the identification and possible quantification of the contribution of sealevel pressure (wind), air-temperature and precipitation to the low-frequency (decadal and multi-decadal) variability of Baltic Sea level. It is known that the wind forcing is the main factor explaining average Baltic Sea level variability at inter-annual to decadal timescales, especially in wintertime. In this thesis it is statistically estimated to what extent other regional climate factors contribute to the spatially heterogeneous Baltic Sea level variations around the isostatic trend at multi-decadal timescales. Although the statistical analysis cannot be completely conclusive, as the potential climate drivers are all statistically interrelated to some degree, the results indicate that precipitation should be taken into account as an explanatory variable for sea-level variations. On the one hand it has been detected that the amplitude of the annual cycle of Baltic Sea level has increased throughout the 20th century and precipitation seems to be the only factor among those analysed (wind through SLP field, barometric effect, temperature and precipitation) that can account for this evolution. On the other hand, precipitation increases the ability to hindcast inter-annual variations of sea level in some regions and seasons, especially in the Southern Baltic in summertime. The mechanism by which precipitation exerts its influence on Baltic Sea level is not ascertained in this statistical analysis due to the lack of long salinity time series. This result, however, represents a working hypothesis that can be confirmed or disproved by long simulations of the Baltic Sea system - ocean
A Decade-Long European-Scale Convection-Resolving Climate Simulation on GPUs

Science.gov (United States)

Leutwyler, D.; Fuhrer, O.; Ban, N.; Lapillonne, X.; Lüthi, D.; Schar, C.

2016-12-01

Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer designs that involve conventional multi-core CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation over Europe using the GPU-enabled COSMO version on a computational domain with 1536x1536x60 gridpoints. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss some of the advantages and prospects from using GPUs, and focus on the performance of the convection-resolving modeling approach on the European scale. Specifically we investigate the organization of convective clouds and on validate hourly rainfall distributions with various high-resolution data sets.
Santa Ana Winds of Southern California: Their Climatology and Variability Spanning 6.5 Decades from Regional Dynamical Modelling

Science.gov (United States)

Guzman-Morales, J.; Gershunov, A.

2015-12-01

Santa Ana Winds (SAWs) are an integral feature of the regional climate of Southern California/Northern Baja California region. In spite of their tremendous episodic impacts on the health, economy and mood of the region, climate-scale behavior of SAW is poorly understood. In the present work, we identify SAWs in mesoscale dynamical downscaling of a global reanalysis product and construct an hourly SAW catalogue spanning 65 years. We describe the long-term SAW climatology at relevant time-space resolutions, i.e, we developed local and regional SAW indices and analyse their variability on hourly, daily, annual, and multi-decadal timescales. Local and regional SAW indices are validated with available anemometer observations. Characteristic behaviors are revealed, e.g. the SAW intensity-duration relationship. At interdecadal time scales, we find that seasonal SAW activity is sensitive to prominent large-scale low-frequency modes of climate variability rooted in the tropical and north Pacific ocean-atmosphere system that are also known to affect the hydroclimate of this region. Lastly, we do not find any long-term trend in SAW frequency and intensity as previously reported. Instead, we identify a significant long-term trend in SAW behavior whereby contribution of extreme SAW events to total seasonal SAW activity has been increasing at the expense of moderate events. These findings motivate further investigation on SAW evolution in future climate and its impact on wildfires.
Hydroclimate variability: comparing dendroclimatic records and future GCM scenarios

International Nuclear Information System (INIS)

Lapp, S.

2008-01-01

Drought events of the 20th Century in western North America have been linked to teleconnections that influence climate variability on inter-annual and decadal to multi-decadal time scales. These teleconnections represent the changes sea surface temperatures (SSTs) in the tropical and extra-tropical regions of the Pacific Ocean, ENSO (El-Nino Southern Oscillation) and PDO (Pacific Decadal Oscillation), respectively, and the Atlantic Ocean, AMO (Atlantic Multidecadal Oscillation), and also to atmospheric circulation patterns (PNA: Pacific-North American). A network of precipitation sensitive tree-ring chronologies from Montana, Alberta, Saskatchewan and NWT highly correlate to the climate moisture index (CMI) of precipitation potential evapotranspiration (P-PET), thus, capturing the long-term hydroclimatic variability of the region. Reconstructions of annual and seasonal CMI identify drought events in previous centuries that are more extreme in magnitude, frequency and duration than recorded during the instrumental period. Variability in the future climate will include these natural climate cycles as well as modulations of these cycles affected by human induced global warming. The proxy hydroclimate records derived from tree-rings present information on decadal and multi-decadal hydroclimatic variability for the past millennium; therefore, providing a unique opportunity to validate the climate variability simulated by GCMs (Global Climate Models) on longer time scales otherwise constrained by the shorter observation records. Developing scenarios of future variability depends: 1) on our understanding of the interaction of these teleconnection; and, 2) to identify climate models that are able to accurately simulate the hydroclimatic variability as detected in the instrumental and proxy records. (author)
Arctic climate change and decadal variability

NARCIS (Netherlands)

Linden, van der Eveline C.

2016-01-01

High northern latitudes exhibit enhanced near-surface warming in a climate with increasing greenhouse gases compared to other parts of the globe, indicating an amplified climate response to external forcing. Decadal to multidecadal variability sometimes enhances and at other times reduces the
Food Price Volatility and Decadal Climate Variability

Science.gov (United States)

Brown, M. E.

2013-12-01

The agriculture system is under pressure to increase production every year as global population expands and more people move from a diet mostly made up of grains, to one with more meat, dairy and processed foods. Weather shocks and large changes in international commodity prices in the last decade have increased pressure on local food prices. This paper will review several studies that link climate variability as measured with satellite remote sensing to food price dynamics in 36 developing countries where local monthly food price data is available. The focus of the research is to understand how weather and climate, as measured by variations in the growing season using satellite remote sensing, has affected agricultural production, food prices and access to food in agricultural societies. Economies are vulnerable to extreme weather at multiple levels. Subsistence small holders who hold livestock and consume much of the food they produce are vulnerable to food production variability. The broader society, however, is also vulnerable to extreme weather because of the secondary effects on market functioning, resource availability, and large-scale impacts on employment in trading, trucking and wage labor that are caused by weather-related shocks. Food price variability captures many of these broad impacts and can be used to diagnose weather-related vulnerability across multiple sectors. The paper will trace these connections using market-level data and analysis. The context of the analysis is the humanitarian aid community, using the guidance of the USAID Famine Early Warning Systems Network and the United Nation's World Food Program in their response to food security crises. These organizations have worked over the past three decades to provide baseline information on food production through satellite remote sensing data and agricultural yield models, as well as assessments of food access through a food price database. Econometric models and spatial analysis are used
Multi-scale approach to the environmental factors effects on spatio-temporal variability of Chironomus salinarius (Diptera: Chironomidae) in a French coastal lagoon

Science.gov (United States)

Cartier, V.; Claret, C.; Garnier, R.; Fayolle, S.; Franquet, E.

2010-03-01

The complexity of the relationships between environmental factors and organisms can be revealed by sampling designs which consider the contribution to variability of different temporal and spatial scales, compared to total variability. From a management perspective, a multi-scale approach can lead to time-saving. Identifying environmental patterns that help maintain patchy distribution is fundamental in studying coastal lagoons, transition zones between continental and marine waters characterised by great environmental variability on spatial and temporal scales. They often present organic enrichment inducing decreased species richness and increased densities of opportunist species like C hironomus salinarius, a common species that tends to swarm and thus constitutes a nuisance for human populations. This species is dominant in the Bolmon lagoon, a French Mediterranean coastal lagoon under eutrophication. Our objective was to quantify variability due to both spatial and temporal scales and identify the contribution of different environmental factors to this variability. The population of C. salinarius was sampled from June 2007 to June 2008 every two months at 12 sites located in two areas of the Bolmon lagoon, at two different depths, with three sites per area-depth combination. Environmental factors (temperature, dissolved oxygen both in sediment and under water surface, sediment organic matter content and grain size) and microbial activities (i.e. hydrolase activities) were also considered as explanatory factors of chironomid densities and distribution. ANOVA analysis reveals significant spatial differences regarding the distribution of chironomid larvae for the area and the depth scales and their interaction. The spatial effect is also revealed for dissolved oxygen (water), salinity and fine particles (area scale), and for water column depth. All factors but water column depth show a temporal effect. Spearman's correlations highlight the seasonal effect
Multi-decadal Arctic sea ice roughness.

Science.gov (United States)

Tsamados, M.; Stroeve, J.; Kharbouche, S.; Muller, J. P., , Prof; Nolin, A. W.; Petty, A.; Haas, C.; Girard-Ardhuin, F.; Landy, J.

2017-12-01

The transformation of Arctic sea ice from mainly perennial, multi-year ice to a seasonal, first-year ice is believed to have been accompanied by a reduction of the roughness of the ice cover surface. This smoothening effect has been shown to (i) modify the momentum and heat transfer between the atmosphere and ocean, (ii) to alter the ice thickness distribution which in turn controls the snow and melt pond repartition over the ice cover, and (iii) to bias airborne and satellite remote sensing measurements that depend on the scattering and reflective characteristics over the sea ice surface topography. We will review existing and novel remote sensing methodologies proposed to estimate sea ice roughness, ranging from airborne LIDAR measurement (ie Operation IceBridge), to backscatter coefficients from scatterometers (ASCAT, QUICKSCAT), to multi angle maging spectroradiometer (MISR), and to laser (Icesat) and radar altimeters (Envisat, Cryosat, Altika, Sentinel-3). We will show that by comparing and cross-calibrating these different products we can offer a consistent multi-mission, multi-decadal view of the declining sea ice roughness. Implications for sea ice physics, climate and remote sensing will also be discussed.
Robustness of observation-based decadal sea level variability in the Indo-Pacific Ocean

Science.gov (United States)

Nidheesh, A. G.; Lengaigne, M.; Vialard, J.; Izumo, T.; Unnikrishnan, A. S.; Meyssignac, B.; Hamlington, B.; de Boyer Montegut, C.

2017-07-01

We examine the consistency of Indo-Pacific decadal sea level variability in 10 gridded, observation-based sea level products for the 1960-2010 period. Decadal sea level variations are robust in the Pacific, with more than 50% of variance explained by decadal modulation of two flavors of El Niño-Southern Oscillation (classical ENSO and Modoki). Amplitude of decadal sea level variability is weaker in the Indian Ocean than in the Pacific. All data sets indicate a transmission of decadal sea level signals from the western Pacific to the northwest Australian coast through the Indonesian throughflow. The southern tropical Indian Ocean sea level variability is associated with decadal modulations of ENSO in reconstructions but not in reanalyses or in situ data set. The Pacific-independent Indian Ocean decadal sea level variability is not robust but tends to be maximum in the southwestern tropical Indian Ocean. The inconsistency of Indian Ocean decadal variability across the sea level products calls for caution in making definitive conclusions on decadal sea level variability in this basin.
Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

Science.gov (United States)

Wilson, B. D.; Manipon, G.; Hua, H.

2012-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within Sci
Data fusion of multi-scale representations for structural damage detection

Science.gov (United States)

Guo, Tian; Xu, Zili

2018-01-01

Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.

A possible interrelation between Earth rotation and climatic variability at decadal time-scale

Directory of Open Access Journals (Sweden)

Leonid Zotov

2016-05-01

Full Text Available Using multichannel singular spectrum analysis (MSSA we decomposed climatic time series into principal components, and compared them with Earth rotation parameters. The global warming trends were initially subtracted. Similar quasi 60 and 20 year periodic oscillations have been found in the global mean Earth temperature anomaly (HadCRUT4 and global mean sea level (GMSL. Similar cycles were also found in Earth rotation variation. Over the last 160 years multi-decadal change of Earth's rotation velocity is correlated with the 60-year temperature anomaly, and Chandler wobble envelope reproduces the form of the 60-year oscillation noticed in GMSL. The quasi 20-year oscillation observed in GMSL is correlated with the Chandler wobble excitation. So, we assume that Earth's rotation and climate indexes are connected. Despite of all the clues hinting this connection, no sound conclusion can be done as far as ocean circulation modelling is not able to correctly catch angular momentum of the oscillatory modes.
Collaborative Research: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic

Energy Technology Data Exchange (ETDEWEB)

Gutowski, William J. [Iowa State Univ., Ames, IA (United States)

2017-12-28

This project developed and applied a regional Arctic System model for enhanced decadal predictions. It built on successful research by four of the current PIs with support from the DOE Climate Change Prediction Program, which has resulted in the development of a fully coupled Regional Arctic Climate Model (RACM) consisting of atmosphere, land-hydrology, ocean and sea ice components. An expanded RACM, a Regional Arctic System Model (RASM), has been set up to include ice sheets, ice caps, mountain glaciers, and dynamic vegetation to allow investigation of coupled physical processes responsible for decadal-scale climate change and variability in the Arctic. RASM can have high spatial resolution (~4-20 times higher than currently practical in global models) to advance modeling of critical processes and determine the need for their explicit representation in Global Earth System Models (GESMs). The pan-Arctic region is a key indicator of the state of global climate through polar amplification. However, a system-level understanding of critical arctic processes and feedbacks needs further development. Rapid climate change has occurred in a number of Arctic System components during the past few decades, including retreat of the perennial sea ice cover, increased surface melting of the Greenland ice sheet, acceleration and thinning of outlet glaciers, reduced snow cover, thawing permafrost, and shifts in vegetation. Such changes could have significant ramifications for global sea level, the ocean thermohaline circulation and heat budget, ecosystems, native communities, natural resource exploration, and commercial transportation. The overarching goal of the RASM project has been to advance understanding of past and present states of arctic climate and to improve seasonal to decadal predictions. To do this the project has focused on variability and long-term change of energy and freshwater flows through the arctic climate system. The three foci of this research are: - Changes
Meridional Modes and Increasing Pacific Decadal Variability Under Anthropogenic Forcing

Science.gov (United States)

Liguori, Giovanni; Di Lorenzo, Emanuele

2018-01-01

Pacific decadal variability has strong impacts on the statistics of weather, atmosphere extremes, droughts, hurricanes, marine heatwaves, and marine ecosystems. Sea surface temperature (SST) observations show that the variance of the El Niño-like decadal variability has increased by 30% (1920-2015) with a stronger coupling between the major Pacific climate modes. Although we cannot attribute these trends to global climate change, the examination of 30 members of the Community Earth System Model Large Ensemble (LENS) forced with the RCP8.5 radiative forcing scenario (1920-2100) suggests that significant anthropogenic trends in Pacific decadal variance will emerge by 2020 in response to a more energetic North Pacific Meridional Mode (PMM)—a well-known El Niño precursor. The PMM is a key mechanism for energizing and coupling tropical and extratropical decadal variability. In the LENS, the increase in PMM variance is consistent with an intensification of the winds-evaporation-SST thermodynamic feedback that results from a warmer mean climate.
Continent-scale global change attribution in European birds - combining annual and decadal time scales

DEFF Research Database (Denmark)

Jørgensen, Peter Søgaard; Böhning-Gaese, Katrin; Thorup, Kasper

2016-01-01

foundation for attributing species responses to global change may be achieved by complementing an attributes-based approach by one estimating the relationship between repeated measures of organismal and environmental changes over short time scales. To assess the benefit of this multiscale perspective, we...... on or in the peak of the breeding season with the largest effect sizes observed in cooler parts of species' climatic ranges. Our results document the potential of combining time scales and integrating both species attributes and environmental variables for global change attribution. We suggest such an approach......Species attributes are commonly used to infer impacts of environmental change on multiyear species trends, e.g. decadal changes in population size. However, by themselves attributes are of limited value in global change attribution since they do not measure the changing environment. A broader...
Contribution of solar radiation to decadal temperature variability over land.

Science.gov (United States)

Wang, Kaicun; Dickinson, Robert E

2013-09-10

Global air temperature has become the primary metric for judging global climate change. The variability of global temperature on a decadal timescale is still poorly understood. This paper examines further one suggested hypothesis, that variations in solar radiation reaching the surface (Rs) have caused much of the observed decadal temperature variability. Because Rs only heats air during the day, its variability is plausibly related to the variability of diurnal temperature range (daily maximum temperature minus its minimum). We show that the variability of diurnal temperature range is consistent with the variability of Rs at timescales from monthly to decadal. This paper uses long comprehensive datasets for diurnal temperature range to establish what has been the contribution of Rs to decadal temperature variability. It shows that Rs over land globally peaked in the 1930s, substantially decreased from the 1940s to the 1970s, and changed little after that. Reduction of Rs caused a reduction of more than 0.2 °C in mean temperature during May to October from the 1940s through the 1970s, and a reduction of nearly 0.2 °C in mean air temperature during November to April from the 1960s through the 1970s. This cooling accounts in part for the near-constant temperature from the 1930s into the 1970s. Since then, neither the rapid increase in temperature from the 1970s through the 1990s nor the slowdown of warming in the early twenty-first century appear to be significantly related to changes of Rs.
Exploring the Links in Monthly to Decadal Variability of the Atmospheric Water Balance Over the Wettest Regions in ERA-20C

Science.gov (United States)

Nogueira, M.

2017-10-01

Monthly-to-decadal variability of the regional precipitation over Intertropical Convergence Zone and north-Atlantic and north-Pacific storm tracks was investigated using ERA-20C reanalysis. Satellite-based precipitation (P) and evaporation (E) climatological patterns were well reproduced by ERA-20C. Regional P and E monthly time series displayed 20% differences, but these decreased rapidly with time scale ( 10% at yearly time scales). Spectral analysis showed good scale-by-scale statistical agreement between ERA-20C and observations. Using ERA-Interim showed no improvement despite the much wider range of information assimilated (including satellites). Remarkably high Detrended Cross-Correlation Analysis coefficients (ρDCCA > 0.7 and often ρDCCA > 0.9) revealed tight links between the nonperiodic variability of P, moisture divergence (DIV), and pressure velocity (ω) at monthly-to-decadal time scales over all the wet regions. In contrast, ρDCCA was essentially nonsignificant between nonperiodic P and E or sea surface temperature (SST). Thus, the nonperiodic monthly-to-decadal variability of precipitation in these regions is almost fully controlled by dynamics and not by local E or SST (suggested by Clausius-Clapeyron relation). Analysis of regional nonperiodic standard deviations and power spectra (and respective spectral exponents, β) provided further robustness to this conclusion. Finally, clear transitions in β for P, DIV, and ω between tropical and storm track regions were found. The latter is dominated by transient storms, with energy accumulation at synoptic scales and β β values (0.2 to 0.4) were found in the tropics, implying longer-range autocorrelations and slower decreasing variability and information creation with time scale, consistent with the important forcing from internal modes of variability (e.g., El Niño-Southern Oscillation).
Studies of Ocean Predictability at Decade to Century Time Scales Using a Global Ocean General Circulation Model in a Parallel Computing Environment; FINAL

International Nuclear Information System (INIS)

Barnett, T.P.

1998-01-01

The objectives of this report are to determine the structure of oceanic natural variability at time scales of decades to centuries, characterize the physical mechanisms responsible for the variability; determine the relative importance of heat, fresh water, and moment fluxes on the variability; determine the predictability of the variability on these times scales
Multi-year predictability in a coupled general circulation model

Energy Technology Data Exchange (ETDEWEB)

Power, Scott; Colman, Rob [Bureau of Meteorology Research Centre, Melbourne, VIC (Australia)

2006-02-01

Multi-year to decadal variability in a 100-year integration of a BMRC coupled atmosphere-ocean general circulation model (CGCM) is examined. The fractional contribution made by the decadal component generally increases with depth and latitude away from surface waters in the equatorial Indo-Pacific Ocean. The relative importance of decadal variability is enhanced in off-equatorial ''wings'' in the subtropical eastern Pacific. The model and observations exhibit ''ENSO-like'' decadal patterns. Analytic results are derived, which show that the patterns can, in theory, occur in the absence of any predictability beyond ENSO time-scales. In practice, however, modification to this stochastic view is needed to account for robust differences between ENSO-like decadal patterns and their interannual counterparts. An analysis of variability in the CGCM, a wind-forced shallow water model, and a simple mixed layer model together with existing and new theoretical results are used to improve upon this stochastic paradigm and to provide a new theory for the origin of decadal ENSO-like patterns like the Interdecadal Pacific Oscillation and Pacific Decadal Oscillation. In this theory, ENSO-driven wind-stress variability forces internal equatorially-trapped Kelvin waves that propagate towards the eastern boundary. Kelvin waves can excite reflected internal westward propagating equatorially-trapped Rossby waves (RWs) and coastally-trapped waves (CTWs). CTWs have no impact on the off-equatorial sub-surface ocean outside the coastal wave guide, whereas the RWs do. If the frequency of the incident wave is too high, then only CTWs are excited. At lower frequencies, both CTWs and RWs can be excited. The lower the frequency, the greater the fraction of energy transmitted to RWs. This lowers the characteristic frequency of variability off the equator relative to its equatorial counterpart. Both the eastern boundary interactions and the accumulation of
Multi-decadal modulation of the El Nino-Indian monsoon relationship by Indian Ocean variability

International Nuclear Information System (INIS)

Ummenhofer, Caroline C; Sen Gupta, Alexander; Li Yue; Taschetto, Andrea S; England, Matthew H

2011-01-01

The role of leading modes of Indo-Pacific climate variability is investigated for modulation of the strength of the Indian summer monsoon during the period 1877-2006. In particular, the effect of Indian Ocean conditions on the relationship between the El Nino-Southern Oscillation (ENSO) and the Indian monsoon is explored. Using an extended classification for ENSO and Indian Ocean dipole (IOD) events for the past 130 years and reanalyses, we have expanded previous interannual work to show that variations in Indian Ocean conditions modulate the ENSO-Indian monsoon relationship also on decadal timescales. El Nino events are frequently accompanied by a significantly reduced Indian monsoon and widespread drought conditions due to anomalous subsidence associated with a shift in the descending branch of the zonal Walker circulation. However, for El Nino events that co-occur with positive IOD (pIOD) events, Indian Ocean conditions act to counter El Nino's drought-inducing subsidence by enhancing moisture convergence over the Indian subcontinent, with an average monsoon season resulting. Decadal modulations of the frequency of independent and combined El Nino and pIOD events are consistent with a strengthened El Nino-Indian monsoon relationship observed at the start of the 20th century and the apparent recent weakening of the El Nino-Indian monsoon relationship.
Multi-decadal modulation of the El Nino-Indian monsoon relationship by Indian Ocean variability

Energy Technology Data Exchange (ETDEWEB)

Ummenhofer, Caroline C; Sen Gupta, Alexander; Li Yue; Taschetto, Andrea S; England, Matthew H, E-mail: c.ummenhofer@unsw.edu.au [Climate Change Research Centre, University of New South Wales, Sydney (Australia)

2011-07-15

The role of leading modes of Indo-Pacific climate variability is investigated for modulation of the strength of the Indian summer monsoon during the period 1877-2006. In particular, the effect of Indian Ocean conditions on the relationship between the El Nino-Southern Oscillation (ENSO) and the Indian monsoon is explored. Using an extended classification for ENSO and Indian Ocean dipole (IOD) events for the past 130 years and reanalyses, we have expanded previous interannual work to show that variations in Indian Ocean conditions modulate the ENSO-Indian monsoon relationship also on decadal timescales. El Nino events are frequently accompanied by a significantly reduced Indian monsoon and widespread drought conditions due to anomalous subsidence associated with a shift in the descending branch of the zonal Walker circulation. However, for El Nino events that co-occur with positive IOD (pIOD) events, Indian Ocean conditions act to counter El Nino's drought-inducing subsidence by enhancing moisture convergence over the Indian subcontinent, with an average monsoon season resulting. Decadal modulations of the frequency of independent and combined El Nino and pIOD events are consistent with a strengthened El Nino-Indian monsoon relationship observed at the start of the 20th century and the apparent recent weakening of the El Nino-Indian monsoon relationship.
Estimating decadal variability in sea level from tide gauge records: An application to the North Sea

NARCIS (Netherlands)

Frederikse, Thomas; Riva, R.E.M.; Slobbe, Cornelis; Broerse, D.B.T.; Verlaan, Martin

2016-01-01

One of the primary observational data sets of sea level is represented by the tide gauge record. We propose a new method to estimate variability on decadal time scales from tide gauge data by using a state space formulation, which couples the direct observations to a predefined state space model by
Estimating decadal variability in sea level from tide gauge records : An application to the North Sea

NARCIS (Netherlands)

Frederikse, T.; Riva, R.E.M.; Slobbe, D.C.; Broerse, D.B.T.; Verlaan, M.

2016-01-01

One of the primary observational data sets of sea level is represented by the tide gauge record. We propose a new method to estimate variability on decadal time scales from tide gauge data by using a state space formulation, which couples the direct observations to a predefined state space model
Multi-physics and multi-scale characterization of shale anisotropy

Science.gov (United States)

Sarout, J.; Nadri, D.; Delle Piane, C.; Esteban, L.; Dewhurst, D.; Clennell, M. B.

2012-12-01

Shales are the most abundant sedimentary rock type in the Earth's shallow crust. In the past decade or so, they have attracted increased attention from the petroleum industry as reservoirs, as well as more traditionally for their sealing capacity for hydrocarbon/CO2 traps or underground waste repositories. The effectiveness of both fundamental and applied shale research is currently limited by (i) the extreme variability of physical, mechanical and chemical properties observed for these rocks, and by (ii) the scarce data currently available. The variability in observed properties is poorly understood due to many factors that are often irrelevant for other sedimentary rocks. The relationships between these properties and the petrophysical measurements performed at the field and laboratory scales are not straightforward, translating to a scale dependency typical of shale behaviour. In addition, the complex and often anisotropic micro-/meso-structures of shales give rise to a directional dependency of some of the measured physical properties that are tensorial by nature such as permeability or elastic stiffness. Currently, fundamental understanding of the parameters controlling the directional and scale dependency of shale properties is far from complete. Selected results of a multi-physics laboratory investigation of the directional and scale dependency of some critical shale properties are reported. In particular, anisotropic features of shale micro-/meso-structures are related to the directional-dependency of elastic and fluid transport properties: - Micro-/meso-structure (μm to cm scale) characterization by electron microscopy and X-ray tomography; - Estimation of elastic anisotropy parameters on a single specimen using elastic wave propagation (cm scale); - Estimation of the permeability tensor using the steady-state method on orthogonal specimens (cm scale); - Estimation of the low-frequency diffusivity tensor using NMR method on orthogonal specimens (example
Multi-decadal scale variability in the eastern Baltic cod fishery 1550-1860 - Evidence and causes

DEFF Research Database (Denmark)

MacKenzie, Brian; Bager, M.; Ojaveer, H.

2007-01-01

in the Baltic as developed and implemented by organisations such as the International Council for the Exploration of the Sea (ICES), the Baltic Marine Environment Protection Commission (HELCOM), the nine coastal countries and the European Union includes recovery of the cod population, a reduction in nutrient...... is unknown, as is the relative role of fishing, climate variability/regimes, eutrophication and reduction of marine mammal predator populations. We have begun to investigate whether historical fisheries information (landings, effort, distribution) from before the 1880s is available in Baltic archives...
The Adaptive Multi-scale Simulation Infrastructure

Energy Technology Data Exchange (ETDEWEB)

Tobin, William R. [Rensselaer Polytechnic Inst., Troy, NY (United States)

2015-09-01

The Adaptive Multi-scale Simulation Infrastructure (AMSI) is a set of libraries and tools developed to support the development, implementation, and execution of general multimodel simulations. Using a minimal set of simulation meta-data AMSI allows for minimally intrusive work to adapt existent single-scale simulations for use in multi-scale simulations. Support for dynamic runtime operations such as single- and multi-scale adaptive properties is a key focus of AMSI. Particular focus has been spent on the development on scale-sensitive load balancing operations to allow single-scale simulations incorporated into a multi-scale simulation using AMSI to use standard load-balancing operations without affecting the integrity of the overall multi-scale simulation.
Two decades of ocean CO2 sink and variability

International Nuclear Information System (INIS)

Quere, C. Le; Bopp, L.; Heimann, M.; Prentice, I.C.; Aumont, O.; Bousquet, P.; Ciais, P.; Francey, R.; Rayner, P.J.; Keeling, C.D.; Keeling, R.F.; Piper, S.C.; Kheshgi, H.; Peyliln, P.

2003-01-01

Atmospheric CO 2 has increased at a nearly identical average rate of 3.3 and 3.2 Pg C/yr for the decades of the 1980s and the 1990s, in spite of a large increase in fossil fuel emissions from 5.4 to 6.3 Pg C/yr. Thus, the sum of the ocean and land CO 2 sinks was 1 Pg C/yr larger in the 1990s than in to the 1980s. Here we quantify the ocean and land sinks for these two decades using recent atmospheric inversions and ocean models. The ocean and land sinks are estimated to be, respectively, 0.3 (0.1 to 0.6) and 0.7 (0.4 to 0.9) Pg C/yr larger in the 1990s than in the 1980s. When variability less than 5 yr is removed, all estimates show a global oceanic sink more or less steadily increasing with time, and a large anomaly in the land sink during 1990-1994. For year-to-year variability, all estimates show 1/3 to 1/2 less variability in the ocean than on land, but the amplitude and phase of the oceanic variability remain poorly determined. A mean oceanic sink of 1.9 Pg C/yr for the 1990s based on O 2 observations corrected for ocean outgassing is supported by these estimates, but an uncertainty on the mean value of the order of ±0.7 Pg C/yr remains. The difference between the two decades appears to be more robust than the absolute value of either of the two decades
Estimating decadal variability in sea level from tide gauge records: An application to the North Sea

OpenAIRE

Frederikse, Thomas; Riva, R.E.M.; Slobbe, Cornelis; Broerse, D.B.T.; Verlaan, Martin

2016-01-01

One of the primary observational data sets of sea level is represented by the tide gauge record. We propose a new method to estimate variability on decadal time scales from tide gauge data by using a state space formulation, which couples the direct observations to a predefined state space model by using a Kalman filter. The model consists of a time-varying trend and seasonal cycle, and variability induced by several physical processes, such as wind, atmospheric pressure changes and teleconne...
Multi-year climate variability in the Southwestern United States within a context of a dynamically downscaled twentieth century reanalysis

Science.gov (United States)

Carrillo, Carlos M.; Castro, Christopher L.; Chang, Hsin-I.; Luong, Thang M.

2017-12-01

This investigation evaluates whether there is coherency in warm and cool season precipitation at the low-frequency scale that may be responsible for multi-year droughts in the US Southwest. This low-frequency climate variability at the decadal scale and longer is studied within the context of a twentieth-century reanalysis (20CR) and its dynamically-downscaled version (DD-20CR). A spectral domain matrix methods technique (Multiple-Taper-Method Singular Value Decomposition) is applied to these datasets to identify statistically significant spatiotemporal precipitation patterns for the cool (November-April) and warm (July-August) seasons. The low-frequency variability in the 20CR is evaluated by exploring global to continental-scale spatiotemporal variability in moisture flux convergence (MFC) to the occurrence of multiyear droughts and pluvials in Central America, as this region has a demonstrated anti-phase relationship in low-frequency climate variability with northern Mexico and the southwestern US By using the MFC in lieu of precipitation, this study reveals that the 20CR is able to resolve well the low-frequency, multiyear climate variability. In the context of the DD-20CR, multiyear droughts and pluvials in the southwestern US (in the early twentieth century) are significantly related to this low-frequency climate variability. The precipitation anomalies at these low-frequency timescales are in phase between the cool and warm seasons, consistent with the concept of dual-season drought as has been suggested in tree ring studies.
Variability of basin-scale terrestrial water storage from a novel application of the water budget equation: the Amazon and the Mississippi

Science.gov (United States)

Yoon, J.; Zeng, N.; Mariotti, A.; Swenson, S.

2007-12-01

In an approach termed the P-E-R (or simply PER) method, we apply the basin water budget equation to diagnose the long-term variability of the total terrestrial water storage (TWS). The key input variables are observed precipitation (P) and runoff (R), and estimated evaporation (E). Unlike typical offline land-surface model estimate where only atmospheric variables are used as input, the direct use of observed runoff in the PER method imposes an important constraint on the diagnosed TWS. Although there lack basin-scale observations of evaporation, the tendency of E to have significantly less variability than the difference between precipitation and runoff (P-R) minimizes the uncertainties originating from estimated evaporation. Compared to the more traditional method using atmospheric moisture convergence (MC) minus R (MCR method), the use of observed precipitation in PER method is expected to lead to general improvement, especially in regions atmospheric radiosonde data are too sparse to constrain the atmospheric model analyzed MC such as in the remote tropics. TWS was diagnosed using the PER method for the Amazon (1970-2006) and the Mississippi Basin (1928-2006), and compared with MCR method, land-surface model and reanalyses, and NASA's GRACE satellite gravity data. The seasonal cycle of diagnosed TWS over the Amazon is about 300 mm. The interannual TWS variability in these two basins are 100-200 mm, but multi-dacadal changes can be as large as 600-800 mm. Major droughts such as the Dust Bowl period had large impact with water storage depleted by 500 mm over a decade. Within the short period 2003-2006 when GRACE data was available, PER and GRACE show good agreement both for seasonal cycle and interannual variability, providing potential to cross-validate each other. In contrast, land-surface model results are significantly smaller than PER and GRACE, especially towards longer timescales. While we currently lack independent means to verify these long-term changes
The response of the North Pacific Decadal Variability to strong tropical volcanic eruptions

Energy Technology Data Exchange (ETDEWEB)

Wang, Tao [Chinese Academy of Sciences, Nansen-Zhu International Research Center, Institute of Atmospheric Physics, Beijing (China); Otteraa, Odd Helge [Uni Bjerknes Centre, Uni Research, Bergen (Norway); Bjerknes Center for Climate Research, Bergen (Norway); Gao, Yongqi [Chinese Academy of Sciences, Nansen-Zhu International Research Center, Institute of Atmospheric Physics, Beijing (China); Bjerknes Center for Climate Research, Bergen (Norway); Nansen Environmental and Remote Sensing Center, Bergen (Norway); Wang, Huijun [Chinese Academy of Sciences, Nansen-Zhu International Research Center, Institute of Atmospheric Physics, Beijing (China); Chinese Academy of Sciences, Climate Change Research Center, Institute of Atmospheric Physics, Beijing (China)

2012-12-15

In this study, the effects of volcanic forcing on North Pacific climate variability, on interannual to decadal time scales, are examined using climate model simulations covering the last 600 years. The model used is the Bergen Climate Model, a fully coupled atmosphere-ocean general circulation model. It is found that natural external forcings, such as tropical strong volcanic eruptions (SVEs) and variations in total solar irradiance, play an important role in regulating North Pacific Decadal Variability (NPDV). In response to tropical SVEs the lower stratospheric pole-to-equator temperature gradient is enhanced. The North polar vortex is strengthened, which forces a significant positive Arctic Oscillation. At the same time, dipole zonal wind anomalies associated with strong polar vortex propagate downward from the lower stratosphere. Through positive feedbacks in the troposphere, the surface westerly winds across the central North Pacific are significantly weakened, and positive sea level pressure anomalies are formed in the North Pacific. This anomalous surface circulation results in changes in the net heat fluxes and the oceanic advection across the North Pacific. As a result of this, warm water converges in the subtropical western North Pacific, where the surface waters in addition are heated by significantly reduced latent and sensible heat fluxes from the ocean. In the eastern and high-latitude North Pacific the ocean loses more heat, and large-scale decreases in sea surface temperatures are found. The overall response of this chain of events is that the North Pacific enters a negative phase of the Pacific decadal oscillation (PDO), and this negative phase of the PDO is maintained for several years. It is thus concluded that the volcanic forcing plays a key role in the phasing of the PDO. The model results furthermore highlight the important role of troposphere-stratosphere coupling, tropical-extratropical teleconnections and extratropical ocean

The adaptive value of habitat preferences from a multi-scale spatial perspective: insights from marsh-nesting avian species

Directory of Open Access Journals (Sweden)

Jan Jedlikowski

2017-03-01

Full Text Available Background Habitat selection and its adaptive outcomes are crucial features for animal life-history strategies. Nevertheless, congruence between habitat preferences and breeding success has been rarely demonstrated, which may result from the single-scale evaluation of animal choices. As habitat selection is a complex multi-scale process in many groups of animal species, investigating adaptiveness of habitat selection in a multi-scale framework is crucial. In this study, we explore whether habitat preferences acting at different spatial scales enhance the fitness of bird species, and check the appropriateness of single vs. multi-scale models. We expected that variables found to be more important for habitat selection at individual scale(s, would coherently play a major role in affecting nest survival at the same scale(s. Methods We considered habitat preferences of two Rallidae species, little crake (Zapornia parva and water rail (Rallus aquaticus, at three spatial scales (landscape, territory, and nest-site and related them to nest survival. Single-scale versus multi-scale models (GLS and glmmPQL were compared to check which model better described adaptiveness of habitat preferences. Consistency between the effect of variables on habitat selection and on nest survival was checked to investigate their adaptive value. Results In both species, multi-scale models for nest survival were more supported than single-scale ones. In little crake, the multi-scale model indicated vegetation density and water depth at the territory scale, as well as vegetation height at nest-site scale, as the most important variables. The first two variables were among the most important for nest survival and habitat selection, and the coherent effects suggested the adaptive value of habitat preferences. In water rail, the multi-scale model of nest survival showed vegetation density at territory scale and extent of emergent vegetation within landscape scale as the most
Interannual to Decadal SST Variability in the Tropical Indian Ocean

Science.gov (United States)

Wang, G.; Newman, M.; Han, W.

2017-12-01

The Indian Ocean has received increasing attention in recent years for its large impacts on regional and global climate. However, due mainly to the close interdependence of the climate variation within the Tropical Pacific and the Indian Ocean, the internal sea surface temperature (SST) variability within the Indian Ocean has not been studied extensively on longer time scales. In this presentation we will show analysis of the interannual to decadal SST variability in the Tropical Indian Ocean in observations and Linear Inverse Model (LIM) results. We also compare the decoupled Indian Ocean SST variability from the Pacific against fully coupled one based on LIM integrations, to test the factors influence the features of the leading SST modes in the Indian Ocean. The result shows the Indian Ocean Basin (IOB) mode, which is strongly related to global averaged SST variability, passively responses to the Pacific variation. Without tropical Indo-Pacific coupling interaction, the intensity of IOB significantly decreases by 80%. The Indian Ocean Dipole (IOD) mode demonstrates its independence from the Pacific SST variability since the IOD does not change its long-term characteristics at all without inter-basin interactions. The overall SSTA variance decreases significantly in the Tropical Indian Ocean in the coupling restricted LIM runs, especially when the one-way impact from the Pacific to the Indian Ocean is turned off, suggesting that most of the variability in the Indian Ocean comes from the Pacific influence. On the other hand, the Indian Ocean could also transport anomalies to the Pacific, making the interaction a complete two-way process.
Small Scale Variability and the Problem of Data Validation

Science.gov (United States)

Sparling, L. C.; Avallone, L.; Einaudi, Franco (Technical Monitor)

2000-01-01

Numerous measurements taken with a variety of airborne, balloon borne and ground based instruments over the past decade have revealed a complex multiscaled 3D structure in both chemical and dynamical fields in the upper troposphere/lower stratosphere. The variability occurs on scales that are well below the resolution of satellite measurements, leading to problems in measurement validation. We discuss some statistical ideas that can shed some light on the contribution of the natural variability to the inevitable differences in correlative measurements that are not strictly colocated, or that have different spatial resolution.
CCSM3 simulation of pacific multi-decadal climate variability: the role of subpolar North Pacific Ocean

International Nuclear Information System (INIS)

Zhong, Y; Liu, Z

2008-01-01

Previous analyses of the CCSM3 standard integration have revealed pronounced multidecadal variability in the Pacific climate system. The purpose of the present work is to investigate the physical mechanism underlying the Pacific multidecadal variability (PMV) using specifically designed sensitivity experiments. A novel mechanism is advanced, characterized by a crucial role of the subpolar North Pacific Ocean. The multidecadal signal in ocean temperature and salinity fields is found to originate from the subsurface of the subpolar North Pacific, as result of the wave adjustment to the preceding basin-scale wind curl forcing. The multidecadal signal then ascends to the surface and is amplified through local temperature/salinity convective feedback. Along the southward Oyashio current, the anomaly travels to the Kuroshio Extension (KOE) region and is further intensified through a similar convective feedback in addition to the wind-evaporation-sea surface temperature feedback. The temperature anomaly in the KOE is able to feed back to the large-scale atmospheric circulation, inducing wind curl anomaly over the subpolar region, which in turn generates anomalous oceanic circulation and causes temperature/salinty variability in the subpolar subsurface. Thereby, a closed loop of PMV is established, in the form of a subpolar delayed oscillator
Asymmetry of agricultural water consumption in arid regions during alternating decadal scale wet and dry periods: explanation using behavioral economics

Science.gov (United States)

Tian, Fuqiang

2017-04-01

Increase of human water consumption for agriculture and consequent degradation of the ecological environment is a common feature in many arid regions. Understanding the driving mechanisms behind this phenomenon is of critical importance for regional sustainable development. In this study, analyses of temporal patterns of human water consumption are carried out in three hyper-arid inland basins, i.e., Aral Sea Basin in Central Asia, and the Tarim and Heihe River Basins in Northwestern China. Multi-decadal time series of hydrological and human consumption data are divided into decadal sequences of wet and dry years. During the wet phases, the greater water availability inspires economic expansion and human water consumption experiences growth at a rate faster than that of incoming water. During the dry phases, however, the expanded economy (e.g., irrigation land expansion in an agriculture-based economy) has been managed to sustain or even to increase production by over-exploitation of water with sophisticated technologies. Inability to reduce human water consumption at a rate commensurate with the decrease of incoming water supply leads to serious ecosystem degradation. This asymmetric human water consumption response of society to decadal scale hydrologic variability can be explained in terms of prospect theory drawn from behavioral economics, which states that people tend to be risk averse when facing gains and show risk preference when facing losses. In the three socio-hydrological case studies, direct economic gain/loss has relatively low value but high certainty when compared to indirect economic loss/gain (such as environmental or sustainability loss/gain), which has high value but with high uncertainty. According to prospect theory, people tend to gain direct economic benefits at the expense of environmental degradation and at the risk of system collapse. The outcomes of this study have major implications for water resources management at long time scales
Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

Science.gov (United States)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

2013-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the 'A-Train' platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (MERRA), stratify the comparisons using a classification of the 'cloud scenes' from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically 'sharded' by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will
Decadal Variability of Total Alkalinity in the North Pacific Ocean

Science.gov (United States)

Cross, J. N.; Carter, B. R.; Siedlecki, S. A.; Alin, S. R.; Dickson, A. G.; Feely, R. A.; Mathis, J. T.; Wanninkhof, R. H.; Macdonald, A. M.; Mecking, S.; Talley, L. D.

2016-02-01

Recent observations of acidification-driven shoaling of the calcium carbonate saturation horizon in the North Pacific have prompted new interest in carbonate cycling in this region, particularly related to impacts on biogenic calcification at the surface layer. Some estimates project that the impacts of OA on alkalinity cycling are beginning to emerge. Here, we present total alkalinity concentrations along a meridional transect of the North Pacific (WOCE, CLIVAR, and US GO-SHIP line P16N; 152 °W) over a period of three decades. The largest source of variability in alkalinity concentrations is related to North Pacific circulation, particularly in the surface mixed layer. Precise normalization of these data reveal some small spatial and temporal variability in the background. We explore these decadal trends in the context of decadal oscillations, ocean biogeochemical cycles, and global change processes such as ocean acidification.
Using coral Ba/Ca records to investigate seasonal to decadal scale biogeochemical cycling in the surface and intermediate ocean.

Science.gov (United States)

LaVigne, M.; Cobb, K. M.; DeLong, K. L.; Freiberger, M. M.; Grottoli, A. G.; Hill, T. M.; Miller, H. R.; Nurhati, I. S.; Richey, J. N.; Serrato Marks, G.; Sherrell, R. M.

2016-12-01

Dissolved barium (BaSW), a bio-intermediate element, is linked to several biogeochemical processes such as the cycling and export of nutrients, organic carbon (Corg), and barite in surface and intermediate oceans. Dynamic BaSW cycling has been demonstrated in the water column on short timescales (days-weeks) while sedimentary records have documented geologic-scale changes in barite preservation driven by export production. Our understanding of how seasonal-decadal scale climate variability impacts these biogeochemical processes currently lacks robust records. Ba/Ca calibrations in surface and deep sea corals suggest barium is incorporated via cationic substitution in both aragonite and calcite. Here we demonstrate the utility of Ba/Ca for reconstructing biogeochemical variability using examples of surface and deep sea coral records. Century-long deep sea coral records from the California Current System (bamboo corals: 900-1500m) record interannual variations in Ba/Ca, likely reflecting changes in barite formation via bacterial Corg respiration or barite saturation state. A surface Porites coral Ba/Ca record from Christmas Island (central equatorial Pacific: 1978-1995) shows maxima during low productivity El Niño warm periods, suggesting that variations in BaSW are driven by biological removal via direct cellular uptake or indirectly via barite precipitation with the decomposition of large phytoplankton blooms at this location. Similarly, a sixteen-year long Siderastera siderea surface coral record from Dry Tortugas, FL (Gulf of Mexico: 1991-2007) shows seasonal Ba/Ca cycles that align with annual chlorophyll and δ13C. Taken together, these records demonstrate the linkages among Corg, nutrient cycling and BaSW in the surface and intermediate ocean on seasonal to decadal timescales. Multi-proxy paleoceanographic reconstructions including Ba/Ca have the potential to elucidate the mechanisms linking past climate, productivity, nutrients, and BaSW cycling in the past.
Carbon and nitrogen elemental and isotopic ratios of filter-feeding bivalves along the French coasts: An assessment of specific, geographic, seasonal and multi-decadal variations.

Science.gov (United States)

Briant, Nicolas; Savoye, Nicolas; Chouvelon, Tiphaine; David, Valérie; Rodriguez, Samuel; Charlier, Karine; Sonke, Jeroen E; Chiffoleau, Jean François; Brach-Papa, Christophe; Knoery, Joël

2018-02-01

Primary consumers play a key role in coastal ecosystems by transferring organic matter from primary producers to predators. Among them, suspension-feeders, like bivalve molluscs are widely used in trophic web studies. The main goal of this study was to investigate variations of C and N elemental and isotopic ratios in common bivalves (M. edulis, M. galloprovincialis, and C. gigas) at large spatial (i.e. among three coastal regions) and different temporal (i.e. from seasonal to multi-decadal) scales in France, in order to identify potential general or specific patterns and speculate on their drivers. The observed spatial variability was related to the trophic status of the coastal regions (oligotrophic Mediterranean Sea versus meso- to eutrophic English Channel and Atlantic ocean), but not to ecosystem typology (estuaries, versus lagoons versus bays versus littoral systems). Furthermore, it highlighted local specificities in terms of the origin of the POM assimilated by bivalves (e.g., mainly continental POM vs. marine phytoplankton vs. microphytobenthic algae). Likewise, seasonal variability was related both to the reproduction cycle for C/N ratios of Mytilus spp. and to changes in trophic resources for δ 13 C of species located close to river mouth. Multi-decadal evolution exhibited shifts and trends for part of the 30-year series with decreases in δ 13 C and δ 15 N. Specifically, shifts appeared in the early 2000's, likely linking bivalve isotopic ratios to a cascade of processes affected by local drivers. Copyright © 2017 Elsevier B.V. All rights reserved.
Mass-flux subgrid-scale parameterization in analogy with multi-component flows: a formulation towards scale independence

Directory of Open Access Journals (Sweden)

J.-I. Yano

2012-11-01

Full Text Available A generalized mass-flux formulation is presented, which no longer takes a limit of vanishing fractional areas for subgrid-scale components. The presented formulation is applicable to a~situation in which the scale separation is still satisfied, but fractional areas occupied by individual subgrid-scale components are no longer small. A self-consistent formulation is presented by generalizing the mass-flux formulation under the segmentally-constant approximation (SCA to the grid–scale variabilities. The present formulation is expected to alleviate problems arising from increasing resolutions of operational forecast models without invoking more extensive overhaul of parameterizations.

The present formulation leads to an analogy of the large-scale atmospheric flow with multi-component flows. This analogy allows a generality of including any subgrid-scale variability into the mass-flux parameterization under SCA. Those include stratiform clouds as well as cold pools in the boundary layer.

An important finding under the present formulation is that the subgrid-scale quantities are advected by the large-scale velocities characteristic of given subgrid-scale components (large-scale subcomponent flows, rather than by the total large-scale flows as simply defined by grid-box average. In this manner, each subgrid-scale component behaves as if like a component of multi-component flows. This formulation, as a result, ensures the lateral interaction of subgrid-scale variability crossing the grid boxes, which are missing in the current parameterizations based on vertical one-dimensional models, and leading to a reduction of the grid-size dependencies in its performance. It is shown that the large-scale subcomponent flows are driven by large-scale subcomponent pressure gradients. The formulation, as a result, furthermore includes a self-contained description of subgrid-scale momentum transport.

The main purpose of the present paper
Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling

Science.gov (United States)

Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana

2018-01-01

This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.
Effects of climate variability on global scale flood risk

Science.gov (United States)

Ward, P.; Dettinger, M. D.; Kummu, M.; Jongman, B.; Sperna Weiland, F.; Winsemius, H.

2013-12-01

In this contribution we demonstrate the influence of climate variability on flood risk. Globally, flooding is one of the worst natural hazards in terms of economic damages; Munich Re estimates global losses in the last decade to be in excess of $240 billion. As a result, scientifically sound estimates of flood risk at the largest scales are increasingly needed by industry (including multinational companies and the insurance industry) and policy communities. Several assessments of global scale flood risk under current and conditions have recently become available, and this year has seen the first studies assessing how flood risk may change in the future due to global change. However, the influence of climate variability on flood risk has as yet hardly been studied, despite the fact that: (a) in other fields (drought, hurricane damage, food production) this variability is as important for policy and practice as long term change; and (b) climate variability has a strong influence in peak riverflows around the world. To address this issue, this contribution illustrates the influence of ENSO-driven climate variability on flood risk, at both the globally aggregated scale and the scale of countries and large river basins. Although it exerts significant and widespread influences on flood peak discharges in many parts of the world, we show that ENSO does not have a statistically significant influence on flood risk once aggregated to global totals. At the scale of individual countries, though, strong relationships exist over large parts of the Earth's surface. For example, we find particularly strong anomalies of flood risk in El Niño or La Niña years (compared to all years) in southern Africa, parts of western Africa, Australia, parts of Central Eurasia (especially for El Niño), the western USA (especially for La Niña), and parts of South America. These findings have large implications for both decadal climate-risk projections and long-term future climate change
Variability in Multi-Tenant Enterprise Software

OpenAIRE

Kabbedijk, J.

2014-01-01

Enterprise software applications have changed significantly over the last decades. Increasingly, software is deployed in a central location to be accessed through the internet, instead of installing software at end-users. Having software in a central location enables multi-tenancy, where multiple customers transparently share a system’s resources. Currently, multi-tenancy is a popular way to offer functionality of a software product through the internet to numerous customers, offering many ad...
Front-end vision and multi-scale image analysis multi-scale computer vision theory and applications, written in Mathematica

CERN Document Server

Romeny, Bart M Haar

2008-01-01

Front-End Vision and Multi-Scale Image Analysis is a tutorial in multi-scale methods for computer vision and image processing. It builds on the cross fertilization between human visual perception and multi-scale computer vision (`scale-space') theory and applications. The multi-scale strategies recognized in the first stages of the human visual system are carefully examined, and taken as inspiration for the many geometric methods discussed. All chapters are written in Mathematica, a spectacular high-level language for symbolic and numerical manipulations. The book presents a new and effective
The modulation of Tibetan Plateau heating on the multi-scale northernmost margin activity of East Asia summer monsoon in northern China

Science.gov (United States)

Zhang, Jie; Liu, Chen; Chen, Haishan

2018-02-01

The northernmost margin of East Asian summer monsoon (EASM) could well reflect wet/dry climate variability in the EASM marginal zone (northern China). The study shows that EASM occurs in northern China from Meiyu period to midsummer, and it is also the advancing period of the northern margin of EASM (NMEASM) before the 43rd pentad. NMEASM activity exhibits multi-scale variability, at cycles of 2-3-yr, 4-6-yr and 9-12-yr, which respond not only to EASM intensity but also to westerly circulation anomaly, exhibiting the mid-latitude Eurasian waves and the high-latitude Eurasian teleconnection (EU) patterns. The positive anomalies of Silk Road pattern and EU pattern in recent two decades contribute to the enhanced west-ridge and east-trough anomaly around 120°E over northern China, leading to divergence of moisture flux and north wind anomaly, which is helpful for southward western pacific subtropical high (WPSH) and southward NMEASM. Negative Eurasian pattern along subtropical Jet leads to anticyclone anomaly over south of the Yangtze River, deep trough and north wind anomaly along the west coast of the subtropical Pacific, contributing to southward WPSH and NMEASM at the cycle of 4-6-yr. Remote forcing sources of these anomalous Eurasian waves include North Europe, north of Caspian Sea, Central Asia, Tibetan Plateau and the west of Lake Baikal; the south of Lake Baikal is a local forcing region. The Tibetan Plateau heating and snow cover could modulate Eurasian wave pattern at multi-scale, which could be used as prediction reference of multi-scale NMEASM.
A Null-hypothesis to explain the El Niño-like Pacific Decadal Variability

Science.gov (United States)

Di Lorenzo, E.

2016-02-01

Pacific low-frequency variability (timescale > 8 year) exhibits a well-known El Niño-like pattern of basin-scale sea surface temperature, which is found in all the major modes of Pacific decadal climate. Using a set of climate model experiments and observations, we decompose the mechanisms contributing to the growth, peak and decay of the Pacific low-frequency spatial variance. We find that the El-Niño-like inter-decadal pattern is established through the combined actions of Pacific Meridional Modes (MM) and the El Niño Southern Oscillation (ENSO). Specifically, in the growing phase of the pattern, sub-tropical stochastic excitation of the MM, and its ENSO-precursor dynamics, becomes an important source of tropical low-frequency variance (e.g. red noise). Once in the tropics, ENSO amplifies and distributes this low-frequency energy in the extra-tropics through global teleconnections in the peak and decaying phases. In this stochastic red noise model of Pacific climate, the timescale of the MM/ENSO progression and extra-tropical decay (1-2 year) enhances the spatial memory of the decadal and inter-decadal El-Niño-like pattern.
Multi-Object Spectroscopy in the Next Decade: A Conference Summary

NARCIS (Netherlands)

Trager, S. C.; Skillen, I.; Barcells, M.

2016-01-01

I present a highly-biased summary of the conference "Multi-Object Spectroscopy in the Next Decade: Big Questions, Large Surveys, and Wide Fields," held 2-6 March 2015 in Santa Cruz de la Palma, Spain. I focus on four issues in this summary: (1) complexity in objects, physics, and instruments is
Sea-ice cover anomalies in the Arctic Basin associated with atmospheric variability from multi-decadal trends to intermittent quasi-biennial oscillations

Directory of Open Access Journals (Sweden)

Motoyoshi Ikeda

2012-06-01

Full Text Available Arctic Ocean sea ice has been diminishing since 1970, as shown by National Snow and Ice Data Center data. In addition to decadal variability, low ice anomalies in the Pacific–Siberian region have been occurring at shorter timescales. The influence of the widely-known Northern Annular Mode (NAM occurs across all seasons. In this study, empirical orthogonal function (EOF analysis was applied to sea-level pressure in National Centers for Environmental Prediction Reanalysis data for 1960–2007, showing the NAM to be the leading mode of variability and the Arctic Dipole Mode (ADM to be the second leading mode. The ADM changes markedly across seasons. In autumn–winter, it has a pole over Siberia and a pole over Greenland, at opposite signs at a several-year scale, whereas the spring–summer ADM (ADMSS has a pole over Europe and a pole over Canada. In the 1980s, the most influential mode shifted from the NAM to the ADM, when the Pacific sector had low ice cover at a 1-year lag from the positive ADM, which was marked by low pressure over Siberia. In years when the ADMSS was pronounced, it was responsible for distinct ice variability over the East Siberian–Laptev seas. The frequency separation in this study identified the contributions of the ADM and ADMSS. Effects of the latter are difficult to predict since it is intermittent and changes its sign biennially. The ADM and ADMSS should be closely watched in relation to the ongoing ice reduction in the Pacific–Siberian region.
Variability in Multi-Tenant Enterprise Software

NARCIS (Netherlands)

Kabbedijk, J.

2014-01-01

Enterprise software applications have changed significantly over the last decades. Increasingly, software is deployed in a central location to be accessed through the internet, instead of installing software at end-users. Having software in a central location enables multi-tenancy, where multiple
Improving seasonal forecasts of hydroclimatic variables through the state of multiple large-scale climate signals

Science.gov (United States)

Castelletti, A.; Giuliani, M.; Block, P. J.

2017-12-01

Increasingly uncertain hydrologic regimes combined with more frequent and intense extreme events are challenging water systems management worldwide, emphasizing the need of accurate medium- to long-term predictions to timely prompt anticipatory operations. Despite modern forecasts are skillful over short lead time (from hours to days), predictability generally tends to decrease on longer lead times. Global climate teleconnection, such as El Niño Southern Oscillation (ENSO), may contribute in extending forecast lead times. However, ENSO teleconnection is well defined in some locations, such as Western USA and Australia, while there is no consensus on how it can be detected and used in other regions, particularly in Europe, Africa, and Asia. In this work, we generalize the Niño Index Phase Analysis (NIPA) framework by contributing the Multi Variate Niño Index Phase Analysis (MV-NIPA), which allows capturing the state of multiple large-scale climate signals (i.e. ENSO, North Atlantic Oscillation, Pacific Decadal Oscillation, Atlantic Multi-decadal Oscillation, Indian Ocean Dipole) to forecast hydroclimatic variables on a seasonal time scale. Specifically, our approach distinguishes the different phases of the considered climate signals and, for each phase, identifies relevant anomalies in Sea Surface Temperature (SST) that influence the local hydrologic conditions. The potential of the MV-NIPA framework is demonstrated through an application to the Lake Como system, a regulated lake in northern Italy which is mainly operated for flood control and irrigation supply. Numerical results show high correlations between seasonal SST values and one season-ahead precipitation in the Lake Como basin. The skill of the resulting MV-NIPA forecast outperforms the one of ECMWF products. This information represents a valuable contribution to partially anticipate the summer water availability, especially during drought events, ultimately supporting the improvement of the Lake Como

Relating system-to-CFD coupled code analyses to theoretical framework of a multi-scale method

International Nuclear Information System (INIS)

Cadinu, F.; Kozlowski, T.; Dinh, T.N.

2007-01-01

Over past decades, analyses of transient processes and accidents in a nuclear power plant have been performed, to a significant extent and with a great success, by means of so called system codes, e.g. RELAP5, CATHARE, ATHLET codes. These computer codes, based on a multi-fluid model of two-phase flow, provide an effective, one-dimensional description of the coolant thermal-hydraulics in the reactor system. For some components in the system, wherever needed, the effect of multi-dimensional flow is accounted for through approximate models. The later are derived from scaled experiments conducted for selected accident scenarios. Increasingly, however, we have to deal with newer and ever more complex accident scenarios. In some such cases the system codes fail to serve as simulation vehicle, largely due to its deficient treatment of multi-dimensional flow (in e.g. downcomer, lower plenum). A possible way of improvement is to use the techniques of Computational Fluid Dynamics (CFD). Based on solving Navier-Stokes equations, CFD codes have been developed and used, broadly, to perform analysis of multi-dimensional flow, dominantly in non-nuclear industry and for single-phase flow applications. It is clear that CFD simulations can not substitute system codes but just complement them. Given the intrinsic multi-scale nature of this problem, we propose to relate it to the more general field of research on multi-scale simulations. Even though multi-scale methods are developed on case-by-case basis, the need for a unified framework brought to the development of the heterogeneous multi-scale method (HMM)
The Baltic Sea natural long-term variability of salinity

Science.gov (United States)

Schimanke, Semjon; Markus Meier, H. E.

2015-04-01

The Baltic Sea is one of the largest brackish sea areas of the world. The sensitive state of the Baltic Sea is sustained by a fresh-water surplus by river discharge and precipitation on one hand as well as inflows of highly saline and oxygen-rich water masses from the North Sea on the other. Major inflows which are crucial for the renewal of the deep water occur very intermittent with a mean frequency of approximately one per year. Stagnation periods (periods without major inflows) lead for instance to a reduction of oxygen concentration in the deep Baltic Sea spreading hypoxic conditions. Depending on the amount of salt water inflow and fresh-water supply the deep water salinity of the Baltic Sea varies between 11 to 14 PSU on the decadal scale. The goal of this study is to understand the contribution of different driving factors for the decadal to multi-decadal variability of salinity in the Baltic Sea. Continuous measurement series of salinity exist from the 1950 but are not sufficiently long for the investigation of long-term fluctuations. Therefore, a climate simulation of more than 800 years has been carried out with the Rossby Center Ocean model (RCO). RCO is a biogeochemical regional climate model which covers the entire Baltic Sea. It is driven with atmospheric data dynamical downscaled from a GCM mimicking natural climate variability. The analysis focus on the role of variations in river discharge and precipitation, changes in wind speed and direction, fluctuations in temperature and shifts in large scale pressure patterns (e.g. NAO). Hereby, the length of the simulation will allow to identify mechanisms working on decadal to multi-decadal time scales. Moreover, it will be discussed how likely long stagnation periods are under natural climate variability and if the observed exceptional long stagnation period between 1983-1993 might be related to beginning climate change.
Toward a global multi-scale heliophysics observatory

Science.gov (United States)

Semeter, J. L.

2017-12-01

We live within the only known stellar-planetary system that supports life. What we learn about this system is not only relevant to human society and its expanding reach beyond Earth's surface, but also to our understanding of the origins and evolution of life in the universe. Heliophysics is focused on solar-terrestrial interactions mediated by the magnetic and plasma environment surrounding the planet. A defining feature of energy flow through this environment is interaction across physical scales. A solar disturbance aimed at Earth can excite geospace variability on scales ranging from thousands of kilometers (e.g., global convection, region 1 and 2 currents, electrojet intensifications) to 10's of meters (e.g., equatorial spread-F, dispersive Alfven waves, plasma instabilities). Most "geospace observatory" concepts are focused on a single modality (e.g., HF/UHF radar, magnetometer, optical) providing a limited parameter set over a particular spatiotemporal resolution. Data assimilation methods have been developed to couple heterogeneous and distributed observations, but resolution has typically been prescribed a-priori and according to physical assumptions. This paper develops a conceptual framework for the next generation multi-scale heliophysics observatory, capable of revealing and quantifying the complete spectrum of cross-scale interactions occurring globally within the geospace system. The envisioned concept leverages existing assets, enlists citizen scientists, and exploits low-cost access to the geospace environment. Examples are presented where distributed multi-scale observations have resulted in substantial new insight into the inner workings of our stellar-planetary system.
Probabilistic Simulation of Multi-Scale Composite Behavior

Science.gov (United States)

Chamis, Christos C.

2012-01-01

A methodology is developed to computationally assess the non-deterministic composite response at all composite scales (from micro to structural) due to the uncertainties in the constituent (fiber and matrix) properties, in the fabrication process and in structural variables (primitive variables). The methodology is computationally efficient for simulating the probability distributions of composite behavior, such as material properties, laminate and structural responses. Bi-products of the methodology are probabilistic sensitivities of the composite primitive variables. The methodology has been implemented into the computer codes PICAN (Probabilistic Integrated Composite ANalyzer) and IPACS (Integrated Probabilistic Assessment of Composite Structures). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in composite typical laminates and comparing the results with the Monte Carlo simulation method. Available experimental data of composite laminate behavior at all scales fall within the scatters predicted by PICAN. Multi-scaling is extended to simulate probabilistic thermo-mechanical fatigue and to simulate the probabilistic design of a composite redome in order to illustrate its versatility. Results show that probabilistic fatigue can be simulated for different temperature amplitudes and for different cyclic stress magnitudes. Results also show that laminate configurations can be selected to increase the redome reliability by several orders of magnitude without increasing the laminate thickness--a unique feature of structural composites. The old reference denotes that nothing fundamental has been done since that time.
Global Ocean Evaporation: How Well Can We Estimate Interannual to Decadal Variability?

Science.gov (United States)

Robertson, Franklin R.; Bosilovich, Michael G.; Roberts, Jason B.; Wang, Hailan

2015-01-01

Evaporation from the world's oceans constitutes the largest component of the global water balance. It is important not only as the ultimate source of moisture that is tied to the radiative processes determining Earth's energy balance but also to freshwater availability over land, governing habitability of the planet. Here we focus on variability of ocean evaporation on scales from interannual to decadal by appealing to three sources of data: the new MERRA-2 (Modern-Era Retrospective analysis for Research and Applications -2); climate models run with historical sea-surface temperatures, ice and atmospheric constituents (so-called AMIP experiments); and state-of-the-art satellite retrievals from the Seaflux and HOAPS (Hamburg Ocean-Atmosphere Parameters and Fluxes from Satellite) projects. Each of these sources has distinct advantages as well as drawbacks. MERRA-2, like other reanalyses, synthesizes evaporation estimates consistent with observationally constrained physical and dynamical models-but data stream discontinuities are a major problem for interpreting multi-decadal records. The climate models used in data assimilation can also be run with lesser constraints such as with SSTs and sea-ice (i.e. AMIPs) or with additional, minimal observations of surface pressure and marine observations that have longer and less fragmentary observational records. We use the new ERA-20C reanalysis produced by ECMWF embodying the latter methodology. Still, the model physics biases in climate models and the lack of a predicted surface energy balance are of concern. Satellite retrievals and comparisons to ship-based measurements offer the most observationally-based estimates, but sensor inter-calibration, algorithm retrieval assumptions, and short records are dominant issues. Our strategy depends on maximizing the advantages of these combined records. The primary diagnostic tool used here is an analysis of bulk aerodynamic computations produced by these sources and uses a first
Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

Energy Technology Data Exchange (ETDEWEB)

Stander, Nielen; Basudhar, Anirban; Basu, Ushnish; Gandikota, Imtiaz; Savic, Vesna; Sun, Xin; Choi, Kyoo Sil; Hu, Xiaohua; Pourboghrat, F.; Park, Taejoon; Mapar, Aboozar; Kumar, Shavan; Ghassemi-Armaki, Hassan; Abu-Farha, Fadi

2015-09-14

Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project to develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive
Comparison of single- and multi-scale models for the prediction of the Culicoides biting midge distribution in Germany

Directory of Open Access Journals (Sweden)

Renke Lühken

2016-05-01

Full Text Available This study analysed Culicoides presence-absence data from 46 sampling sites in Germany, where monitoring was carried out from April 2007 until May 2008. Culicoides presence-absence data were analysed in relation to land cover data, in order to study whether the prevalence of biting midges is correlated to land cover data with respect to the trapping sites. We differentiated eight scales, i.e. buffer zones with radii of 0.5, 1, 2, 3, 4, 5, 7.5 and 10 km, around each site, and chose several land cover variables. For each species, we built eight single-scale models (i.e. predictor variables from one of the eight scales for each model based on averaged, generalised linear models and two multiscale models (i.e. predictor variables from all of the eight scales based on averaged, generalised linear models and generalised linear models with random forest variable selection. There were no significant differences between performance indicators of models built with land cover data from different buffer zones around the trapping sites. However, the overall performance of multi-scale models was higher than the alternatives. Furthermore, these models mostly achieved the best performance for the different species using the index area under the receiver operating characteristic curve. However, as also presented in this study, the relevance of the different variables could significantly differ between various scales, including the number of species affected and the positive or negative direction. This is an even more severe problem if multi-scale models are concerned, in which one model can have the same variable at different scales but with different directions, i.e. negative and positive direction of the same variable at different scales. However, multi-scale modelling is a promising approach to model the distribution of Culicoides species, accounting much more for the ecology of biting midges, which uses different resources (breeding sites, hosts, etc. at
Relationship between Eurasian large-scale patterns and regional climate variability over the Black and Baltic Seas

Energy Technology Data Exchange (ETDEWEB)

Stankunavicius, G.; Pupienis, D. [Vilnius Univ. (Lithuania). Dept. of Hydrology and Climatology; Basharin, D. [National Academy of Science of Ukraine, Sevastopol (Ukraine). Sevastopol Marine Hydrophysical Inst.

2012-11-01

Using a NCEP/NCAR Reanalysis dataset and the empirical orthogonal function (EOF) analysis approach we studied interannual to decadal variabilities of the sea-level air pressure (SLP) and the surface air temperature (SAT) fields over Eurasia during the 2nd part of the 20th century. Our results agree with those of the previous studies, which conclude that Eurasian trends are the result of storm-path changes driven by the interdecadal behaviour of the NAO-like meridional dipole pattern in the Atlantic. On interannual and decadal time scales, significant synchronous correlations between correspondent modes of SAT and SLP EOF patterns were found. This fact suggests that there is a strong and stable Eurasian interrelationship between SAT and SLP large-scale fields which affects the local climate of two sub-regions: the Black and Baltic Seas. The climate variability in these sub-regions was studied in terms of Eurasian large-scale surface-temperature and air-pressure patterns responses. We concluded that the sub-regional climate variability substantially differs over the Black and Baltic Seas, and depends on different Eurasian large-scale patterns. We showed that the Baltic Sea region is influenced by the patterns arising primary from NAO-like meridional dipole, as well as Scandinavian patterns, while the Black Sea's SAT/SLP variability is influenced mainly by the second mode EOF (eastern Atlantic) and large scale tropospheric wave structures. (orig.)
Spatial scales of pollution from variable resolution satellite imaging.

Science.gov (United States)

Chudnovsky, Alexandra A; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

2013-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(2.5) as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM(2.5) and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM(2.5) ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM(2.5) levels and wind speed. Copyright © 2012 Elsevier Ltd. All rights reserved.
Integrated multi-scale modelling and simulation of nuclear fuels

International Nuclear Information System (INIS)

Valot, C.; Bertolus, M.; Masson, R.; Malerba, L.; Rachid, J.; Besmann, T.; Phillpot, S.; Stan, M.

2015-01-01

This chapter aims at discussing the objectives, implementation and integration of multi-scale modelling approaches applied to nuclear fuel materials. We will first show why the multi-scale modelling approach is required, due to the nature of the materials and by the phenomena involved under irradiation. We will then present the multiple facets of multi-scale modelling approach, while giving some recommendations with regard to its application. We will also show that multi-scale modelling must be coupled with appropriate multi-scale experiments and characterisation. Finally, we will demonstrate how multi-scale modelling can contribute to solving technology issues. (authors)
Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

Energy Technology Data Exchange (ETDEWEB)

Stander, Nielen [Livermore Software Technology Corporation, CA (United States); Basudhar, Anirban [Livermore Software Technology Corporation, CA (United States); Basu, Ushnish [Livermore Software Technology Corporation, CA (United States); Gandikota, Imtiaz [Livermore Software Technology Corporation, CA (United States); Savic, Vesna [General Motors, Flint, MI (United States); Sun, Xin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hu, XiaoHua [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Pourboghrat, Farhang [The Ohio State Univ., Columbus, OH (United States); Park, Taejoon [The Ohio State Univ., Columbus, OH (United States); Mapar, Aboozar [Michigan State Univ., East Lansing, MI (United States); Kumar, Sharvan [Brown Univ., Providence, RI (United States); Ghassemi-Armaki, Hassan [Brown Univ., Providence, RI (United States); Abu-Farha, Fadi [Clemson Univ., SC (United States)

2015-06-15

Ever-tightening regulations on fuel economy and carbon emissions demand continual innovation in finding ways for reducing vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials by adding material diversity, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing thickness while retaining sufficient strength and ductility required for durability and safety. Such a project was proposed and is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the Department of Energy. Under this program, new steel alloys (Third Generation Advanced High Strength Steel or 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. In this project the principal phases identified are (i) material identification, (ii) formability optimization and (iii) multi-disciplinary vehicle optimization. This paper serves as an introduction to the LS-OPT methodology and therefore mainly focuses on the first phase, namely an approach to integrate material identification using material models of different length scales. For this purpose, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a Homogenized State Variable (SV) model, is discussed and demonstrated. The paper concludes with proposals for integrating the multi-scale methodology into the overall vehicle design.
Characterizing Temperature Variability and Associated Large Scale Meteorological Patterns Across South America

Science.gov (United States)

Detzer, J.; Loikith, P. C.; Mechoso, C. R.; Barkhordarian, A.; Lee, H.

2017-12-01

South America's climate varies considerably owing to its large geographic range and diverse topographical features. Spanning the tropics to the mid-latitudes and from high peaks to tropical rainforest, the continent experiences an array of climate and weather patterns. Due to this considerable spatial extent, assessing temperature variability at the continent scale is particularly challenging. It is well documented in the literature that temperatures have been increasing across portions of South America in recent decades, and while there have been many studies that have focused on precipitation variability and change, temperature has received less scientific attention. Therefore, a more thorough understanding of the drivers of temperature variability is critical for interpreting future change. First, k-means cluster analysis is used to identify four primary modes of temperature variability across the continent, stratified by season. Next, composites of large scale meteorological patterns (LSMPs) are calculated for months assigned to each cluster. Initial results suggest that LSMPs, defined using meteorological variables such as sea level pressure (SLP), geopotential height, and wind, are able to identify synoptic scale mechanisms important for driving temperature variability at the monthly scale. Some LSMPs indicate a relationship with known recurrent modes of climate variability. For example, composites of geopotential height suggest that the Southern Annular Mode is an important, but not necessarily dominant, component of temperature variability over southern South America. This work will be extended to assess the drivers of temperature extremes across South America.
Causes of interannual to decadal variability of Gila River streamflow over the past century

Directory of Open Access Journals (Sweden)

M.A. Pascolini-Campbell

2015-03-01

Full Text Available Study region: The Gila River, New Mexico, is characterized by two peaks in streamflow: one in the winter–spring (December–May, and summer (August–September. The region is influenced both by Pacific SST variability as well as the North American Monsoon. Study focus: The mechanisms responsible for the variability of the winter–spring and summer streamflow peaks are investigated by correlation of streamflow with precipitation and sea surface temperature for 1928–2012. Decadal variability in the flow record is examined for a longer term perspective on Gila River streamflow using tree ring-based reconstructions of the Palmer Drought Severity Index (PDSI and the Standardized Precipitation Index (SPI. New hydrological insights for the region: Results indicate a strong influence of winter–spring precipitation and Pacific SST anomalies on the winter–spring streamflow, with El Niño conditions in the Pacific causing increased precipitation and streamflow. Decadal Pacific variability helps explain the transition from high winter flow in the late 20th century to lower flows in the most recent decade. The summer streamflow has a somewhat weaker correlation with precipitation and Pacific SST than the winter–spring streamflow. Its variability is more likely influenced by local North American Monsoon precipitation variability. PDSI and SPI reconstructions indicate much more severe and extended periods of droughts and pluvials in past centuries as well as periods of concurrent winter and summer drought. Keywords: Streamflow decadal variability, Drought, Pluvials, Treering, Teleconnections, North American Monsoon
Multi-scale and multi-orientation medical image analysis

NARCIS (Netherlands)

Haar Romenij, ter B.M.; Deserno, T.M.

2011-01-01

Inspired by multi-scale and multi-orientation mechanisms recognized in the first stages of our visual system, this chapter gives a tutorial overview of the basic principles. Images are discrete, measured data. The optimal aperture for an observation with as little artefacts as possible, is derived
Spatial scales of pollution from variable resolution satellite imaging

International Nuclear Information System (INIS)

Chudnovsky, Alexandra A.; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

2013-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM 2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM 2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM 2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM 2.5 levels and wind speed. - Highlights: ► The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. ► High resolution MAIAC AOD 1 km retrieval can be used to investigate within-city PM 2.5 variability. ► Low pollution days exhibit higher spatial variability of AOD and PM 2.5 then moderate pollution days. ► AOD spatial variability within urban area is higher during the lower wind speed conditions. - The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. The new high-resolution MAIAC AOD retrieval has the potential to capture PM 2.5 variability at the intra-urban scale.
Extremes in East African hydroclimate and links to Indo-Pacific variability on interannual to decadal timescales

Science.gov (United States)

Ummenhofer, Caroline C.; Kulüke, Marco; Tierney, Jessica E.

2018-04-01

East African hydroclimate exhibits considerable variability across a range of timescales, with implications for its population that depends on the region's two rainy seasons. Recent work demonstrated that current state-of-the-art climate models consistently underestimate the long rains in boreal spring over the Horn of Africa while overestimating the short rains in autumn. This inability to represent the seasonal cycle makes it problematic for climate models to project changes in East African precipitation. Here we consider whether this bias also has implications for understanding interannual and decadal variability in the East African long and short rains. Using a consistent framework with an unforced multi-century global coupled climate model simulation, the role of Indo-Pacific variability for East African rainfall is compared across timescales and related to observations. The dominant driver of East African rainfall anomalies critically depends on the timescale under consideration: Interannual variations in East African hydroclimate coincide with significant sea surface temperature (SST) anomalies across the Indo-Pacific, including those associated with the El Niño-Southern Oscillation (ENSO) in the eastern Pacific, and are linked to changes in the Walker circulation, regional winds and vertical velocities over East Africa. Prolonged drought/pluvial periods in contrast exhibit anomalous SST predominantly in the Indian Ocean and Indo-Pacific warm pool (IPWP) region, while eastern Pacific anomalies are insignificant. We assessed dominant frequencies in Indo-Pacific SST and found the eastern equatorial Pacific dominated by higher-frequency variability in the ENSO band, while the tropical Indian Ocean and IPWP exhibit lower-frequency variability beyond 10 years. This is consistent with the different contribution to regional precipitation anomalies for the eastern Pacific versus Indian Ocean and IPWP on interannual and decadal timescales, respectively. In the model
Consensus of Multi-Agent Systems with Prestissimo Scale-Free Networks

International Nuclear Information System (INIS)

Yang Hongyong; Lu Lan; Cao Kecai; Zhang Siying

2010-01-01

In this paper, the relations of the network topology and the moving consensus of multi-agent systems are studied. A consensus-prestissimo scale-free network model with the static preferential-consensus attachment is presented on the rewired link of the regular network. The effects of the static preferential-consensus BA network on the algebraic connectivity of the topology graph are compared with the regular network. The robustness gain to delay is analyzed for variable network topology with the same scale. The time to reach the consensus is studied for the dynamic network with and without communication delays. By applying the computer simulations, it is validated that the speed of the convergence of multi-agent systems can be greatly improved in the preferential-consensus BA network model with different configuration. (interdisciplinary physics and related areas of science and technology)
Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models.

Science.gov (United States)

Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

2014-01-01

The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. © 2014 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.
Preliminary Multi-Variable Parametric Cost Model for Space Telescopes

Science.gov (United States)

Stahl, H. Philip; Hendrichs, Todd

2010-01-01

This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.
Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

Directory of Open Access Journals (Sweden)

J. Fyke

2017-11-01

Full Text Available Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and ice core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.

A multi-decadal assessment of the performance of gauge- and model-based rainfall products over Saudi Arabia: Climatology, anomalies and trends

KAUST Repository

El Kenawy, Ahmed M.

2015-05-15

Many arid and semi-arid regions have sparse precipitation observing networks, which limits the capacity for detailed hydrological modelling, water resources management and flood forecasting efforts. The objective of this work is to evaluate the utility of relatively high-spatial resolution rainfall products to reproduce observed multi-decadal rainfall characteristics such as climatologies, anomalies and trends over Saudi Arabia. Our study compares the statistical characteristics of rainfall from 53 observatories over the reference period 1965-2005, with rainfall data from six widely used gauge-based products, including APHRODITE, GPCC, PRINCETON, UDEL, CRU and PREC/L. In addition, the performance of three global climate models (GCMs), including CCSM4, EC-EARTH and MRI-I-CGCM3, integrated as part of the Fifth Coupled Model Intercomparison Project (CMIP5), was also evaluated. Results indicate that the gauge-based products were generally skillful in reproducing rainfall characteristics in Saudi Arabia. In most cases, the gauge-based products were also able to capture the annual cycle, anomalies and climatologies of observed data, although significant inter-product variability was observed, depending on the assessment metric being used. In comparison, the GCM-based products generally exhibited poor performance, with larger biases and very weak correlations, particularly during the summertime. Importantly, all products generally failed to reproduce the observed long-term seasonal and annual trends in the region, particularly during the dry seasons (summer and autumn). Overall, this work suggests that selected gauge-based products with daily (APHRODITE and PRINCETON) and monthly (GPCC and CRU) resolutions show superior performance relative to other products, implying that they may be the most appropriate data source from which multi-decadal variations of rainfall can be investigated at the regional scale over Saudi Arabia. Discriminating these skillful products is
Multi-scale responses of scattering layers to environmental variability in Monterey Bay, California

Science.gov (United States)

Urmy, Samuel S.; Horne, John K.

2016-07-01

A 38 kHz upward-facing echosounder was deployed on the seafloor at a depth of 875 m in Monterey Bay, CA, USA (36° 42.748‧N, 122° 11.214‧W) from 27 February 2009 to 18 August 2010. This 18-month record of acoustic backscatter was compared to oceanographic time series from a nearby data buoy to investigate the responses of animals in sound-scattering layers to oceanic variability at seasonal and sub-seasonal time scales. Pelagic animals, as measured by acoustic backscatter, moved higher in the water column and decreased in abundance during spring upwelling, attributed to avoidance of a shoaling oxycline and advection offshore. Seasonal changes were most evident in a non-migrating scattering layer near 500 m depth that disappeared in spring and reappeared in summer, building to a seasonal maximum in fall. At sub-seasonal time scales, similar responses were observed after individual upwelling events, though they were much weaker than the seasonal relationship. Correlations of acoustic backscatter with oceanographic variability also differed with depth. Backscatter in the upper water column decreased immediately following upwelling, then increased approximately 20 days later. Similar correlations existed deeper in the water column, but at increasing lags, suggesting that near-surface productivity propagated down the water column at 10-15 m d-1, consistent with sinking speeds of marine snow measured in Monterey Bay. Sub-seasonal variability in backscatter was best correlated with sea-surface height, suggesting that passive physical transport was most important at these time scales.
A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

Science.gov (United States)

Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

2017-01-01

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.
Correlations of stock price fluctuations under multi-scale and multi-threshold scenarios

Science.gov (United States)

Sui, Guo; Li, Huajiao; Feng, Sida; Liu, Xueyong; Jiang, Meihui

2018-01-01

The multi-scale method is widely used in analyzing time series of financial markets and it can provide market information for different economic entities who focus on different periods. Through constructing multi-scale networks of price fluctuation correlation in the stock market, we can detect the topological relationship between each time series. Previous research has not addressed the problem that the original fluctuation correlation networks are fully connected networks and more information exists within these networks that is currently being utilized. Here we use listed coal companies as a case study. First, we decompose the original stock price fluctuation series into different time scales. Second, we construct the stock price fluctuation correlation networks at different time scales. Third, we delete the edges of the network based on thresholds and analyze the network indicators. Through combining the multi-scale method with the multi-threshold method, we bring to light the implicit information of fully connected networks.
Multi-scale salient feature extraction on mesh models

KAUST Repository

Yang, Yongliang; Shen, ChaoHui

2012-01-01

We present a new method of extracting multi-scale salient features on meshes. It is based on robust estimation of curvature on multiple scales. The coincidence between salient feature and the scale of interest can be established straightforwardly, where detailed feature appears on small scale and feature with more global shape information shows up on large scale. We demonstrate this multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection. Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes. © 2012 Springer-Verlag.
Study on high density multi-scale calculation technique

International Nuclear Information System (INIS)

Sekiguchi, S.; Tanaka, Y.; Nakada, H.; Nishikawa, T.; Yamamoto, N.; Yokokawa, M.

2004-01-01

To understand degradation of nuclear materials under irradiation, it is essential to know as much about each phenomenon observed from multi-scale points of view; they are micro-scale in atomic-level, macro-level in structural scale and intermediate level. In this study for application to meso-scale materials (100A ∼ 2μm), computer technology approaching from micro- and macro-scales was developed including modeling and computer application using computational science and technology method. And environmental condition of grid technology for multi-scale calculation was prepared. The software and MD (molecular dynamics) stencil for verifying the multi-scale calculation were improved and their movement was confirmed. (A. Hishinuma)
Multi-scale method for the resolution of the neutronic kinetics equations

International Nuclear Information System (INIS)

Chauvet, St.

2008-10-01

In this PhD thesis and in order to improve the time/precision ratio of the numerical simulation calculations, we investigate multi-scale techniques for the resolution of the reactor kinetics equations. We choose to focus on the mixed dual diffusion approximation and the quasi-static methods. We introduce a space dependency for the amplitude function which only depends on the time variable in the standard quasi-static context. With this new factorization, we develop two mixed dual problems which can be solved with Cea's solver MINOS. An algorithm is implemented, performing the resolution of these problems defined on different scales (for time and space). We name this approach: the Local Quasi-Static method. We present here this new multi-scale approach and its implementation. The inherent details of amplitude and shape treatments are discussed and justified. Results and performances, compared to MINOS, are studied. They illustrate the improvement on the time/precision ratio for kinetics calculations. Furthermore, we open some new possibilities to parallelize computations with MINOS. For the future, we also introduce some improvement tracks with adaptive scales. (author)
Reconstruction of regional climate and climate change in past decades

Science.gov (United States)

von Storch, H.; Feser, F.; Weisse, R.; Zahn, M.

2009-12-01

Regional climate models, which are constrained by large scale information (spectral nudging) provided by re-analyses, allow for the construction of a mostly homogeneous description of regional weather statistics since about 1950. The potential of this approach has been demonstrated for Northern Europe. That data set, named CoastDat, does not only contain hourly data on atmospheric variables, in particular wind, but also on marine weather, i.e., short term water level, current and sea state variations. Another example is the multi-decadal variability of Polar Lows in the subarctic waters. The utility of such data sets is broad, from risk assessments related to coastal wind and wave conditions, assessment of determining the causes for regional climate change, a-posteriori analysis of the efficiency of environmental legislation (example: lead). In the paper, the methodology is outlined, examples are provided and the utility of the product discussed.
Transitions of the Multi-Scale Singularity Trees

DEFF Research Database (Denmark)

Somchaipeng, Kerawit; Sporring, Jon; Kreiborg, Sven

2005-01-01

Multi-Scale Singularity Trees(MSSTs) [10] are multi-scale image descriptors aimed at representing the deep structures of images. Changes in images are directly translated to changes in the deep structures; therefore transitions in MSSTs. Because MSSTs can be used to represent the deep structure...
Decadal-scale climate drivers for glacial dynamics in Glacier National Park, Montana, USA

Science.gov (United States)

Pederson, Gregory T.; Fagre, Daniel B.; Gray, Stephen T.; Graumlich, Lisa J.

2004-06-01

Little Ice Age (14th-19th centuries A.D.) glacial maxima and 20th century retreat have been well documented in Glacier National Park, Montana, USA. However, the influence of regional and Pacific Basin driven climate variability on these events is poorly understood. We use tree-ring reconstructions of North Pacific surface temperature anomalies and summer drought as proxies for winter glacial accumulation and summer ablation, respectively, over the past three centuries. These records show that the 1850's glacial maximum was likely produced by ~70 yrs of cool/wet summers coupled with high snowpack. Post 1850, glacial retreat coincides with an extended period (>50 yr) of summer drought and low snowpack culminating in the exceptional events of 1917 to 1941 when retreat rates for some glaciers exceeded 100 m/yr. This research highlights potential local and ocean-based drivers of glacial dynamics, and difficulties in separating the effects of global climate change from regional expressions of decadal-scale climate variability.
Microphysics in Multi-scale Modeling System with Unified Physics

Science.gov (United States)

Tao, Wei-Kuo

2012-01-01

Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.
Improve projections of changes in southern African summer rainfall through comprehensive multi-timescale empirical statistical downscaling

Science.gov (United States)

Dieppois, B.; Pohl, B.; Eden, J.; Crétat, J.; Rouault, M.; Keenlyside, N.; New, M. G.

2017-12-01

The water management community has hitherto neglected or underestimated many of the uncertainties in climate impact scenarios, in particular, uncertainties associated with decadal climate variability. Uncertainty in the state-of-the-art global climate models (GCMs) is time-scale-dependant, e.g. stronger at decadal than at interannual timescales, in response to the different parameterizations and to internal climate variability. In addition, non-stationarity in statistical downscaling is widely recognized as a key problem, in which time-scale dependency of predictors plays an important role. As with global climate modelling, therefore, the selection of downscaling methods must proceed with caution to avoid unintended consequences of over-correcting the noise in GCMs (e.g. interpreting internal climate variability as a model bias). GCM outputs from the Coupled Model Intercomparison Project 5 (CMIP5) have therefore first been selected based on their ability to reproduce southern African summer rainfall variability and their teleconnections with Pacific sea-surface temperature across the dominant timescales. In observations, southern African summer rainfall has recently been shown to exhibit significant periodicities at the interannual timescale (2-8 years), quasi-decadal (8-13 years) and inter-decadal (15-28 years) timescales, which can be interpret as the signature of ENSO, the IPO, and the PDO over the region. Most of CMIP5 GCMs underestimate southern African summer rainfall variability and their teleconnections with Pacific SSTs at these three timescales. In addition, according to a more in-depth analysis of historical and pi-control runs, this bias is might result from internal climate variability in some of the CMIP5 GCMs, suggesting potential for bias-corrected prediction based empirical statistical downscaling. A multi-timescale regression based downscaling procedure, which determines the predictors across the different timescales, has thus been used to
Scale-dependent spatial variability in peatland lead pollution in the southern Pennines, UK.

Science.gov (United States)

Rothwell, James J; Evans, Martin G; Lindsay, John B; Allott, Timothy E H

2007-01-01

Increasingly, within-site and regional comparisons of peatland lead pollution have been undertaken using the inventory approach. The peatlands of the Peak District, southern Pennines, UK, have received significant atmospheric inputs of lead over the last few hundred years. A multi-core study at three peatland sites in the Peak District demonstrates significant within-site spatial variability in industrial lead pollution. Stochastic simulations reveal that 15 peat cores are required to calculate reliable lead inventories at the within-site and within-region scale for this highly polluted area of the southern Pennines. Within-site variability in lead pollution is dominant at the within-region scale. The study demonstrates that significant errors may be associated with peatland lead inventories at sites where only a single peat core has been used to calculate an inventory. Meaningful comparisons of lead inventories at the regional or global scale can only be made if the within-site variability of lead pollution has been quantified reliably.
OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

Directory of Open Access Journals (Sweden)

Y. Jia

2016-06-01

Full Text Available The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.
The Goddard multi-scale modeling system with unified physics

Directory of Open Access Journals (Sweden)

W.-K. Tao

2009-08-01

Full Text Available Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1 a cloud-resolving model (CRM, (2 a regional-scale model, the NASA unified Weather Research and Forecasting Model (WRF, and (3 a coupled CRM-GCM (general circulation model, known as the Goddard Multi-scale Modeling Framework or MMF. The same cloud-microphysical processes, long- and short-wave radiative transfer and land-surface processes are applied in all of the models to study explicit cloud-radiation and cloud-surface interactive processes in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator for comparison and validation with NASA high-resolution satellite data.

This paper reviews the development and presents some applications of the multi-scale modeling system, including results from using the multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols. In addition, use of the multi-satellite simulator to identify the strengths and weaknesses of the model-simulated precipitation processes will be discussed as well as future model developments and applications.
Multi-variable systems in nuclear power plant

International Nuclear Information System (INIS)

Collins, G.B.; Howell, J.

1982-01-01

Nuclear power plant are complex multi-variable dynamically interactive systems which employ many facets of systems and control theory in their analysis and design. Whole plant mathematical models must be developed and validated and in addition to their obvious role in control system synthesis and design, they are also widely used for operational constraint and plant malfunction analysis. The need for and scope of an integrated power plant control system is discussed and, as a specific example, the design of an integrated feedwater regulator is reviewed. The multi-variable frequency response analysis employed in the design is described in detail. (author)
A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

Directory of Open Access Journals (Sweden)

Marko Budinich

Full Text Available Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA and multi-objective flux variability analysis (MO-FVA. Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity that take place at the ecosystem scale.
Improvement and Extension of Shape Evaluation Criteria in Multi-Scale Image Segmentation

Science.gov (United States)

Sakamoto, M.; Honda, Y.; Kondo, A.

2016-06-01

From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region's shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape's diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape's reproducibility.
The swan song in context: long-time-scale X-ray variability of NGC 4051

Science.gov (United States)

Uttley, P.; McHardy, I. M.; Papadakis, I. E.; Guainazzi, M.; Fruscione, A.

1999-07-01

On 1998 May 9-11, the highly variable, low-luminosity Seyfert 1 galaxy NGC 4051 was observed in an unusual low-flux state by BeppoSAX, RXTE and EUVE. We present fits of the 4-15keV RXTE spectrum and BeppoSAX MECS spectrum obtained during this observation, which are consistent with the interpretation that the source had switched off, leaving only the spectrum of pure reflection from distant cold matter. We place this result in context by showing the X-ray light curve of NGC 4051 obtained by our RXTE monitoring campaign over the past two and a half years, which shows that the low state lasted for ~150d before the May observations (implying that the reflecting material is >10^17cm from the continuum source) and forms part of a light curve showing distinct variations in long-term average flux over time-scales > months. We show that the long-time-scale component to X-ray variability is intrinsic to the primary continuum and is probably distinct from the variability at shorter time-scales. The long-time-scale component to variability maybe associated with variations in the accretion flow of matter on to the central black hole. As the source approaches the low state, the variability process becomes non-linear. NGC 4051 may represent a microcosm of all X-ray variability in radio-quiet active galactic nuclei (AGNs), displaying in a few years a variety of flux states and variability properties which more luminous AGNs may pass through on time-scales of decades to thousands of years.
Decadal variability of extreme wave height representing storm severity in the northeast Atlantic and North Sea since the foundation of the Royal Society

Science.gov (United States)

Santo, H.; Taylor, P. H.; Gibson, R.

2016-09-01

Long-term estimation of extreme wave height remains a key challenge because of the short duration of available wave data, and also because of the possible impact of climate variability on ocean waves. Here, we analyse storm-based statistics to obtain estimates of extreme wave height at locations in the northeast Atlantic and North Sea using the NORA10 wave hindcast (1958-2011), and use a 5 year sliding window to examine temporal variability. The decadal variability is correlated to the North Atlantic oscillation and other atmospheric modes, using a six-term predictor model incorporating the climate indices and their Hilbert transforms. This allows reconstruction of the historic extreme climate back to 1661, using a combination of known and proxy climate indices. Significant decadal variability primarily driven by the North Atlantic oscillation is observed, and this should be considered for the long-term survivability of offshore structures and marine renewable energy devices. The analysis on wave climate reconstruction reveals that the variation of the mean, 99th percentile and extreme wave climates over decadal time scales for locations close to the dominant storm tracks in the open North Atlantic are comparable, whereas the wave climates for the rest of the locations including the North Sea are rather different.

Multi-scale biomedical systems: measurement challenges

International Nuclear Information System (INIS)

Summers, R

2016-01-01

Multi-scale biomedical systems are those that represent interactions in materials, sensors, and systems from a holistic perspective. It is possible to view such multi-scale activity using measurement of spatial scale or time scale, though in this paper only the former is considered. The biomedical application paradigm comprises interactions that range from quantum biological phenomena at scales of 10-12 for one individual to epidemiological studies of disease spread in populations that in a pandemic lead to measurement at a scale of 10+7. It is clear that there are measurement challenges at either end of this spatial scale, but those challenges that relate to the use of new technologies that deal with big data and health service delivery at the point of care are also considered. The measurement challenges lead to the use, in many cases, of model-based measurement and the adoption of virtual engineering. It is these measurement challenges that will be uncovered in this paper. (paper)
2D deblending using the multi-scale shaping scheme

Science.gov (United States)

Li, Qun; Ban, Xingan; Gong, Renbin; Li, Jinnuo; Ge, Qiang; Zu, Shaohuan

2018-01-01

Deblending can be posed as an inversion problem, which is ill-posed and requires constraint to obtain unique and stable solution. In blended record, signal is coherent, whereas interference is incoherent in some domains (e.g., common receiver domain and common offset domain). Due to the different sparsity, coefficients of signal and interference locate in different curvelet scale domains and have different amplitudes. Take into account the two differences, we propose a 2D multi-scale shaping scheme to constrain the sparsity to separate the blended record. In the domain where signal concentrates, the multi-scale scheme passes all the coefficients representing signal, while, in the domain where interference focuses, the multi-scale scheme suppresses the coefficients representing interference. Because the interference is suppressed evidently at each iteration, the constraint of multi-scale shaping operator in all scale domains are weak to guarantee the convergence of algorithm. We evaluate the performance of the multi-scale shaping scheme and the traditional global shaping scheme by using two synthetic and one field data examples.
ReOBS: a new approach to synthesize long-term multi-variable dataset and application to the SIRTA supersite

Science.gov (United States)

Chiriaco, Marjolaine; Dupont, Jean-Charles; Bastin, Sophie; Badosa, Jordi; Lopez, Julio; Haeffelin, Martial; Chepfer, Helene; Guzman, Rodrigo

2018-05-01

A scientific approach is presented to aggregate and harmonize a set of 60 geophysical variables at hourly timescale over a decade, and to allow multiannual and multi-variable studies combining atmospheric dynamics and thermodynamics, radiation, clouds and aerosols from ground-based observations. Many datasets from ground-based observations are currently in use worldwide. They are very valuable because they contain complete and precise information due to their spatio-temporal co-localization over more than a decade. These datasets, in particular the synergy between different type of observations, are under-used because of their complexity and diversity due to calibration, quality control, treatment, format, temporal averaging, metadata, etc. Two main results are presented in this article: (1) a set of methods available for the community to robustly and reliably process ground-based data at an hourly timescale over a decade is described and (2) a single netCDF file is provided based on the SIRTA supersite observations. This file contains approximately 60 geophysical variables (atmospheric and in ground) hourly averaged over a decade for the longest variables. The netCDF file is available and easy to use for the community. In this article, observations are re-analyzed. The prefix re refers to six main steps: calibration, quality control, treatment, hourly averaging, homogenization of the formats and associated metadata, as well as expertise on more than a decade of observations. In contrast, previous studies (i) took only some of these six steps into account for each variable, (ii) did not aggregate all variables together in a single file and (iii) did not offer an hourly resolution for about 60 variables over a decade (for the longest variables). The approach described in this article can be applied to different supersites and to additional variables. The main implication of this work is that complex atmospheric observations are made readily available for scientists
Algorithmic foundation of multi-scale spatial representation

CERN Document Server

Li, Zhilin

2006-01-01

With the widespread use of GIS, multi-scale representation has become an important issue in the realm of spatial data handling. However, no book to date has systematically tackled the different aspects of this discipline. Emphasizing map generalization, Algorithmic Foundation of Multi-Scale Spatial Representation addresses the mathematical basis of multi-scale representation, specifically, the algorithmic foundation.Using easy-to-understand language, the author focuses on geometric transformations, with each chapter surveying a particular spatial feature. After an introduction to the essential operations required for geometric transformations as well as some mathematical and theoretical background, the book describes algorithms for a class of point features/clusters. It then examines algorithms for individual line features, such as the reduction of data points, smoothing (filtering), and scale-driven generalization, followed by a discussion of algorithms for a class of line features including contours, hydrog...
Multi-Scale Scattering Transform in Music Similarity Measuring

Science.gov (United States)

Wang, Ruobai

Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.
Scale-dependent spatial variability in peatland lead pollution in the southern Pennines, UK

International Nuclear Information System (INIS)

Rothwell, James J.; Evans, Martin G.; Lindsay, John B.; Allott, Timothy E.H.

2007-01-01

Increasingly, within-site and regional comparisons of peatland lead pollution have been undertaken using the inventory approach. The peatlands of the Peak District, southern Pennines, UK, have received significant atmospheric inputs of lead over the last few hundred years. A multi-core study at three peatland sites in the Peak District demonstrates significant within-site spatial variability in industrial lead pollution. Stochastic simulations reveal that 15 peat cores are required to calculate reliable lead inventories at the within-site and within-region scale for this highly polluted area of the southern Pennines. Within-site variability in lead pollution is dominant at the within-region scale. The study demonstrates that significant errors may be associated with peatland lead inventories at sites where only a single peat core has been used to calculate an inventory. Meaningful comparisons of lead inventories at the regional or global scale can only be made if the within-site variability of lead pollution has been quantified reliably. - Multiple peat cores are required for accurate peatland Pb inventories
BROAD ABSORPTION LINE VARIABILITY ON MULTI-YEAR TIMESCALES IN A LARGE QUASAR SAMPLE

Energy Technology Data Exchange (ETDEWEB)

Filiz Ak, N.; Brandt, W. N.; Schneider, D. P. [Department of Astronomy and Astrophysics, Pennsylvania State University, University Park, PA 16802 (United States); Hall, P. B. [Department of Physics and Astronomy, York University, 4700 Keele St., Toronto, Ontario, M3J 1P3 (Canada); Anderson, S. F. [Astronomy Department, University of Washington, Seattle, WA 98195 (United States); Hamann, F. [Department of Astronomy, University of Florida, Gainesville, FL 32611-2055 (United States); Lundgren, B. F. [Department of Astronomy, University of Wisconsin, Madison, WI 53706 (United States); Myers, Adam D. [Department of Physics and Astronomy, University of Wyoming, Laramie, WY 82071 (United States); Pâris, I. [Departamento de Astronomía, Universidad de Chile, Casilla 36-D, Santiago (Chile); Petitjean, P. [Universite Paris 6, Institut d' Astrophysique de Paris, 75014, Paris (France); Ross, Nicholas P. [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 92420 (United States); Shen, Yue [Harvard-Smithsonian Center for Astrophysics, 60 Garden St., MS-51, Cambridge, MA 02138 (United States); York, Don, E-mail: nfilizak@astro.psu.edu [The University of Chicago, Department of Astronomy and Astrophysics, Chicago, IL 60637 (United States)

2013-11-10

We present a detailed investigation of the variability of 428 C IV and 235 Si IV broad absorption line (BAL) troughs identified in multi-epoch observations of 291 quasars by the Sloan Digital Sky Survey-I/II/III. These observations primarily sample rest-frame timescales of 1-3.7 yr over which significant rearrangement of the BAL wind is expected. We derive a number of observational results on, e.g., the frequency of BAL variability, the velocity range over which BAL variability occurs, the primary observed form of BAL-trough variability, the dependence of BAL variability upon timescale, the frequency of BAL strengthening versus weakening, correlations between BAL variability and BAL-trough profiles, relations between C IV and Si IV BAL variability, coordinated multi-trough variability, and BAL variations as a function of quasar properties. We assess implications of these observational results for quasar winds. Our results support models where most BAL absorption is formed within an order-of-magnitude of the wind-launching radius, although a significant minority of BAL troughs may arise on larger scales. We estimate an average lifetime for a BAL trough along our line-of-sight of a few thousand years. BAL disappearance and emergence events appear to be extremes of general BAL variability, rather than being qualitatively distinct phenomena. We derive the parameters of a random-walk model for BAL EW variability, finding that this model can acceptably describe some key aspects of EW variability. The coordinated trough variability of BAL quasars with multiple troughs suggests that changes in 'shielding gas' may play a significant role in driving general BAL variability.
The Scaling LInear Macroweather model (SLIM): using scaling to forecast global scale macroweather from months to decades

Science.gov (United States)

Lovejoy, S.; del Rio Amador, L.; Hébert, R.

2015-03-01

At scales of ≈ 10 days (the lifetime of planetary scale structures), there is a drastic transition from high frequency weather to low frequency macroweather. This scale is close to the predictability limits of deterministic atmospheric models; so that in GCM macroweather forecasts, the weather is a high frequency noise. But neither the GCM noise nor the GCM climate is fully realistic. In this paper we show how simple stochastic models can be developped that use empirical data to force the statistics and climate to be realistic so that even a two parameter model can outperform GCM's for annual global temperature forecasts. The key is to exploit the scaling of the dynamics and the enormous stochastic memories that it implies. Since macroweather intermittency is low, we propose using the simplest model based on fractional Gaussian noise (fGn): the Scaling LInear Macroweather model (SLIM). SLIM is based on a stochastic ordinary differential equations, differing from usual linear stochastic models (such as the Linear Inverse Modelling, LIM) in that it is of fractional rather than integer order. Whereas LIM implicitly assumes there is no low frequency memory, SLIM has a huge memory that can be exploited. Although the basic mathematical forecast problem for fGn has been solved, we approach the problem in an original manner notably using the method of innovations to obtain simpler results on forecast skill and on the size of the effective system memory. A key to successful forecasts of natural macroweather variability is to first remove the low frequency anthropogenic component. A previous attempt to use fGn for forecasts had poor results because this was not done. We validate our theory using hindcasts of global and Northern Hemisphere temperatures at monthly and annual resolutions. Several nondimensional measures of forecast skill - with no adjustable parameters - show excellent agreement with hindcasts and these show some skill even at decadal scales. We also compare
The impact of resolution on the adjustment and decadal variability of the Atlantic meridional overturning circulation in a coupled climate model

Energy Technology Data Exchange (ETDEWEB)

Hodson, Daniel L.R.; Sutton, Rowan T. [University of Reading, NCAS-Climate, Department of Meteorology, Earley Gate, PO Box 243, Reading (United Kingdom)

2012-12-15

Variations in the Atlantic meridional overturning circulation (MOC) exert an important influence on climate, particularly on decadal time scales. Simulation of the MOC in coupled climate models is compromised, to a degree that is unknown, by their lack of fidelity in resolving some of the key processes involved. There is an overarching need to increase the resolution and fidelity of climate models, but also to assess how increases in resolution influence the simulation of key phenomena such as the MOC. In this study we investigate the impact of significantly increasing the (ocean and atmosphere) resolution of a coupled climate model on the simulation of MOC variability by comparing high and low resolution versions of the same model. In both versions, decadal variability of the MOC is closely linked to density anomalies that propagate from the Labrador Sea southward along the deep western boundary. We demonstrate that the MOC adjustment proceeds more rapidly in the higher resolution model due the increased speed of western boundary waves. However, the response of the Atlantic sea surface temperatures to MOC variations is relatively robust - in pattern if not in magnitude - across the two resolutions. The MOC also excites a coupled ocean-atmosphere response in the tropical Atlantic in both model versions. In the higher resolution model, but not the lower resolution model, there is evidence of a significant response in the extratropical atmosphere over the North Atlantic 6 years after a maximum in the MOC. In both models there is evidence of a weak negative feedback on deep density anomalies in the Labrador Sea, and hence on the MOC (with a time scale of approximately ten years). Our results highlight the need for further work to understand the decadal variability of the MOC and its simulation in climate models. (orig.)
IMPROVEMENT AND EXTENSION OF SHAPE EVALUATION CRITERIA IN MULTI-SCALE IMAGE SEGMENTATION

Directory of Open Access Journals (Sweden)

M. Sakamoto

2016-06-01

Full Text Available From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region’s shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape’s diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape’s reproducibility.
Stochastic simulation and decadal prediction of hydroclimate in the Western Himalayas

Science.gov (United States)

Robertson, A. W.; Chekroun, M. D.; Cook, E.; D'Arrigo, R.; Ghil, M.; Greene, A. M.; Holsclaw, T.; Kondrashov, D. A.; Lall, U.; Lu, M.; Smyth, P.

2012-12-01

Improved estimates of climate over the next 10 to 50 years are needed for long-term planning in water resource and flood management. However, the task of effectively incorporating the results of climate change research into decision-making face a ``double conflict of scales'': the temporal scales of climate model projections are too long, while their usable spatial scales (global to planetary) are much larger than those needed for actual decision making (at the regional to local level). This work is designed to help tackle this ``double conflict'' in the context of water management over monsoonal Asia, based on dendroclimatic multi-century reconstructions of drought indices and river flows. We identify low-frequency modes of variability with time scales from interannual to interdecadal based on these series, and then generate future scenarios based on (a) empirical model decadal predictions, and (b) stochastic simulations generated with autoregressive models that reproduce the power spectrum of the data. Finally, we consider how such scenarios could be used to develop reservoir optimization models. Results will be presented based on multi-century Upper Indus river discharge reconstructions that exhibit a strong periodicity near 27 years that is shown to yield some retrospective forecasting skill over the 1700-2000 period, at a 15-yr yield time. Stochastic simulations of annual PDSI drought index values over the Upper Indus basin are constructed using Empirical Model Reduction; their power spectra are shown to be quite realistic, with spectral peaks near 5--8 years.
Rainfall variability, climate change and regionalization in the African monsoon region

International Nuclear Information System (INIS)

Fontaine, Bernard; Roucou, Pascal; Vigaud, Nicolas; Camara, Moctar; Konare, Abdourahamane; Sanda, Seidou Ibrah; Diedhiou, Arona; Janicot, Serge

2012-01-01

This summary recalls some results at the end of the AMMA international experiment (2003-2010) in terms of variability of the African monsoon at the intra-seasonal to multi-decadal scales and of climate prospective. The results confirmed the weight of surface temperatures and marine tele-connections for inter-annual and decadal fluctuations and stressed the importance of atmospheric variability. They also described the dominant modes of intra-seasonal variability as their interactions with the surface. Several hypotheses involving memory effects related to soil water and vegetation, particularly in boreal spring and autumn have also been made. Prospective analysis from model output suggests rainfall surplus around 2050 over the Eastern-central Sahel and relative deficit to the West. Phase 2 of AMMA (2010-2020) will focus more on aspects that have a high social impact in direct collaboration with meteorological services predictability, prediction scores, operational indicators, evaluation of the part of anthropogenic forcing in the current and future variations. (authors)
Conformal-Based Surface Morphing and Multi-Scale Representation

Directory of Open Access Journals (Sweden)

Ka Chun Lam

2014-05-01

Full Text Available This paper presents two algorithms, based on conformal geometry, for the multi-scale representations of geometric shapes and surface morphing. A multi-scale surface representation aims to describe a 3D shape at different levels of geometric detail, which allows analyzing or editing surfaces at the global or local scales effectively. Surface morphing refers to the process of interpolating between two geometric shapes, which has been widely applied to estimate or analyze deformations in computer graphics, computer vision and medical imaging. In this work, we propose two geometric models for surface morphing and multi-scale representation for 3D surfaces. The basic idea is to represent a 3D surface by its mean curvature function, H, and conformal factor function λ, which uniquely determine the geometry of the surface according to Riemann surface theory. Once we have the (λ, H parameterization of the surface, post-processing of the surface can be done directly on the conformal parameter domain. In particular, the problem of multi-scale representations of shapes can be reduced to the signal filtering on the λ and H parameters. On the other hand, the surface morphing problem can be transformed to an interpolation process of two sets of (λ, H parameters. We test the proposed algorithms on 3D human face data and MRI-derived brain surfaces. Experimental results show that our proposed methods can effectively obtain multi-scale surface representations and give natural surface morphing results.
A multi-decadal wind-wave hindcast for the North Sea 1949-2014: coastDat2

Science.gov (United States)

Groll, Nikolaus; Weisse, Ralf

2017-12-01

Long and consistent wave data are important for analysing wave climate variability and change. Moreover, such wave data are also needed in coastal and offshore design and for addressing safety-related issues at sea. Using the third-generation spectral wave model WAM a multi-decadal wind-wave hindcast for the North Sea covering the period 1949-2014 was produced. The hindcast is part of the coastDat database representing a consistent and homogeneous met-ocean data set. It is shown that despite not being perfect, data from the wave hindcast are generally suitable for wave climate analysis. In particular, comparisons of hindcast data with in situ and satellite observations show on average a reasonable agreement, while a tendency towards overestimation of the highest waves could be inferred. Despite these limitations, the wave hindcast still provides useful data for assessing wave climate variability and change as well as for risk analysis, in particular when conservative estimates are needed. Hindcast data are stored at the World Data Center for Climate (WDCC) and can be freely accessed using the doi:10.1594/WDCC/coastDat-2_WAM-North_Sea Groll and Weisse(2016) or via the coastDat web-page http://www.coastdat.de.
Multi-scale symbolic transfer entropy analysis of EEG

Science.gov (United States)

Yao, Wenpo; Wang, Jun

2017-10-01

From both global and local perspectives, we symbolize two kinds of EEG and analyze their dynamic and asymmetrical information using multi-scale transfer entropy. Multi-scale process with scale factor from 1 to 199 and step size of 2 is applied to EEG of healthy people and epileptic patients, and then the permutation with embedding dimension of 3 and global approach are used to symbolize the sequences. The forward and reverse symbol sequences are taken as the inputs of transfer entropy. Scale factor intervals of permutation and global way are (37, 57) and (65, 85) where the two kinds of EEG have satisfied entropy distinctions. When scale factor is 67, transfer entropy of the healthy and epileptic subjects of permutation, 0.1137 and 0.1028, have biggest difference. And the corresponding values of the global symbolization is 0.0641 and 0.0601 which lies in the scale factor of 165. Research results show that permutation which takes contribution of local information has better distinction and is more effectively applied to our multi-scale transfer entropy analysis of EEG.
Multi-Model Assessment of Trends and Variability in Terrestrial Carbon Uptake in India

Science.gov (United States)

Rao, A. S.; Bala, G.; Ravindranath, N. H.

2015-12-01

Indian terrestrial ecosystem exhibits large temporal and spatial variability in carbon sources and sinks due to its monsoon based climate system, diverse land use and land cover distribution and cultural practices. In this study, a multi-model based assessment is made to study the trends and variability in the land carbon uptake for India over the 20th century. Data from nine models which are a part of a recent land surface model intercomparison project called TRENDY is used for the study. These models are driven with common forcing data over the period of 1901-2010. Model output variables assessed include: gross primary production (GPP), heterotrophic respiration (Rh), autotrophic respiration (Ra) and net primary production (NPP). The net ecosystem productivity (NEP) for the Indian region was calculated as a difference of NPP and Rh and it was found that NEP for the region indicates an estimated increase in uptake over the century by -0.6 TgC/year per year. NPP for India also shows an increasing trend of 2.03% per decade from 1901-2010. Seasonal variation in the multimodel mean NPP is maximum during the southwest monsoon period (JJA) followed by the post monsoon period (SON) and is attributed to the maximum in rainfall for the region during the months of JJA. To attribute the changes seen in the land carbon variables, influence of climatic drivers such as precipitation, temperature and remote influences of large scale phenomenon such as ENSO on the land carbon of the region are also estimated in the study. It is found that although changes in precipitation shows a good correlation to the changes seen in NEP, remote drivers like ENSO do not have much effect on them. The Net Ecosystem Exchange is calculated with the inclusion of the land use change flux and fire flux from the models. NEE suggests that the region behaves as a small sink for carbon with an net uptake of 5 GtC over the past hundred years.
IUTAM Symposium on Innovative Numerical Approaches for Materials and Structures in Multi-Field and Multi-Scale Problems : in Honor of Michael Ortiz's 60th Birthday

CERN Document Server

Pandolfi, Anna

2016-01-01

This book provides readers with a detailed insight into diverse and exciting recent developments in computational solid mechanics, documenting new perspectives and horizons. The topics addressed cover a wide range of current research, from computational materials modeling, including crystal plasticity, micro-structured materials, and biomaterials, to multi-scale simulations of multi-physics phenomena. Particular emphasis is placed on pioneering discretization methods for the solution of coupled non-linear problems at different length scales. The book, written by leading experts, reflects the remarkable advances that have been made in the field over the past decade and more, largely due to the development of a sound mathematical background and efficient computational strategies. The contents build upon the 2014 IUTAM symposium celebrating the 60th birthday of Professor Michael Ortiz, to whom this book is dedicated. His work has long been recognized as pioneering and is a continuing source of inspiration for ma...
Analysis of multi-scale morphodynamic behaviour of a high energy beach facing the Sea of Japan

Directory of Open Access Journals (Sweden)

Harshinie Urmila Karunarathna

2015-07-01

Full Text Available Monthly cross shore beach profiles measured at the Ogata Wave Observation pier located in Joetsu-Ogata Coast, Niigata Prefecture, Japan, was analysed to investigate multi-scale morphodynamic beach behaviour. The Ogata beach, facing the Sea of Japan, is subjected to high energy wave conditions with that has a strong winter/summer seasonal signature. The measured beach profiles at the beach show very significant variability where cross-shore movement of shoreline position and lowering of the beach at the location of measurements exceed 20 m and 4 m respectively. The shoreline position seems to follow the seasonal variability of incident wave climate where a correlation coefficient of 0.77 was found between monthly averaged incident significant wave height and the measured monthly shoreline position. During the summer months, the beach variability mostly concentrated to in the sub-tidal part of the profile, while a significant amount of upper beach change was observed during the winter months. The beach profile shape was found to rotate between three different beach states in time; (i concave reflective profile; (ii profile with sub-tidal berm; and (iii gentle, dissipative profile. Empirical Orthogonal Function (EOF analysis of the profiles show that the variability of beach profile shape is dominated by (a upper shoreface steepening; (b sub tidal berm development and dissipation; and (c variability of the overall profile slope, which have some longer than seasonal cyclic signatures. Comparison of temporal EOFs with climate indices such as Southern Oscillation Index and Pacific Decadal Oscillation index shows notable some correlations between profile change and climatic variability in the region. The analysis also shows that the morphological variability of Joetsu-Ogata Coast has similarities and some distinct spatial and temporal differences to beaches of similar kind found elsewhere.
Multi-scale simulation for homogenization of cement media

International Nuclear Information System (INIS)

Abballe, T.

2011-01-01

To solve diffusion problems on cement media, two scales must be taken into account: a fine scale, which describes the micrometers wide microstructures present in the media, and a work scale, which is usually a few meters long. Direct numerical simulations are almost impossible because of the huge computational resources (memory, CPU time) required to assess both scales at the same time. To overcome this problem, we present in this thesis multi-scale resolution methods using both Finite Volumes and Finite Elements, along with their efficient implementations. More precisely, we developed a multi-scale simulation tool which uses the SALOME platform to mesh domains and post-process data, and the parallel calculation code MPCube to solve problems. This SALOME/MPCube tool can solve automatically and efficiently multi-scale simulations. Parallel structure of computer clusters can be use to dispatch the more time-consuming tasks. We optimized most functions to account for cement media specificities. We presents numerical experiments on various cement media samples, e.g. mortar and cement paste. From these results, we manage to compute a numerical effective diffusivity of our cement media and to reconstruct a fine scale solution. (author) [fr
MEGAPOLI: concept of multi-scale modelling of megacity impact on air quality and climate

Science.gov (United States)

Baklanov, A.; Lawrence, M.; Pandis, S.; Mahura, A.; Finardi, S.; Moussiopoulos, N.; Beekmann, M.; Laj, P.; Gomes, L.; Jaffrezo, J.-L.; Borbon, A.; Coll, I.; Gros, V.; Sciare, J.; Kukkonen, J.; Galmarini, S.; Giorgi, F.; Grimmond, S.; Esau, I.; Stohl, A.; Denby, B.; Wagner, T.; Butler, T.; Baltensperger, U.; Builtjes, P.; van den Hout, D.; van der Gon, H. D.; Collins, B.; Schluenzen, H.; Kulmala, M.; Zilitinkevich, S.; Sokhi, R.; Friedrich, R.; Theloke, J.; Kummer, U.; Jalkinen, L.; Halenka, T.; Wiedensholer, A.; Pyle, J.; Rossow, W. B.

2010-11-01

The EU FP7 Project MEGAPOLI: "Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation" (http://megapoli.info) brings together leading European research groups, state-of-the-art scientific tools and key players from non-European countries to investigate the interactions among megacities, air quality and climate. MEGAPOLI bridges the spatial and temporal scales that connect local emissions, air quality and weather with global atmospheric chemistry and climate. The suggested concept of multi-scale integrated modelling of megacity impact on air quality and climate and vice versa is discussed in the paper. It requires considering different spatial and temporal dimensions: time scales from seconds and hours (to understand the interaction mechanisms) up to years and decades (to consider the climate effects); spatial resolutions: with model down- and up-scaling from street- to global-scale; and two-way interactions between meteorological and chemical processes.

Multi-Decadal Averages of Basal Melt for Ross Ice Shelf, Antarctica Using Airborne Observations

Science.gov (United States)

Das, I.; Bell, R. E.; Tinto, K. J.; Frearson, N.; Kingslake, J.; Padman, L.; Siddoway, C. S.; Fricker, H. A.

2017-12-01

Changes in ice shelf mass balance are key to the long term stability of the Antarctic Ice Sheet. Although the most extensive ice shelf mass loss currently is occurring in the Amundsen Sea sector of West Antarctica, many other ice shelves experience changes in thickness on time scales from annual to ice age cycles. Here, we focus on the Ross Ice Shelf. An 18-year record (1994-2012) of satellite radar altimetry shows substantial variability in Ross Ice Shelf height on interannual time scales, complicating detection of potential long-term climate-change signals in the mass budget of this ice shelf. Variability of radar signal penetration into the ice-shelf surface snow and firn layers further complicates assessment of mass changes. We investigate Ross Ice Shelf mass balance using aerogeophysical data from the ROSETTA-Ice surveys using IcePod. We use two ice-penetrating radars; a 2 GHz unit that images fine-structure in the upper 400 m of the ice surface and a 360 MHz radar to identify the ice shelf base. We have identified internal layers that are continuous along flow from the grounding line to the ice shelf front. Based on layer continuity, we conclude that these layers must be the horizons between the continental ice of the outlet glaciers and snow accumulation once the ice is afloat. We use the Lagrangian change in thickness of these layers, after correcting for strain rates derived using modern day InSAR velocities, to estimate multidecadal averaged basal melt rates. This method provides a novel way to quantify basal melt, avoiding the confounding impacts of spatial and short-timescale variability in surface accumulation and firn densification processes. Our estimates show elevated basal melt rates (> -1m/yr) around Byrd and Mullock glaciers within 100 km from the ice shelf front. We also compare modern InSAR velocity derived strain rates with estimates from the comprehensive ground-based RIGGS observations during 1973-1978 to estimate the potential magnitude of
Validating Remotely Sensed Land Surface Evapotranspiration Based on Multi-scale Field Measurements

Science.gov (United States)

Jia, Z.; Liu, S.; Ziwei, X.; Liang, S.

2012-12-01

The land surface evapotranspiration plays an important role in the surface energy balance and the water cycle. There have been significant technical and theoretical advances in our knowledge of evapotranspiration over the past two decades. Acquisition of the temporally and spatially continuous distribution of evapotranspiration using remote sensing technology has attracted the widespread attention of researchers and managers. However, remote sensing technology still has many uncertainties coming from model mechanism, model inputs, parameterization schemes, and scaling issue in the regional estimation. Achieving remotely sensed evapotranspiration (RS_ET) with confident certainty is required but difficult. As a result, it is indispensable to develop the validation methods to quantitatively assess the accuracy and error sources of the regional RS_ET estimations. This study proposes an innovative validation method based on multi-scale evapotranspiration acquired from field measurements, with the validation results including the accuracy assessment, error source analysis, and uncertainty analysis of the validation process. It is a potentially useful approach to evaluate the accuracy and analyze the spatio-temporal properties of RS_ET at both the basin and local scales, and is appropriate to validate RS_ET in diverse resolutions at different time-scales. An independent RS_ET validation using this method was presented over the Hai River Basin, China in 2002-2009 as a case study. Validation at the basin scale showed good agreements between the 1 km annual RS_ET and the validation data such as the water balanced evapotranspiration, MODIS evapotranspiration products, precipitation, and landuse types. Validation at the local scale also had good results for monthly, daily RS_ET at 30 m and 1 km resolutions, comparing to the multi-scale evapotranspiration measurements from the EC and LAS, respectively, with the footprint model over three typical landscapes. Although some
Impact of Emissions and Long-Range Transport on Multi-Decadal Aerosol Trends: Implications for Air Quality and Climate

Science.gov (United States)

Chin, Mian

2012-01-01

We present a global model analysis of the impact of long-range transport and anthropogenic emissions on the aerosol trends in the major pollution regions in the northern hemisphere and in the Arctic in the past three decades. We will use the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model to analyze the multi-spatial and temporal scale data, including observations from Terra, Aqua, and CALIPSO satellites and from the long-term surface monitoring stations. We will analyze the source attribution (SA) and source-receptor (SR) relationships in North America, Europe, East Asia, South Asia, and the Arctic at the surface and free troposphere and establish the quantitative linkages between emissions from different source regions. We will discuss the implications for regional air quality and climate change.
Assessment of Heart Rate Variability during an Endurance Mountain Trail Race by Multi-Scale Entropy Analysis

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Montserrat Vallverdú

2017-12-01

Full Text Available The aim of the study was to analyze heart rate variability (HRV response to high-intensity exercise during a 35-km mountain trail race and to ascertain whether fitness level could influence autonomic nervous system (ANS modulation. Time-domain, frequency-domain, and multi-scale entropy (MSE indexes were calculated for eleven mountain-trail runners who completed the race. Many changes were observed, mostly related to exercise load and fatigue. These changes were characterized by increased mean values and standard deviations of the normal-to-normal intervals associated with sympathetic activity, and by decreased differences between successive intervals related to parasympathetic activity. Normalized low frequency (LF power suggested that ANS modulation varied greatly during the race and between individuals. Normalized high frequency (HF power, associated with parasympathetic activity, varied considerably over the race, and tended to decrease at the final stages, whereas changes in the LF/HF ratio corresponded to intervals with varying exercise load. MSE indexes, related to system complexity, indicated the existence of many interactions between the heart and its neurological control mechanism. The time-domain, frequency-domain, and MSE indexes were also able to discriminate faster from slower runners, mainly in the more difficult and in the final stages of the race. These findings suggest the use of HRV analysis to study cardiac function mechanisms in endurance sports.
Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

Science.gov (United States)

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding
Land-Atmosphere Coupling in the Multi-Scale Modelling Framework

Science.gov (United States)

Kraus, P. M.; Denning, S.

2015-12-01

The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced
Managing living marine resources in a dynamic environment: The role of seasonal to decadal climate forecasts

Science.gov (United States)

Tommasi, Desiree; Stock, Charles A.; Hobday, Alistair J.; Methot, Rick; Kaplan, Isaac C.; Eveson, J. Paige; Holsman, Kirstin; Miller, Timothy J.; Gaichas, Sarah; Gehlen, Marion; Pershing, Andrew; Vecchi, Gabriel A.; Msadek, Rym; Delworth, Tom; Eakin, C. Mark; Haltuch, Melissa A.; Séférian, Roland; Spillman, Claire M.; Hartog, Jason R.; Siedlecki, Samantha; Samhouri, Jameal F.; Muhling, Barbara; Asch, Rebecca G.; Pinsky, Malin L.; Saba, Vincent S.; Kapnick, Sarah B.; Gaitan, Carlos F.; Rykaczewski, Ryan R.; Alexander, Michael A.; Xue, Yan; Pegion, Kathleen V.; Lynch, Patrick; Payne, Mark R.; Kristiansen, Trond; Lehodey, Patrick; Werner, Francisco E.

2017-03-01

Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefitting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystem-relevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.
Multi spectral scaling data acquisition system

International Nuclear Information System (INIS)

Behere, Anita; Patil, R.D.; Ghodgaonkar, M.D.; Gopalakrishnan, K.R.

1997-01-01

In nuclear spectroscopy applications, it is often desired to acquire data at high rate with high resolution. With the availability of low cost computers, it is possible to make a powerful data acquisition system with minimum hardware and software development, by designing a PC plug-in acquisition board. But in using the PC processor for data acquisition, the PC can not be used as a multitasking node. Keeping this in view, PC plug-in acquisition boards with on-board processor find tremendous applications. Transputer based data acquisition board has been designed which can be configured as a high count rate pulse height MCA or as a Multi Spectral Scaler. Multi Spectral Scaling (MSS) is a new technique, in which multiple spectra are acquired in small time frames and are then analyzed. This paper describes the details of this multi spectral scaling data acquisition system. 2 figs
The ScaLIng Macroweather Model (SLIMM): using scaling to forecast global-scale macroweather from months to decades

Science.gov (United States)

Lovejoy, S.; del Rio Amador, L.; Hébert, R.

2015-09-01

On scales of ≈ 10 days (the lifetime of planetary-scale structures), there is a drastic transition from high-frequency weather to low-frequency macroweather. This scale is close to the predictability limits of deterministic atmospheric models; thus, in GCM (general circulation model) macroweather forecasts, the weather is a high-frequency noise. However, neither the GCM noise nor the GCM climate is fully realistic. In this paper we show how simple stochastic models can be developed that use empirical data to force the statistics and climate to be realistic so that even a two-parameter model can perform as well as GCMs for annual global temperature forecasts. The key is to exploit the scaling of the dynamics and the large stochastic memories that we quantify. Since macroweather temporal (but not spatial) intermittency is low, we propose using the simplest model based on fractional Gaussian noise (fGn): the ScaLIng Macroweather Model (SLIMM). SLIMM is based on a stochastic ordinary differential equation, differing from usual linear stochastic models (such as the linear inverse modelling - LIM) in that it is of fractional rather than integer order. Whereas LIM implicitly assumes that there is no low-frequency memory, SLIMM has a huge memory that can be exploited. Although the basic mathematical forecast problem for fGn has been solved, we approach the problem in an original manner, notably using the method of innovations to obtain simpler results on forecast skill and on the size of the effective system memory. A key to successful stochastic forecasts of natural macroweather variability is to first remove the low-frequency anthropogenic component. A previous attempt to use fGn for forecasts had disappointing results because this was not done. We validate our theory using hindcasts of global and Northern Hemisphere temperatures at monthly and annual resolutions. Several nondimensional measures of forecast skill - with no adjustable parameters - show excellent
Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education

Science.gov (United States)

Schwalbe, Michelle Kristin

2010-01-01

This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…
Variational Multi-Scale method with spectral approximation of the sub-scales.

KAUST Repository

Dia, Ben Mansour; Chá con-Rebollo, Tomas

2015-01-01

A variational multi-scale method where the sub-grid scales are computed by spectral approximations is presented. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base
Ecohydrological Linkages, Multi-scale Processes, Temporal Variability, and Drivers of Change in a Degraded Pinyon-Juniper Watershed: Implications for Erosion Modeling

Science.gov (United States)

Allen, C. D.

2006-12-01

In 1993 long-term research began on the runoff and erosion dynamics of a pinyon-juniper woodland hillslope at Bandelier National Monument in northern New Mexico (USA). In the 1.09 ha Frijolito watershed, erosion has been continuously studied at 3 spatial scales: 1 square meter, about 1000 square meters, and the entire watershed. This site is currently representative of degraded woodlands of pinyon (Pinus edulis) and one-seed juniper (Juniperus monosperma) in this region, exhibiting marked connectivity of exposed bare soil interspaces between tree canopy patches and obvious geomorphic signs of accelerated soil erosion (e.g., pedestalling, actively expanding rill networks). Ecological and land use histories show that this site has undergone a number of dramatic ecohydrological shifts since ca. C.E. 1850, transitioning from: 1) open ponderosa pine (Pinus ponderosa) overstory with limited pinyon-juniper component and substantial herbaceous understory that supported surface fires and constrained soil erosion, to; 2) ponderosa pine with reduced herbaceous cover due to livestock grazing after ca.1870, resulting in collapse of the surface fire regime and increased establishment of young pinyon and juniper trees, to; 3) mortality of all of the ponderosa pine during the extreme drought of the 1950s, leaving eroding pinyon-juniper woodland, to; 4) mortality of all mature pinyon at or above sapling size during the 2002-2003 drought, with juniper now the only dominant woody species. Detailed measurements since 1993 document high rates of soil erosion (> 2.75 Mg/ha/year on average at the watershed scale) that are rapidly stripping the local soils. Long-term observations are needed to distinguish short-term variability from longer term trends, as measurements of runoff and erosion show extreme variability at multiple time scales since 1993. The multi-scale erosion data from the Frijolito watershed reveal little dropoff in erosion rate (g/meter-squared) between the one meter
Multi-time, multi-scale correlation functions in turbulence and in turbulent models

NARCIS (Netherlands)

Biferale, L.; Boffetta, G.; Celani, A.; Toschi, F.

1999-01-01

A multifractal-like representation for multi-time, multi-scale velocity correlation in turbulence and dynamical turbulent models is proposed. The importance of subleading contributions to time correlations is highlighted. The fulfillment of the dynamical constraints due to the equations of motion is
Reliability of Multi-Category Rating Scales

Science.gov (United States)

Parker, Richard I.; Vannest, Kimberly J.; Davis, John L.

2013-01-01

The use of multi-category scales is increasing for the monitoring of IEP goals, classroom and school rules, and Behavior Improvement Plans (BIPs). Although they require greater inference than traditional data counting, little is known about the inter-rater reliability of these scales. This simulation study examined the performance of nine…
A Decade of High-Resolution Arctic Sea Ice Measurements from Airborne Altimetry

Science.gov (United States)

Duncan, K.; Farrell, S. L.; Connor, L. N.; Jackson, C.; Richter-Menge, J.

2017-12-01

Satellite altimeters carried on board ERS-1,-2, EnviSat, ICESat, CryoSat-2, AltiKa and Sentinel-3 have transformed our ability to map the thickness and volume of the polar sea ice cover, on seasonal and decadal time-scales. The era of polar satellite altimetry has coincided with a rapid decline of the Arctic ice cover, which has thinned, and transitioned from a predominantly multi-year to first-year ice cover. In conjunction with basin-scale satellite altimeter observations, airborne surveys of the Arctic Ocean at the end of winter are now routine. These surveys have been targeted to monitor regions of rapid change, and are designed to obtain the full snow and ice thickness distribution, across a range of ice types. Sensors routinely deployed as part of NASA's Operation IceBridge (OIB) campaigns include the Airborne Topographic Mapper (ATM) laser altimeter, the frequency-modulated continuous-wave snow radar, and the Digital Mapping System (DMS). Airborne measurements yield high-resolution data products and thus present a unique opportunity to assess the quality and characteristics of the satellite observations. We present a suite of sea ice data products that describe the snow depth and thickness of the Arctic ice cover during the last decade. Fields were derived from OIB measurements collected between 2009-2017, and from reprocessed data collected during ad-hoc sea ice campaigns prior to OIB. Our bespoke algorithms are designed to accommodate the heterogeneous sea ice surface topography, that varies at short spatial scales. We assess regional and inter-annual variability in the sea ice thickness distribution. Results are compared to satellite-derived ice thickness fields to highlight the sensitivities of satellite footprints to the tails of the thickness distribution. We also show changes in the dynamic forcing shaping the ice pack over the last eight years through an analysis of pressure-ridge sail-height distributions and surface roughness conditions
A multi scale model for small scale plasticity

International Nuclear Information System (INIS)

Zbib, Hussein M.

2002-01-01

Full text.A framework for investigating size-dependent small-scale plasticity phenomena and related material instabilities at various length scales ranging from the nano-microscale to the mesoscale is presented. The model is based on fundamental physical laws that govern dislocation motion and their interaction with various defects and interfaces. Particularly, a multi-scale model is developed merging two scales, the nano-microscale where plasticity is determined by explicit three-dimensional dislocation dynamics analysis providing the material length-scale, and the continuum scale where energy transport is based on basic continuum mechanics laws. The result is a hybrid simulation model coupling discrete dislocation dynamics with finite element analyses. With this hybrid approach, one can address complex size-dependent problems, including dislocation boundaries, dislocations in heterogeneous structures, dislocation interaction with interfaces and associated shape changes and lattice rotations, as well as deformation in nano-structured materials, localized deformation and shear band
Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts.

Science.gov (United States)

Bellamy, Chloe; Altringham, John

2015-01-01

Conservation increasingly operates at the landscape scale. For this to be effective, we need landscape scale information on species distributions and the environmental factors that underpin them. Species records are becoming increasingly available via data centres and online portals, but they are often patchy and biased. We demonstrate how such data can yield useful habitat suitability models, using bat roost records as an example. We analysed the effects of environmental variables at eight spatial scales (500 m - 6 km) on roost selection by eight bat species (Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula, Myotis mystacinus, M. brandtii, M. nattereri, M. daubentonii, and Plecotus auritus) using the presence-only modelling software MaxEnt. Modelling was carried out on a selection of 418 data centre roost records from the Lake District National Park, UK. Target group pseudoabsences were selected to reduce the impact of sampling bias. Multi-scale models, combining variables measured at their best performing spatial scales, were used to predict roosting habitat suitability, yielding models with useful predictive abilities. Small areas of deciduous woodland consistently increased roosting habitat suitability, but other habitat associations varied between species and scales. Pipistrellus were positively related to built environments at small scales, and depended on large-scale woodland availability. The other, more specialist, species were highly sensitive to human-altered landscapes, avoiding even small rural towns. The strength of many relationships at large scales suggests that bats are sensitive to habitat modifications far from the roost itself. The fine resolution, large extent maps will aid targeted decision-making by conservationists and planners. We have made available an ArcGIS toolbox that automates the production of multi-scale variables, to facilitate the application of our methods to other taxa and locations. Habitat suitability modelling has the
Multi-scale analysis of lung computed tomography images

CERN Document Server

Gori, I; Fantacci, M E; Preite Martinez, A; Retico, A; De Mitri, I; Donadio, S; Fulcheri, C

2007-01-01

A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.
Multi-scale analysis of teleconnection indices: climate noise and nonlinear trend analysis

Directory of Open Access Journals (Sweden)

C. Franzke

2009-02-01

Full Text Available The multi-scale nature and climate noise properties of teleconnection indices are examined by using the Empirical Mode Decomposition (EMD procedure. The EMD procedure allows for the analysis of non-stationary time series to extract physically meaningful intrinsic mode functions (IMF and nonlinear trends. The climatologically relevant monthly mean teleconnection indices of the North Atlantic Oscillation (NAO, the North Pacific index (NP and the Southern Annular Mode (SAM are analyzed.

The significance of IMFs and trends are tested against the null hypothesis of climate noise. The analysis of surrogate monthly mean time series from a red noise process shows that the EMD procedure is effectively a dyadic filter bank and the IMFs (except the first IMF are nearly Gaussian distributed. The distribution of the variance contained in IMFs of an ensemble of AR(1 simulations is nearly χ² distributed. To test the statistical significance of the IMFs of the teleconnection indices and their nonlinear trends we utilize an ensemble of corresponding monthly averaged AR(1 processes, which we refer to as climate noise. Our results indicate that most of the interannual and decadal variability of the analysed teleconnection indices cannot be distinguished from climate noise. The NP and SAM indices have significant nonlinear trends, while the NAO has no significant trend when tested against a climate noise hypothesis.
Iterative equalization for OFDM systems over wideband Multi-Scale Multi-Lag channels

NARCIS (Netherlands)

Xu, T.; Tang, Z.; Remis, R.; Leus, G.

2012-01-01

OFDM suffers from inter-carrier interference (ICI) when the channel is time varying. This article seeks to quantify the amount of interference resulting from wideband OFDM channels, which are assumed to follow the multi-scale multi-lag (MSML) model. The MSML channel model results in full channel

Magnetic hysteresis at the domain scale of a multi-scale material model for magneto-elastic behaviour

Energy Technology Data Exchange (ETDEWEB)

Vanoost, D., E-mail: dries.vanoost@kuleuven-kulak.be [KU Leuven Technology Campus Ostend, ReMI Research Group, Oostende B-8400 (Belgium); KU Leuven Kulak, Wave Propagation and Signal Processing Research Group, Kortrijk B-8500 (Belgium); Steentjes, S. [Institute of Electrical Machines, RWTH Aachen University, Aachen D-52062 (Germany); Peuteman, J. [KU Leuven Technology Campus Ostend, ReMI Research Group, Oostende B-8400 (Belgium); KU Leuven, Department of Electrical Engineering, Electrical Energy and Computer Architecture, Heverlee B-3001 (Belgium); Gielen, G. [KU Leuven, Department of Electrical Engineering, Microelectronics and Sensors, Heverlee B-3001 (Belgium); De Gersem, H. [KU Leuven Kulak, Wave Propagation and Signal Processing Research Group, Kortrijk B-8500 (Belgium); TU Darmstadt, Institut für Theorie Elektromagnetischer Felder, Darmstadt D-64289 (Germany); Pissoort, D. [KU Leuven Technology Campus Ostend, ReMI Research Group, Oostende B-8400 (Belgium); KU Leuven, Department of Electrical Engineering, Microelectronics and Sensors, Heverlee B-3001 (Belgium); Hameyer, K. [Institute of Electrical Machines, RWTH Aachen University, Aachen D-52062 (Germany)

2016-09-15

This paper proposes a multi-scale energy-based material model for poly-crystalline materials. Describing the behaviour of poly-crystalline materials at three spatial scales of dominating physical mechanisms allows accounting for the heterogeneity and multi-axiality of the material behaviour. The three spatial scales are the poly-crystalline, grain and domain scale. Together with appropriate scale transitions rules and models for local magnetic behaviour at each scale, the model is able to describe the magneto-elastic behaviour (magnetostriction and hysteresis) at the macroscale, although the data input is merely based on a set of physical constants. Introducing a new energy density function that describes the demagnetisation field, the anhysteretic multi-scale energy-based material model is extended to the hysteretic case. The hysteresis behaviour is included at the domain scale according to the micro-magnetic domain theory while preserving a valid description for the magneto-elastic coupling. The model is verified using existing measurement data for different mechanical stress levels. - Highlights: • A ferromagnetic hysteretic energy-based multi-scale material model is proposed. • The hysteresis is obtained by new proposed hysteresis energy density function. • Avoids tedious parameter identification.
Results from Navigator GPS Flight Testing for the Magnetospheric MultiScale Mission

Science.gov (United States)

Lulich, Tyler D.; Bamford, William A.; Wintermitz, Luke M. B.; Price, Samuel R.

2012-01-01

The recent delivery of the first Goddard Space Flight Center (GSFC) Navigator Global Positioning System (GPS) receivers to the Magnetospheric MultiScale (MMS) mission spacecraft is a high water mark crowning a decade of research and development in high-altitude space-based GPS. Preceding MMS delivery, the engineering team had developed receivers to support multiple missions and mission studies, such as Low Earth Orbit (LEO) navigation for the Global Precipitation Mission (GPM), above the constellation navigation for the Geostationary Operational Environmental Satellite (GOES) proof-of-concept studies, cis-Lunar navigation with rapid re-acquisition during re-entry for the Orion Project and an orbital demonstration on the Space Shuttle during the Hubble Servicing Mission (HSM-4).
Decadal Variations in Eastern Canada's Taiga Wood Biomass Production Forced by Ocean-Atmosphere Interactions.

Science.gov (United States)

Boucher, Etienne; Nicault, Antoine; Arseneault, Dominique; Bégin, Yves; Karami, Mehdi Pasha

2017-05-26

Across Eastern Canada (EC), taiga forests represent an important carbon reservoir, but the extent to which climate variability affects this ecosystem over decades remains uncertain. Here, we analyze an extensive network of black spruce (Picea mariana Mill.) ring width and wood density measurements and provide new evidence that wood biomass production is influenced by large-scale, internal ocean-atmosphere processes. We show that while black spruce wood biomass production is primarily governed by growing season temperatures, the Atlantic ocean conveys heat from the subtropics and influences the decadal persistence in taiga forests productivity. Indeed, we argue that 20-30 years periodicities in Sea Surface Temperatures (SSTs) as part of the the Atlantic Multi-decadal Oscillation (AMO) directly influence heat transfers to adjacent lands. Winter atmospheric conditions associated with the North Atlantic Oscillation (NAO) might also impact EC's taiga forests, albeit indirectly, through its effect on SSTs and sea ice conditions in surrounding seas. Our work emphasizes that taiga forests would benefit from the combined effects of a warmer atmosphere and stronger ocean-to-land heat transfers, whereas a weakening of these transfers could cancel out, for decades or longer, the positive effects of climate change on Eastern Canada's largest ecosystem.
Exploring Hardware Support For Scaling Irregular Applications on Multi-node Multi-core Architectures

Energy Technology Data Exchange (ETDEWEB)

Secchi, Simone; Ceriani, Marco; Tumeo, Antonino; Villa, Oreste; Palermo, Gianluca; Raffo, Luigi

2013-06-05

With the recent emergence of large-scale knowledge dis- covery, data mining and social network analysis, irregular applications have gained renewed interest. Classic cache-based high-performance architectures do not provide optimal performances with such kind of workloads, mainly due to the very low spatial and temporal locality of the irregular control and memory access patterns. In this paper, we present a multi-node, multi-core, fine-grained multi-threaded shared-memory system architecture specifically designed for the execution of large-scale irregular applications, and built on top of three pillars, that we believe are fundamental to support these workloads. First, we offer transparent hardware support for Partitioned Global Address Space (PGAS) to provide a large globally-shared address space with no software library overhead. Second, we employ multi-threaded multi-core processing nodes to achieve the necessary latency tolerance required by accessing global memory, which potentially resides in a remote node. Finally, we devise hardware support for inter-thread synchronization on the whole global address space. We first model the performances by using an analytical model that takes into account the main architecture and application characteristics. We describe the hardware design of the proposed cus- tom architectural building blocks that provide support for the above- mentioned three pillars. Finally, we present a limited-scale evaluation of the system on a multi-board FPGA prototype with typical irregular kernels and benchmarks. The experimental evaluation demonstrates the architecture performance scalability for different configurations of the whole system.
Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

Science.gov (United States)

Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.

2013-12-01

Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at
Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

Science.gov (United States)

Somogyi, Endre; Sluka, James P; Glazier, James A

2016-10-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.
Multi-scale modeling of composites

DEFF Research Database (Denmark)

Azizi, Reza

A general method to obtain the homogenized response of metal-matrix composites is developed. It is assumed that the microscopic scale is sufficiently small compared to the macroscopic scale such that the macro response does not affect the micromechanical model. Therefore, the microscopic scale......-Mandel’s energy principle is used to find macroscopic operators based on micro-mechanical analyses using the finite element method under generalized plane strain condition. A phenomenologically macroscopic model for metal matrix composites is developed based on constitutive operators describing the elastic...... to plastic deformation. The macroscopic operators found, can be used to model metal matrix composites on the macroscopic scale using a hierarchical multi-scale approach. Finally, decohesion under tension and shear loading is studied using a cohesive law for the interface between matrix and fiber....
Coordinated Multi-layer Multi-domain Optical Network (COMMON) for Large-Scale Science Applications (COMMON)

Energy Technology Data Exchange (ETDEWEB)

Vokkarane, Vinod [University of Massachusetts

2013-09-01

We intend to implement a Coordinated Multi-layer Multi-domain Optical Network (COMMON) Framework for Large-scale Science Applications. In the COMMON project, specific problems to be addressed include 1) anycast/multicast/manycast request provisioning, 2) deployable OSCARS enhancements, 3) multi-layer, multi-domain quality of service (QoS), and 4) multi-layer, multidomain path survivability. In what follows, we outline the progress in the above categories (Year 1, 2, and 3 deliverables).
Coupled numerical approach combining finite volume and lattice Boltzmann methods for multi-scale multi-physicochemical processes

Energy Technology Data Exchange (ETDEWEB)

Chen, Li; He, Ya-Ling [Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Kang, Qinjun [Computational Earth Science Group (EES-16), Los Alamos National Laboratory, Los Alamos, NM (United States); Tao, Wen-Quan, E-mail: wqtao@mail.xjtu.edu.cn [Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China)

2013-12-15

A coupled (hybrid) simulation strategy spatially combining the finite volume method (FVM) and the lattice Boltzmann method (LBM), called CFVLBM, is developed to simulate coupled multi-scale multi-physicochemical processes. In the CFVLBM, computational domain of multi-scale problems is divided into two sub-domains, i.e., an open, free fluid region and a region filled with porous materials. The FVM and LBM are used for these two regions, respectively, with information exchanged at the interface between the two sub-domains. A general reconstruction operator (RO) is proposed to derive the distribution functions in the LBM from the corresponding macro scalar, the governing equation of which obeys the convection–diffusion equation. The CFVLBM and the RO are validated in several typical physicochemical problems and then are applied to simulate complex multi-scale coupled fluid flow, heat transfer, mass transport, and chemical reaction in a wall-coated micro reactor. The maximum ratio of the grid size between the FVM and LBM regions is explored and discussed. -- Highlights: •A coupled simulation strategy for simulating multi-scale phenomena is developed. •Finite volume method and lattice Boltzmann method are coupled. •A reconstruction operator is derived to transfer information at the sub-domains interface. •Coupled multi-scale multiple physicochemical processes in micro reactor are simulated. •Techniques to save computational resources and improve the efficiency are discussed.
Multi-scale magnetic field intermittence in the plasma sheet

Directory of Open Access Journals (Sweden)

Z. Vörös

2003-09-01

Full Text Available This paper demonstrates that intermittent magnetic field fluctuations in the plasma sheet exhibit transitory, localized, and multi-scale features. We propose a multifractal-based algorithm, which quantifies intermittence on the basis of the statistical distribution of the "strength of burstiness", estimated within a sliding window. Interesting multi-scale phenomena observed by the Cluster spacecraft include large-scale motion of the current sheet and bursty bulk flow associated turbulence, interpreted as a cross-scale coupling (CSC process.Key words. Magnetospheric physics (magnetotail; plasma sheet – Space plasma physics (turbulence
Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

Science.gov (United States)

Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

2018-03-06

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.
Simulating multi-scale oceanic processes around Taiwan on unstructured grids

Science.gov (United States)

Yu, Hao-Cheng; Zhang, Yinglong J.; Yu, Jason C. S.; Terng, C.; Sun, Weiling; Ye, Fei; Wang, Harry V.; Wang, Zhengui; Huang, Hai

2017-11-01

We validate a 3D unstructured-grid (UG) model for simulating multi-scale processes as occurred in Northwestern Pacific around Taiwan using recently developed new techniques (Zhang et al., Ocean Modeling, 102, 64-81, 2016) that require no bathymetry smoothing even for this region with prevalent steep bottom slopes and many islands. The focus is on short-term forecast for several months instead of long-term variability. Compared with satellite products, the errors for the simulated Sea-surface Height (SSH) and Sea-surface Temperature (SST) are similar to a reference data-assimilated global model. In the nearshore region, comparison with 34 tide gauges located around Taiwan indicates an average RMSE of 13 cm for the tidal elevation. The average RMSE for SST at 6 coastal buoys is 1.2 °C. The mean transport and eddy kinetic energy compare reasonably with previously published values and the reference model used to provide boundary and initial conditions. The model suggests ∼2-day interruption of Kuroshio east of Taiwan during a typhoon period. The effect of tidal mixing is shown to be significant nearshore. The multi-scale model is easily extendable to target regions of interest due to its UG framework and a flexible vertical gridding system, which is shown to be superior to terrain-following coordinates.
Atmospheric and oceanic excitation of decadal-scale Earth orientation variations

Science.gov (United States)

Gross, Richard S.; Fukumori, Ichiro; Menemenlis, Dimitris

2005-09-01

The contribution of atmospheric wind and surface pressure and oceanic current and bottom pressure variations during 1949-2002 to exciting changes in the Earth's orientation on decadal timescales is investigated using an atmospheric angular momentum series computed from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis project and an oceanic angular momentum series computed from a near-global ocean model that was forced by surface fluxes from the NCEP/NCAR reanalysis project. Not surprisingly, since decadal-scale variations in the length of day are caused mainly by interactions between the mantle and core, the effect of the atmosphere and oceans is found to be only about 14% of that observed. More surprisingly, it is found that the effect of atmospheric and oceanic processes on decadal-scale changes in polar motion is also only about 20% (x component) and 38% (y component) of that observed. Therefore redistribution of mass within the atmosphere and oceans does not appear to be the main cause of the Markowitz wobble. It is also found that on timescales between 10 days and 4 years the atmospheric and oceanic angular momentum series used here have very little skill in explaining Earth orientation variations before the mid to late 1970s. This is attributed to errors in both the Earth orientation observations prior to 1976 when measurements from the accurate space-geodetic techniques became available and to errors in the modeled atmospheric fields prior to 1979 when the satellite era of global weather observing systems began.
Mid-Holocene onset of high-amplitude decadal to centennial scale variability along the Peru Chile Margin

Science.gov (United States)

Chazen, C. R.; Altabet, M.; Herbert, T. D.

2008-12-01

Understanding the natural climate variations in the eastern tropical Pacific is crucial for predicting the evolution of the El Niño-Southern Oscillation (ENSO) system and for anticipating the ways in which increases in atmospheric CO2 will affect climate. Here we present the first continuous, high-resolution (11-12 yr) climate record across the mid-Holocene transition (10ka-1.4ka) from the Peru-Chile Margin near the epicenter of the modern ENSO system. Although the high productivity of the Peru margin should promote high deposition rates, and the anaerobic bottom water conditions should inhibit sediment mixing by benthic organisms, nearly all sediment cores recovered from this region suffer from major gaps in Holocene sedimentation. Our data comes from a ~5 meter piston core collected from the mid-Peruvian shelf (15° 15"S, 75° 58"W, ~250mwd) in the heart of the oxygen minimum/denitrification zone that provides the first uninterrupted archive of conditions along the Peru-Chile margin. A suite of geochemical proxies allow us to reconstruct sea surface temperature (SST- Uk'37), phytoplankton productivity (C37total and %BSi), and thermocline ventilation (δ15N), variables that are tightly correlated to ENSO events today. Despite the observation that the mean late Holocene state of all three variables did not change over the last 10,000 years, our data reveal a dramatic increase in climate variability after the mid Holocene (~5ka); represented by prolonged periods (50-200yrs) of climate extremes, which are absent in the early Holocene. To further investigate these climate extremes we examine benthic foraminiferal assemblages and oxygen isotopes in combination with our other proxy records in selected late Holocene sections. The roughly centennial-scale oscillations do not show typical El Niño-La Niña correlations between proxies. We therefore posit that a significant fraction of super-ENSO variance during the course of the Holocene may originate outside the tropics
Multi-scale modeling of the thermo-mechanical behavior of particle-based composites

International Nuclear Information System (INIS)

Di Paola, F.

2010-01-01

The aim of this work was to perform numerical simulations of the thermal and mechanical behavior of a particle-based nuclear fuel. This is a refractory composite material made of UO 2 spherical particles which are coated with two layers of pyrocarbon and embedded in a graphite matrix at a high volume fraction (45%). The objective was to develop a multi-scale modeling of this composite material which can estimate its mean behavior as well as the heterogeneity of the local mechanical variables. The first part of this work was dedicated to the modeling of the microstructure in 3D. To do this, we developed tools to generate random distributions of spheres, meshes and to characterize the morphology of the microstructure towards the finite element code Cast3M. A hundred of numerical samples of the composite were created. The second part was devoted to the characterization of the thermo-elastic behavior by the finite element modeling of the samples. We studied the influence of different modeling parameters, one of them is the boundary conditions. We proposed a method to vanish the boundary conditions effects from the computed solution by analyzing it on an internal sub-volume of the sample obtained by erosion. Then, we determined the effective properties (elastic moduli, thermal conductivity and thermal expansion) and the stress distribution within the matrix. Finally, in the third part we proposed a multi-scale modeling to determine the mean values and the variance and covariance of the local mechanical variables for any macroscopic load. This statistical approach have been used to estimate the intra-phase distribution of these variables in the composite material. (author) [fr
Multi-scale modeling of the thermo-mechanical behavior of particle-based composites

International Nuclear Information System (INIS)

Di Paola, F.

2010-11-01

The aim of this work was to perform numerical simulations of the thermal and mechanical behavior of a particle-based nuclear fuel. This is a refractory composite material made of UO 2 spherical particles which are coated with two layers of pyrocarbon and embedded in a graphite matrix at a high volume fraction (45 %). The objective was to develop a multi-scale modeling of this composite material which can estimate its mean behavior as well as the heterogeneity of the local mechanical variables. The first part of this work was dedicated to the modeling of the microstructure in 3D. To do this, we developed tools to generate random distributions of spheres, meshes and to characterize the morphology of the microstructure towards the finite element code Cast3M. A hundred of numerical samples of the composite were created. The second part was devoted to the characterization of the thermo-elastic behavior by the finite element modeling of the samples. We studied the influence of different modeling parameters, one of them is the boundary conditions. We proposed a method to vanish the boundary conditions effects from the computed solution by analyzing it on an internal sub-volume of the sample obtained by erosion. Then, we determined the effective properties (elastic moduli, thermal conductivity and thermal expansion) and the stress distribution within the matrix. Finally, in the third part we proposed a multi-scale modeling to determine the mean values and the variance and covariance of the local mechanical variables for any macroscopic load. This statistical approach have been used to estimate the intra-phase distribution of these variables in the composite material. (author)
Optimal Multi-scale Demand-side Management for Continuous Power-Intensive Processes

Science.gov (United States)

Mitra, Sumit

With the advent of deregulation in electricity markets and an increasing share of intermittent power generation sources, the profitability of industrial consumers that operate power-intensive processes has become directly linked to the variability in energy prices. Thus, for industrial consumers that are able to adjust to the fluctuations, time-sensitive electricity prices (as part of so-called Demand-Side Management (DSM) in the smart grid) offer potential economical incentives. In this thesis, we introduce optimization models and decomposition strategies for the multi-scale Demand-Side Management of continuous power-intensive processes. On an operational level, we derive a mode formulation for scheduling under time-sensitive electricity prices. The formulation is applied to air separation plants and cement plants to minimize the operating cost. We also describe how a mode formulation can be used for industrial combined heat and power plants that are co-located at integrated chemical sites to increase operating profit by adjusting their steam and electricity production according to their inherent flexibility. Furthermore, a robust optimization formulation is developed to address the uncertainty in electricity prices by accounting for correlations and multiple ranges in the realization of the random variables. On a strategic level, we introduce a multi-scale model that provides an understanding of the value of flexibility of the current plant configuration and the value of additional flexibility in terms of retrofits for Demand-Side Management under product demand uncertainty. The integration of multiple time scales leads to large-scale two-stage stochastic programming problems, for which we need to apply decomposition strategies in order to obtain a good solution within a reasonable amount of time. Hence, we describe two decomposition schemes that can be applied to solve two-stage stochastic programming problems: First, a hybrid bi-level decomposition scheme with
Multi-scaling of the dense plasma focus

Science.gov (United States)

Saw, S. H.; Lee, S.

2015-03-01

The dense plasma focus is a copious source of multi-radiations with many potential new applications of special interest such as in advanced SXR lithography, materials synthesizing and testing, medical isotopes and imaging. This paper reviews the series of numerical experiments conducted using the Lee model code to obtain the scaling laws of the multi-radiations.
Sub-decadal- to decadal-scale climate cyclicity during the Holsteinian interglacial (MIS 11 evidenced in annually laminated sediments

Directory of Open Access Journals (Sweden)

A. Koutsodendris

2011-09-01

Full Text Available To unravel the short-term climate variability during Marine Isotope Stage (MIS 11, which represents a close analogue to the Holocene with regard to orbital boundary conditions, we performed microfacies and time series analyses on a ~3200-yr-long record of annually laminated Holsteinian lake sediments from Dethlingen, northern Germany. These biogenic varves comprise two sub-layers: a light sub-layer, which is controlled by spring/summer diatom blooms, and a dark sub-layer consisting mainly of amorphous organic matter and fragmented diatom frustules deposited during autumn/winter. Time series analyses were performed on the thickness of the light and dark sub-layers. Signals exceeding the 95% and 99% confidence levels occur at periods that are near-identical to those known from modern instrumental data and Holocene palaeoclimatic records. Spectral peaks at periods of 90, 25, and 10.5 yr are likely associated with the 88-, 22- and 11-yr solar cycles, respectively. This variability is mainly expressed in the light sub-layer spectra, suggesting solar influence on the palaeoproductivity of the lake. Significant signals at periods between 3 and 5 yr and at ∼6 yr are strongest expressed in the dark sub-layer spectra and may reflect an influence of the El Niño-Southern Oscillation (ENSO and the North Atlantic Oscillation (NAO during autumn/winter. Our results suggest that solar forcing and ENSO/NAO-like variability influenced central European climate during MIS 11 similarly to the present interglacial, thus demonstrating the comparability of the two interglacial periods at sub-decadal to decadal timescales.
Water Stress on U.S. Power Production at Decadal Time Horizons

Energy Technology Data Exchange (ETDEWEB)

Ganguly, Auroop R. [Northeastern Univ., Boston, MA (United States). Sustainability and Data Sciences Lab.. Civil and Environmental Engineering Dept.; Ganguli, Poulomi [Northeastern Univ., Boston, MA (United States). Sustainability and Data Sciences Lab.; Kumar, Devashish [Northeastern Univ., Boston, MA (United States). Sustainability and Data Sciences Lab.

2014-09-01

Thermoelectric power production at risk, owing to current and projected water scarcity and rising stream temperatures, is assessed for the contiguous United States at decadal scales. Regional water scarcity is driven by climate variability and change, as well as by multi-sector water demand. While a planning horizon of zero to about thirty years is occasionally prescribed by stakeholders, the challenges to risk assessment at these scales include the difficulty in delineating decadal climate trends from intrinsic natural or multiple model variability. Current generation global climate or earth system models are not credible at the spatial resolutions of power plants, especially for surface water quantity and stream temperatures, which further exacerbates the assessment challenge. Population changes, which are difficult to project, cannot serve as adequate proxies for changes in the water demand across sectors. The hypothesis that robust assessments of power production at risk are possible, despite the uncertainties, has been examined as a proof of concept. An approach is presented for delineating water scarcity and temperature from climate models, observations and population storylines, as well as for assessing power production at risk by examining geospatial correlations of power plant locations within regions where the usable water supply for energy production happens to be scarcer and warmer. Our analyses showed that in the near term, more than 200 counties are likely to be exposed to water scarcity in the next three decades. Further, we noticed that stream gauges in more than five counties in the 2030s and ten counties in the 2040s showed a significant increase in water temperature, which exceeded the power plant effluent temperature threshold set by the EPA. Power plants in South Carolina, Louisiana, and Texas are likely to be vulnerable owing to climate driven water stresses. In all, our analysis suggests that under various combinations of plausible climate

Winter Arctic sea ice growth: current variability and projections for the coming decades

Science.gov (United States)

Petty, A.; Boisvert, L.; Webster, M.; Holland, M. M.; Bailey, D. A.; Kurtz, N. T.; Markus, T.

2017-12-01

Arctic sea ice increases in both extent and thickness during the cold winter months ( October to May). Winter sea ice growth is an important factor controlling ocean ventilation and winter water/deep water formation, as well as determining the state and vulnerability of the sea ice pack before the melt season begins. Key questions for the Arctic community thus include: (i) what is the current magnitude and variability of winter Arctic sea ice growth and (ii) how might this change in a warming Arctic climate? To address (i), our current best guess of pan-Arctic sea ice thickness, and thus volume, comes from satellite altimetry observations, e.g. from ESA's CryoSat-2 satellite. A significant source of uncertainty in these data come from poor knowledge of the overlying snow depth. Here we present new estimates of winter sea ice thickness from CryoSat-2 using snow depths from a simple snow model forced by reanalyses and satellite-derived ice drift estimates, combined with snow depth estimates from NASA's Operation IceBridge. To address (ii), we use data from the Community Earth System Model's Large Ensemble Project, to explore sea ice volume and growth variability, and how this variability might change over the coming decades. We compare and contrast the model simulations to observations and the PIOMAS ice-ocean model (over recent years/decades). The combination of model and observational analysis provide novel insight into Arctic sea ice volume variability.
A scale-entropy diffusion equation to describe the multi-scale features of turbulent flames near a wall

Science.gov (United States)

Queiros-Conde, D.; Foucher, F.; Mounaïm-Rousselle, C.; Kassem, H.; Feidt, M.

2008-12-01

Multi-scale features of turbulent flames near a wall display two kinds of scale-dependent fractal features. In scale-space, an unique fractal dimension cannot be defined and the fractal dimension of the front is scale-dependent. Moreover, when the front approaches the wall, this dependency changes: fractal dimension also depends on the wall-distance. Our aim here is to propose a general geometrical framework that provides the possibility to integrate these two cases, in order to describe the multi-scale structure of turbulent flames interacting with a wall. Based on the scale-entropy quantity, which is simply linked to the roughness of the front, we thus introduce a general scale-entropy diffusion equation. We define the notion of “scale-evolutivity” which characterises the deviation of a multi-scale system from the pure fractal behaviour. The specific case of a constant “scale-evolutivity” over the scale-range is studied. In this case, called “parabolic scaling”, the fractal dimension is a linear function of the logarithm of scale. The case of a constant scale-evolutivity in the wall-distance space implies that the fractal dimension depends linearly on the logarithm of the wall-distance. We then verified experimentally, that parabolic scaling represents a good approximation of the real multi-scale features of turbulent flames near a wall.
Screening wells by multi-scale grids for multi-stage Markov Chain Monte Carlo simulation

DEFF Research Database (Denmark)

Akbari, Hani; Engsig-Karup, Allan Peter

2018-01-01

/production wells, aiming at accurate breakthrough capturing as well as above mentioned efficiency goals. However this short time simulation needs fine-scale structure of the geological model around wells and running a fine-scale model is not as cheap as necessary for screening steps. On the other hand applying...... it on a coarse-scale model declines important data around wells and causes inaccurate results, particularly accurate breakthrough capturing which is important for prediction applications. Therefore we propose a multi-scale grid which preserves the fine-scale model around wells (as well as high permeable regions...... and fractures) and coarsens rest of the field and keeps efficiency and accuracy for the screening well stage and coarse-scale simulation, as well. A discrete wavelet transform is used as a powerful tool to generate the desired unstructured multi-scale grid efficiently. Finally an accepted proposal on coarse...
Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection

KAUST Repository

Bai, Yancheng

2018-01-28

Activity detection is a fundamental problem in computer vision. Detecting activities of different temporal scales is particularly challenging. In this paper, we propose the contextual multi-scale region convolutional 3D network (CMS-RC3D) for activity detection. To deal with the inherent temporal scale variability of activity instances, the temporal feature pyramid is used to represent activities of different temporal scales. On each level of the temporal feature pyramid, an activity proposal detector and an activity classifier are learned to detect activities of specific temporal scales. Temporal contextual information is fused into activity classifiers for better recognition. More importantly, the entire model at all levels can be trained end-to-end. Our CMS-RC3D detector can deal with activities at all temporal scale ranges with only a single pass through the backbone network. We test our detector on two public activity detection benchmarks, THUMOS14 and ActivityNet. Extensive experiments show that the proposed CMS-RC3D detector outperforms state-of-the-art methods on THUMOS14 by a substantial margin and achieves comparable results on ActivityNet despite using a shallow feature extractor.
Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection

KAUST Repository

Bai, Yancheng; Xu, Huijuan; Saenko, Kate; Ghanem, Bernard

2018-01-01

Activity detection is a fundamental problem in computer vision. Detecting activities of different temporal scales is particularly challenging. In this paper, we propose the contextual multi-scale region convolutional 3D network (CMS-RC3D) for activity detection. To deal with the inherent temporal scale variability of activity instances, the temporal feature pyramid is used to represent activities of different temporal scales. On each level of the temporal feature pyramid, an activity proposal detector and an activity classifier are learned to detect activities of specific temporal scales. Temporal contextual information is fused into activity classifiers for better recognition. More importantly, the entire model at all levels can be trained end-to-end. Our CMS-RC3D detector can deal with activities at all temporal scale ranges with only a single pass through the backbone network. We test our detector on two public activity detection benchmarks, THUMOS14 and ActivityNet. Extensive experiments show that the proposed CMS-RC3D detector outperforms state-of-the-art methods on THUMOS14 by a substantial margin and achieves comparable results on ActivityNet despite using a shallow feature extractor.
Implementation of Grid-computing Framework for Simulation in Multi-scale Structural Analysis

Directory of Open Access Journals (Sweden)

Data Iranata

2010-05-01

Full Text Available A new grid-computing framework for simulation in multi-scale structural analysis is presented. Two levels of parallel processing will be involved in this framework: multiple local distributed computing environments connected by local network to form a grid-based cluster-to-cluster distributed computing environment. To successfully perform the simulation, a large-scale structural system task is decomposed into the simulations of a simplified global model and several detailed component models using various scales. These correlated multi-scale structural system tasks are distributed among clusters and connected together in a multi-level hierarchy and then coordinated over the internet. The software framework for supporting the multi-scale structural simulation approach is also presented. The program architecture design allows the integration of several multi-scale models as clients and servers under a single platform. To check its feasibility, a prototype software system has been designed and implemented to perform the proposed concept. The simulation results show that the software framework can increase the speedup performance of the structural analysis. Based on this result, the proposed grid-computing framework is suitable to perform the simulation of the multi-scale structural analysis.
ENSO related decadal scale climate variability from the Indo-Pacific Warm Pool

NARCIS (Netherlands)

Brijker, J.M.; Jung, S.J.A.; Ganssen, G.M.; Bickert, T.; Kroon, D.

2006-01-01

The El Niño-Southern Oscillation (ENSO) is a climatic phenomenon that affects socio-economical welfare in vast areas in the world. A continuous record of Holocene ENSO related climate variability of the Indo-Pacific Warm pool (IPWP) is constructed on the basis of stable oxygen isotopes in shells of
Quantifying variability in earthquake rupture models using multidimensional scaling: application to the 2011 Tohoku earthquake

KAUST Repository

Razafindrakoto, Hoby

2015-04-22

Finite-fault earthquake source inversion is an ill-posed inverse problem leading to non-unique solutions. In addition, various fault parametrizations and input data may have been used by different researchers for the same earthquake. Such variability leads to large intra-event variability in the inferred rupture models. One way to understand this problem is to develop robust metrics to quantify model variability. We propose a Multi Dimensional Scaling (MDS) approach to compare rupture models quantitatively. We consider normalized squared and grey-scale metrics that reflect the variability in the location, intensity and geometry of the source parameters. We test the approach on two-dimensional random fields generated using a von Kármán autocorrelation function and varying its spectral parameters. The spread of points in the MDS solution indicates different levels of model variability. We observe that the normalized squared metric is insensitive to variability of spectral parameters, whereas the grey-scale metric is sensitive to small-scale changes in geometry. From this benchmark, we formulate a similarity scale to rank the rupture models. As case studies, we examine inverted models from the Source Inversion Validation (SIV) exercise and published models of the 2011 Mw 9.0 Tohoku earthquake, allowing us to test our approach for a case with a known reference model and one with an unknown true solution. The normalized squared and grey-scale metrics are respectively sensitive to the overall intensity and the extension of the three classes of slip (very large, large, and low). Additionally, we observe that a three-dimensional MDS configuration is preferable for models with large variability. We also find that the models for the Tohoku earthquake derived from tsunami data and their corresponding predictions cluster with a systematic deviation from other models. We demonstrate the stability of the MDS point-cloud using a number of realizations and jackknife tests, for
Quantifying variability in earthquake rupture models using multidimensional scaling: application to the 2011 Tohoku earthquake

KAUST Repository

Razafindrakoto, Hoby; Mai, Paul Martin; Genton, Marc G.; Zhang, Ling; Thingbaijam, Kiran Kumar

2015-01-01

Finite-fault earthquake source inversion is an ill-posed inverse problem leading to non-unique solutions. In addition, various fault parametrizations and input data may have been used by different researchers for the same earthquake. Such variability leads to large intra-event variability in the inferred rupture models. One way to understand this problem is to develop robust metrics to quantify model variability. We propose a Multi Dimensional Scaling (MDS) approach to compare rupture models quantitatively. We consider normalized squared and grey-scale metrics that reflect the variability in the location, intensity and geometry of the source parameters. We test the approach on two-dimensional random fields generated using a von Kármán autocorrelation function and varying its spectral parameters. The spread of points in the MDS solution indicates different levels of model variability. We observe that the normalized squared metric is insensitive to variability of spectral parameters, whereas the grey-scale metric is sensitive to small-scale changes in geometry. From this benchmark, we formulate a similarity scale to rank the rupture models. As case studies, we examine inverted models from the Source Inversion Validation (SIV) exercise and published models of the 2011 Mw 9.0 Tohoku earthquake, allowing us to test our approach for a case with a known reference model and one with an unknown true solution. The normalized squared and grey-scale metrics are respectively sensitive to the overall intensity and the extension of the three classes of slip (very large, large, and low). Additionally, we observe that a three-dimensional MDS configuration is preferable for models with large variability. We also find that the models for the Tohoku earthquake derived from tsunami data and their corresponding predictions cluster with a systematic deviation from other models. We demonstrate the stability of the MDS point-cloud using a number of realizations and jackknife tests, for
Closing the sea level budget on a regional scale: Trends and variability on the Northwestern European continental shelf.

Science.gov (United States)

Frederikse, Thomas; Riva, Riccardo; Kleinherenbrink, Marcel; Wada, Yoshihide; van den Broeke, Michiel; Marzeion, Ben

2016-10-28

Long-term trends and decadal variability of sea level in the North Sea and along the Norwegian coast have been studied over the period 1958-2014. We model the spatially nonuniform sea level and solid earth response to large-scale ice melt and terrestrial water storage changes. GPS observations, corrected for the solid earth deformation, are used to estimate vertical land motion. We find a clear correlation between sea level in the North Sea and along the Norwegian coast and open ocean steric variability in the Bay of Biscay and west of Portugal, which is consistent with the presence of wind-driven coastally trapped waves. The observed nodal cycle is consistent with tidal equilibrium. We are able to explain the observed sea level trend over the period 1958-2014 well within the standard error of the sum of all contributing processes, as well as the large majority of the observed decadal sea level variability.
Modeling Climate Responses to Spectral Solar Forcing on Centennial and Decadal Time Scales

Science.gov (United States)

Wen, G.; Cahalan, R.; Rind, D.; Jonas, J.; Pilewskie, P.; Harder, J.

2012-01-01

We report a series of experiments to explore clima responses to two types of solar spectral forcing on decadal and centennial time scales - one based on prior reconstructions, and another implied by recent observations from the SORCE (Solar Radiation and Climate Experiment) SIM (Spectral 1rradiance Monitor). We apply these forcings to the Goddard Institute for Space Studies (GISS) Global/Middle Atmosphere Model (GCMAM). that couples atmosphere with ocean, and has a model top near the mesopause, allowing us to examine the full response to the two solar forcing scenarios. We show different climate responses to the two solar forCing scenarios on decadal time scales and also trends on centennial time scales. Differences between solar maximum and solar minimum conditions are highlighted, including impacts of the time lagged reSponse of the lower atmosphere and ocean. This contrasts with studies that assume separate equilibrium conditions at solar maximum and minimum. We discuss model feedback mechanisms involved in the solar forced climate variations.
Multi scale analysis of ITER pre-compression rings

Energy Technology Data Exchange (ETDEWEB)

Park, Ben, E-mail: ben.park@sener.es [SENER Ingeniería y Sistemas S.A., Barcelona (Spain); Foussat, Arnaud [ITER Organization, St. Paul-Lez-Durance (France); Rajainmaki, Hannu [Fusion for Energy, Barcelona (Spain); Knaster, Juan [IFMIF, Aomori (Japan)

2013-10-15

Highlights: • A multi-scale analysis approach employing various scales of ABAQUS FEM models have been used to calculate the response and performance of the rings. • We have studied the effects of various defects on the performance of the rings under the operating temperatures and loading that will be applied to the PCRs. • The multi scale analysis results are presented here. -- Abstract: The Pre-compression Rings of ITER (PCRs) represent one of the largest and most highly stressed composite structures ever designed for long term operation at 4 K. Six rings, each 5 m in diameter and 337 mm × 288 mm in cross-section, will be manufactured from S2 fiber-glass/epoxy composite and installed three at the top and three at the bottom of the eighteen D shaped toroidal field (TF) coils to apply a total centripetal pre-load of 70 MN per TF coil. The composite rings will be fabricated with a high content (65% by volume) of S2 fiber-glass in an epoxy resin matrix. During the manufacture emphasis will be placed on obtaining a structure with a very low void content and minimal presence of critical defects, such as delaminations. This paper presents a unified framework for the multi-scale analysis of the composite structure of the PCRs. A multi-scale analysis approach employing various scales of ABAQUS FEM models and other analysis tools have been used to calculate the response and performance of the rings over the design life of the structure. We have studied the effects of various defects on the performance of the rings under the operating temperatures and loading that will be applied to the PCRs. The results are presented here.
Changes in intense tropical cyclone activity for the western North Pacific during the last decades derived from a regional climate model simulation

Science.gov (United States)

Barcikowska, Monika; Feser, Frauke; Zhang, Wei; Mei, Wei

2017-11-01

An atmospheric regional climate model (CCLM) was employed to dynamically downscale atmospheric reanalyses (NCEP/NCAR 1, ERA 40) over the western North Pacific and South East Asia. This approach is used for the first time to reconstruct a tropical cyclone climatology, which extends beyond the satellite era and serves as an alternative data set for inhomogeneous observation-derived records (Best Track Data sets). The simulated TC climatology skillfully reproduces observations of the recent decades (1978-2010), including spatial patterns, frequency, lifetime, trends, variability on interannual and decadal time scales and their association with the large-scale circulation patterns. These skills, facilitated here with the spectral nudging method, seem to be a prerequisite to understand the factors determining spatio-temporal variability of TC activity over the western North Pacific. Long-term trends (1948-2011 and 1959-2001) in both simulations show a strong increase of intense tropical cyclone activity. This contrasts with pronounced multidecadal variations found in observations. The discrepancy may partly originate from temporal inhomogeneities in atmospheric reanalyses and Best Track Data, which affect both the model-based and observational-based trends. An adjustment, which removes the simulated upward trend, reduces the apparent discrepancy. Ultimately, our observational and modeling analysis suggests an important contribution of multi-decadal fluctuations in the TC activity during the last six decades. Nevertheless, due to the uncertainties associated with the inconsistencies and quality changes of those data sets, we call for special caution when reconstructing long-term TC statistics either from atmospheric reanalyses or Best Track Data.
A multi-scale investigation of the mechanical behavior of durable sisal fiber cement composites

OpenAIRE

Silva, Flávio de Andrade; Toledo Filho, Romildo D.; Mobasher, Barzin; Chawla, Nikhilesh

2010-01-01

Durable sisal fiber cement composites reinforced with long unidirectional aligned fibers were developed and their mechanical behavior was characterized in a multi-scale level. Tensile tests were performed in individual sisal fibers. Weibull statistics were used to quantify the degree of variability in fiber strength at different gage lengths. The fiber-matrix pull-out behavior was evaluated at several curing ages and embedded lengths. The composite's mechanical response was measured under dir...
Multi codes and multi-scale analysis for void fraction prediction in hot channel for VVER-1000/V392

International Nuclear Information System (INIS)

Hoang Minh Giang; Hoang Tan Hung; Nguyen Huu Tiep

2015-01-01

Recently, an approach of multi codes and multi-scale analysis is widely applied to study core thermal hydraulic behavior such as void fraction prediction. Better results are achieved by using multi codes or coupling codes such as PARCS and RELAP5. The advantage of multi-scale analysis is zooming of the interested part in the simulated domain for detail investigation. Therefore, in this study, the multi codes between MCNP5, RELAP5, CTF and also the multi-scale analysis based RELAP5 and CTF are applied to investigate void fraction in hot channel of VVER-1000/V392 reactor. Since VVER-1000/V392 reactor is a typical advanced reactor that can be considered as the base to develop later VVER-1200 reactor, then understanding core behavior in transient conditions is necessary in order to investigate VVER technology. It is shown that the item of near wall boiling, Γ w in RELAP5 proposed by Lahey mechanistic method may not give enough accuracy of void fraction prediction as smaller scale code as CTF. (author)
A REGION-BASED MULTI-SCALE APPROACH FOR OBJECT-BASED IMAGE ANALYSIS

Directory of Open Access Journals (Sweden)

T. Kavzoglu

2016-06-01

Full Text Available Within the last two decades, object-based image analysis (OBIA considering objects (i.e. groups of pixels instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient. Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.
Decadal-to-centennial-scale climate variability: Insights into the rise and fall of the Great Salt Lake

Science.gov (United States)

Mann, Michael E.; Lall, Upmanu; Saltzman, Barry

1995-01-01

We demonstrate connections between decadal and secular global climatic variations, and historical variations in the volume of the Great Salt Lake. The decadal variations correspond to a low-frequency shifting of storm tracks which influence winter precipitation and explain nearly 18% of the interannual and longer-term variance in the record of monthly volume change. The secular trend accounts for a more modest approximately 1.5% of the variance.
Multi-scale graph-cut algorithm for efficient water-fat separation.

Science.gov (United States)

Berglund, Johan; Skorpil, Mikael

2017-09-01

To improve the accuracy and robustness to noise in water-fat separation by unifying the multiscale and graph cut based approaches to B 0 -correction. A previously proposed water-fat separation algorithm that corrects for B 0 field inhomogeneity in 3D by a single quadratic pseudo-Boolean optimization (QPBO) graph cut was incorporated into a multi-scale framework, where field map solutions are propagated from coarse to fine scales for voxels that are not resolved by the graph cut. The accuracy of the single-scale and multi-scale QPBO algorithms was evaluated against benchmark reference datasets. The robustness to noise was evaluated by adding noise to the input data prior to water-fat separation. Both algorithms achieved the highest accuracy when compared with seven previously published methods, while computation times were acceptable for implementation in clinical routine. The multi-scale algorithm was more robust to noise than the single-scale algorithm, while causing only a small increase (+10%) of the reconstruction time. The proposed 3D multi-scale QPBO algorithm offers accurate water-fat separation, robustness to noise, and fast reconstruction. The software implementation is freely available to the research community. Magn Reson Med 78:941-949, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
MUSIC: MUlti-Scale Initial Conditions

Science.gov (United States)

Hahn, Oliver; Abel, Tom

2013-11-01

MUSIC generates multi-scale initial conditions with multiple levels of refinements for cosmological ‘zoom-in’ simulations. The code uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). MUSIC achieves rms relative errors of the order of 10-4 for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier space-induced interference ringing.
Multi-scale modeling for sustainable chemical production.

Science.gov (United States)

Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J

2013-09-01

With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Distributed parallel cooperative coevolutionary multi-objective large-scale immune algorithm for deployment of wireless sensor networks

DEFF Research Database (Denmark)

Cao, Bin; Zhao, Jianwei; Yang, Po

2018-01-01

-objective evolutionary algorithms the Cooperative Coevolutionary Generalized Differential Evolution 3, the Cooperative Multi-objective Differential Evolution and the Nondominated Sorting Genetic Algorithm III, the proposed algorithm addresses the deployment optimization problem efficiently and effectively.......Using immune algorithms is generally a time-intensive process especially for problems with a large number of variables. In this paper, we propose a distributed parallel cooperative coevolutionary multi-objective large-scale immune algorithm that is implemented using the message passing interface...... (MPI). The proposed algorithm is composed of three layers: objective, group and individual layers. First, for each objective in the multi-objective problem to be addressed, a subpopulation is used for optimization, and an archive population is used to optimize all the objectives. Second, the large...
Deep multi-scale convolutional neural network for hyperspectral image classification

Science.gov (United States)

Zhang, Feng-zhe; Yang, Xia

2018-04-01

In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.
Why are models unable to reproduce multi-decadal trends in lower tropospheric baseline ozone levels?

Science.gov (United States)

Hu, L.; Liu, J.; Mickley, L. J.; Strahan, S. E.; Steenrod, S.

2017-12-01

Assessments of tropospheric ozone radiative forcing rely on accurate model simulations. Parrish et al (2014) found that three chemistry-climate models (CCMs) overestimate present-day O3 mixing ratios and capture only 50% of the observed O3 increase over the last five decades at 12 baseline sites in the northern mid-latitudes, indicating large uncertainties in our understanding of the ozone trends and their implications for radiative forcing. Here we present comparisons of outputs from two chemical transport models (CTMs) - GEOS-Chem and the Global Modeling Initiative model - with O3 observations from the same sites and from the global ozonesonde network. Both CTMs are driven by reanalysis meteorological data (MERRA or MERRA2) and thus are expected to be different in atmospheric transport processes relative to those freely running CCMs. We test whether recent model developments leading to more active ozone chemistry affect the computed ozone sensitivity to perturbations in emissions. Preliminary results suggest these CTMs can reproduce present-day ozone levels but fail to capture the multi-decadal trend since 1980. Both models yield widespread overpredictions of free tropospheric ozone in the 1980s. Sensitivity studies in GEOS-Chem suggest that the model estimate of natural background ozone is too high. We discuss factors that contribute to the variability and trends of tropospheric ozone over the last 30 years, with a focus on intermodel differences in spatial resolution and in the representation of stratospheric chemistry, stratosphere-troposphere exchange, halogen chemistry, and biogenic VOC emissions and chemistry. We also discuss uncertainty in the historical emission inventories used in models, and how these affect the simulated ozone trends.
Superhydrophobic multi-scale ZnO nanostructures fabricated by chemical vapor deposition method.

Science.gov (United States)

Zhou, Ming; Feng, Chengheng; Wu, Chunxia; Ma, Weiwei; Cai, Lan

2009-07-01

The ZnO nanostructures were synthesized on Si(100) substrates by chemical vapor deposition (CVD) method. Different Morphologies of ZnO nanostructures, such as nanoparticle film, micro-pillar and micro-nano multi-structure, were obtained with different conditions. The results of XRD and TEM showed the good quality of ZnO crystal growth. Selected area electron diffraction analysis indicates the individual nano-wire is single crystal. The wettability of ZnO was studied by contact angle admeasuring apparatus. We found that the wettability can be changed from hydrophobic to super-hydrophobic when the structure changed from smooth particle film to single micro-pillar, nano-wire and micro-nano multi-scale structure. Compared with the particle film with contact angle (CA) of 90.7 degrees, the CA of single scale microstructure and sparse micro-nano multi-scale structure is 130-140 degrees, 140-150 degrees respectively. But when the surface is dense micro-nano multi-scale structure such as nano-lawn, the CA can reach to 168.2 degrees . The results indicate that microstructure of surface is very important to the surface wettability. The wettability on the micro-nano multi-structure is better than single-scale structure, and that of dense micro-nano multi-structure is better than sparse multi-structure.
Spatially Extensive Standardized Surveys Reveal Widespread, Multi-Decadal Increase in East Antarctic Adélie Penguin Populations.

Science.gov (United States)

Southwell, Colin; Emmerson, Louise; McKinlay, John; Newbery, Kym; Takahashi, Akinori; Kato, Akiko; Barbraud, Christophe; DeLord, Karine; Weimerskirch, Henri

2015-01-01

Seabirds are considered to be useful and practical indicators of the state of marine ecosystems because they integrate across changes in the lower trophic levels and the physical environment. Signals from this key group of species can indicate broad scale impacts or response to environmental change. Recent studies of penguin populations, the most commonly abundant Antarctic seabirds in the west Antarctic Peninsula and western Ross Sea, have demonstrated that physical changes in Antarctic marine environments have profound effects on biota at high trophic levels. Large populations of the circumpolar-breeding Adélie penguin occur in East Antarctica, but direct, standardized population data across much of this vast coastline have been more limited than in other Antarctic regions. We combine extensive new population survey data, new population estimation methods, and re-interpreted historical survey data to assess decadal-scale change in East Antarctic Adélie penguin breeding populations. We show that, in contrast to the west Antarctic Peninsula and western Ross Sea where breeding populations have decreased or shown variable trends over the last 30 years, East Antarctic regional populations have almost doubled in abundance since the 1980's and have been increasing since the earliest counts in the 1960's. The population changes are associated with five-year lagged changes in the physical environment, suggesting that the changing environment impacts primarily on the pre-breeding age classes. East Antarctic marine ecosystems have been subject to a number of changes over the last 50 years which may have influenced Adélie penguin population growth, including decadal-scale climate variation, an inferred mid-20th century sea-ice contraction, and early-to-mid 20th century exploitation of fish and whale populations.
Spatially Extensive Standardized Surveys Reveal Widespread, Multi-Decadal Increase in East Antarctic Adélie Penguin Populations.

Directory of Open Access Journals (Sweden)

Colin Southwell

Full Text Available Seabirds are considered to be useful and practical indicators of the state of marine ecosystems because they integrate across changes in the lower trophic levels and the physical environment. Signals from this key group of species can indicate broad scale impacts or response to environmental change. Recent studies of penguin populations, the most commonly abundant Antarctic seabirds in the west Antarctic Peninsula and western Ross Sea, have demonstrated that physical changes in Antarctic marine environments have profound effects on biota at high trophic levels. Large populations of the circumpolar-breeding Adélie penguin occur in East Antarctica, but direct, standardized population data across much of this vast coastline have been more limited than in other Antarctic regions. We combine extensive new population survey data, new population estimation methods, and re-interpreted historical survey data to assess decadal-scale change in East Antarctic Adélie penguin breeding populations. We show that, in contrast to the west Antarctic Peninsula and western Ross Sea where breeding populations have decreased or shown variable trends over the last 30 years, East Antarctic regional populations have almost doubled in abundance since the 1980's and have been increasing since the earliest counts in the 1960's. The population changes are associated with five-year lagged changes in the physical environment, suggesting that the changing environment impacts primarily on the pre-breeding age classes. East Antarctic marine ecosystems have been subject to a number of changes over the last 50 years which may have influenced Adélie penguin population growth, including decadal-scale climate variation, an inferred mid-20th century sea-ice contraction, and early-to-mid 20th century exploitation of fish and whale populations.
Bi-decadal variability excited in the coupled ocean-atmosphere system by strong tropical volcanic eruptions

Energy Technology Data Exchange (ETDEWEB)

Zanchettin, D.; Lorenz, S.; Lohmann, K.; Jungclaus, J.H. [Max Planck Institute for Meteorology, Ocean in the Earth System Department, Hamburg (Germany); Timmreck, C. [Max Planck Institute for Meteorology, Atmosphere in the Earth System Department, Hamburg (Germany); Graf, H.-F. [University of Cambridge, Centre for Atmospheric Science, Cambridge (United Kingdom); Rubino, A. [Ca' Foscari University, Department of Environmental Sciences, Venice (Italy); Krueger, K. [Leibniz-Institute of Marine Sciences, IFM-GEOMAR, Kiel (Germany)

2012-07-15

Decadal and bi-decadal climate responses to tropical strong volcanic eruptions (SVEs) are inspected in an ensemble simulation covering the last millennium based on the Max Planck Institute - Earth system model. An unprecedentedly large collection of pre-industrial SVEs (up to 45) producing a peak annual-average top-of-atmosphere radiative perturbation larger than -1.5 Wm{sup -2} is investigated by composite analysis. Post-eruption oceanic and atmospheric anomalies coherently describe a fluctuation in the coupled ocean-atmosphere system with an average length of 20-25 years. The study provides a new physically consistent theoretical framework to interpret decadal Northern Hemisphere (NH) regional winter climates variability during the last millennium. The fluctuation particularly involves interactions between the Atlantic meridional overturning circulation and the North Atlantic gyre circulation closely linked to the state of the winter North Atlantic Oscillation. It is characterized by major distinctive details. Among them, the most prominent are: (a) a strong signal amplification in the Arctic region which allows for a sustained strengthened teleconnection between the North Pacific and the North Atlantic during the first post-eruption decade and which entails important implications from oceanic heat transport and from post-eruption sea ice dynamics, and (b) an anomalous surface winter warming emerging over the Scandinavian/Western Russian region around 10-12 years after a major eruption. The simulated long-term climate response to SVEs depends, to some extent, on background conditions. Consequently, ensemble simulations spanning different phases of background multidecadal and longer climate variability are necessary to constrain the range of possible post-eruption decadal evolution of NH regional winter climates. (orig.)
Patterns and multi-scale drivers of phytoplankton species richness in temperate peri-urban lakes

International Nuclear Information System (INIS)

Catherine, Arnaud; Selma, Maloufi; Mouillot, David; Troussellier, Marc; Bernard, Cécile

2016-01-01

Local species richness (SR) is a key characteristic affecting ecosystem functioning. Yet, the mechanisms regulating phytoplankton diversity in freshwater ecosystems are not fully understood, especially in peri-urban environments where anthropogenic pressures strongly impact the quality of aquatic ecosystems. To address this issue, we sampled the phytoplankton communities of 50 lakes in the Paris area (France) characterized by a large gradient of physico-chemical and catchment-scale characteristics. We used large phytoplankton datasets to describe phytoplankton diversity patterns and applied a machine-learning algorithm to test the degree to which species richness patterns are potentially controlled by environmental factors. Selected environmental factors were studied at two scales: the lake-scale (e.g. nutrients concentrations, water temperature, lake depth) and the catchment-scale (e.g. catchment, landscape and climate variables). Then, we used a variance partitioning approach to evaluate the interaction between lake-scale and catchment-scale variables in explaining local species richness. Finally, we analysed the residuals of predictive models to identify potential vectors of improvement of phytoplankton species richness predictive models. Lake-scale and catchment-scale drivers provided similar predictive accuracy of local species richness (R"2 = 0.458 and 0.424, respectively). Both models suggested that seasonal temperature variations and nutrient supply strongly modulate local species richness. Integrating lake- and catchment-scale predictors in a single predictive model did not provide increased predictive accuracy; therefore suggesting that the catchment-scale model probably explains observed species richness variations through the impact of catchment-scale variables on in-lake water quality characteristics. Models based on catchment characteristics, which include simple and easy to obtain variables, provide a meaningful way of predicting phytoplankton
Patterns and multi-scale drivers of phytoplankton species richness in temperate peri-urban lakes

Energy Technology Data Exchange (ETDEWEB)

Catherine, Arnaud, E-mail: arnocat@mnhn.fr [UMR7245 MCAM MNHN-CNRS, Muséum National d' Histoire Naturelle, CC 39, 12 rue Buffon, F-75231 Paris, Cedex 05 (France); Selma, Maloufi, E-mail: maloufi@mnhn.fr [UMR7245 MCAM MNHN-CNRS, Muséum National d' Histoire Naturelle, CC 39, 12 rue Buffon, F-75231 Paris, Cedex 05 (France); Mouillot, David, E-mail: david.mouillot@univ-montp2.fr [UMR 9190 MARBEC UM2-CNRS-IRD-UM1-IFREMER, CC 93, Place Eugène Bataillon, Université de Montpellier 2, F-34095 Montpellier (France); Troussellier, Marc, E-mail: troussel@univ-montp2.fr [UMR 9190 MARBEC UM2-CNRS-IRD-UM1-IFREMER, CC 93, Place Eugène Bataillon, Université de Montpellier 2, F-34095 Montpellier (France); Bernard, Cécile, E-mail: cbernard@mnhn.fr [UMR7245 MCAM MNHN-CNRS, Muséum National d' Histoire Naturelle, CC 39, 12 rue Buffon, F-75231 Paris, Cedex 05 (France)

2016-07-15

Local species richness (SR) is a key characteristic affecting ecosystem functioning. Yet, the mechanisms regulating phytoplankton diversity in freshwater ecosystems are not fully understood, especially in peri-urban environments where anthropogenic pressures strongly impact the quality of aquatic ecosystems. To address this issue, we sampled the phytoplankton communities of 50 lakes in the Paris area (France) characterized by a large gradient of physico-chemical and catchment-scale characteristics. We used large phytoplankton datasets to describe phytoplankton diversity patterns and applied a machine-learning algorithm to test the degree to which species richness patterns are potentially controlled by environmental factors. Selected environmental factors were studied at two scales: the lake-scale (e.g. nutrients concentrations, water temperature, lake depth) and the catchment-scale (e.g. catchment, landscape and climate variables). Then, we used a variance partitioning approach to evaluate the interaction between lake-scale and catchment-scale variables in explaining local species richness. Finally, we analysed the residuals of predictive models to identify potential vectors of improvement of phytoplankton species richness predictive models. Lake-scale and catchment-scale drivers provided similar predictive accuracy of local species richness (R{sup 2} = 0.458 and 0.424, respectively). Both models suggested that seasonal temperature variations and nutrient supply strongly modulate local species richness. Integrating lake- and catchment-scale predictors in a single predictive model did not provide increased predictive accuracy; therefore suggesting that the catchment-scale model probably explains observed species richness variations through the impact of catchment-scale variables on in-lake water quality characteristics. Models based on catchment characteristics, which include simple and easy to obtain variables, provide a meaningful way of predicting phytoplankton
Final Progress Report: Collaborative Research: Decadal-to-Centennial Climate & Climate Change Studies with Enhanced Variable and Uniform Resolution GCMs Using Advanced Numerical Techniques

Energy Technology Data Exchange (ETDEWEB)

Fox-Rabinovitz, M; Cote, J

2009-06-05

The joint U.S-Canadian project has been devoted to: (a) decadal climate studies using developed state-of-the-art GCMs (General Circulation Models) with enhanced variable and uniform resolution; (b) development and implementation of advanced numerical techniques; (c) research in parallel computing and associated numerical methods; (d) atmospheric chemistry experiments related to climate issues; (e) validation of regional climate modeling strategies for nested- and stretched-grid models. The variable-resolution stretched-grid (SG) GCMs produce accurate and cost-efficient regional climate simulations with mesoscale resolution. The advantage of the stretched grid approach is that it allows us to preserve the high quality of both global and regional circulations while providing consistent interactions between global and regional scales and phenomena. The major accomplishment for the project has been the successful international SGMIP-1 and SGMIP-2 (Stretched-Grid Model Intercomparison Project, phase-1 and phase-2) based on this research developments and activities. The SGMIP provides unique high-resolution regional and global multi-model ensembles beneficial for regional climate modeling and broader modeling community. The U.S SGMIP simulations have been produced using SciDAC ORNL supercomputers. Collaborations with other international participants M. Deque (Meteo-France) and J. McGregor (CSIRO, Australia) and their centers and groups have been beneficial for the strong joint effort, especially for the SGMIP activities. The WMO/WCRP/WGNE endorsed the SGMIP activities in 2004-2008. This project reflects a trend in the modeling and broader communities to move towards regional and sub-regional assessments and applications important for the U.S. and Canadian public, business and policy decision makers, as well as for international collaborations on regional, and especially climate related issues.
Secular variation of the Pacific Decadal Oscillation, the North Pacific Oscillation and climatic jumps in a multi-millennial simulation

Energy Technology Data Exchange (ETDEWEB)

Hunt, B.G. [CSIRO Marine and Atmospheric Research, PO Box 1, Melbourne (Australia)

2008-04-15

Outputs from a 10,000-year simulation with a coupled global climatic model for present climatic conditions have been used to investigate the behaviour of the Pacific Decadal Oscillation (PDO), the North Pacific Oscillation (NPO) and related phenomena. The analysis reveals a wide range of temporal variability for these Oscillations, suggesting that observations to date provide only a limited sample of possible outcomes. In addition, the simulation suggests that the current observed phase relation between the PDO and NPO may not be typical of longer-term variability. Climatic jumps appear to be a ubiquitous feature of climatic variability, and while, as observed, the most common interval between such jumps is about 20 years, intervals of up to 100 years occur in the simulation. The probability density functions of the PDO and NPO are very close to Gaussian, with the PDO being represented by an auto-regressive function of order one, while the NPO consisted of white noise. An FFT analysis of PC1 of the PDO revealed periodicities concentrated near 10 years, while for the NPO the principal periodicities were decadal to bidecadal. Global distributions of the distributions of the correlations between PC1 or the NPO and selected climatic variables were similar, and in agreement with observations. These correlations highlight the inter-relationships between these two Oscillations. The above correlations were not necessarily stable in time for a given geographical point, with transitions occurring between positive and negative extremes. Climatic jumps were identified with transitions of both the PDO and NPO, with magnitudes of importance as regards climatic perturbations. Spatial patterns of the changes associated with such jumps have global scales, and the need to consider the implications of these jumps in regard to greenhouse induced climatic change is noted. (orig.)
Multi-Scale Pattern Recognition for Image Classification and Segmentation

NARCIS (Netherlands)

Li, Y.

2013-01-01

Scale is an important parameter of images. Different objects or image structures (e.g. edges and corners) can appear at different scales and each is meaningful only over a limited range of scales. Multi-scale analysis has been widely used in image processing and computer vision, serving as the basis
Physiologic variability at the verge of systemic inflammation: multi-scale entropy of heart rate variability is affected by very low doses of endotoxin

Science.gov (United States)

Herlitz, Georg N.; Sanders, Renee L.; Cheung, Nora H.; Coyle, Susette M.; Griffel, Benjamin; Macor, Marie A.; Lowry, Stephen F.; Calvano, Steve E.; Gale, Stephen C.

2014-01-01

Introduction Human injury or infection induces systemic inflammation with characteristic neuro-endocrine responses. Fluctuations in autonomic function during inflammation are reflected by beat-to-beat variation in heart rate, termed heart rate variability (HRV). In the present study, we determine threshold doses of endotoxin needed to induce observable changes in markers of systemic inflammation, we investigate whether metrics of HRV exhibit a differing threshold dose from other inflammatory markers, and we investigate the size of data sets required for meaningful use of multi-scale entropy (MSE) analysis of HRV. Methods Healthy human volunteers (n=25) were randomized to receive placebo (normal saline) or endotoxin/lipopolysaccharide (LPS): 0.1, 0.25, 0.5, 1.0, or 2.0 ng/kg administered intravenously. Vital signs were recorded every 30 minutes for 6 hours and then at 9, 12, and 24 hours after LPS. Blood samples were drawn at specific time points for cytokine measurements. HRV analysis was performed using EKG epochs of 5 minutes. MSE for HRV was calculated for all dose groups to scale factor 40. Results The lowest significant threshold dose was noted in core temperature at 0.25ng/kg. Endogenous TNF-α and IL-6 were significantly responsive at the next dosage level (0.5ng/kg) along with elevations in circulating leukocytes and heart rate. Responses were exaggerated at higher doses (1 and 2 ng/kg). Time domain and frequency domain HRV metrics similarly suggested a threshold dose, differing from placebo at 1.0 and 2.0 ng/kg, below which no clear pattern in response was evident. By applying repeated-measures ANOVA across scale factors, a significant decrease in MSE was seen at 1.0 and 2.0 ng/kg by 2 hours post exposure to LPS. While not statistically significant below 1.0 ng/kg, MSE unexpectedly decreased across all groups in an orderly dose-response pattern not seen in the other outcomes. Conclusions By usingrANOVA across scale factors, MSE can detect autonomic change
State-of-the-Art Report on Multi-scale Modelling of Nuclear Fuels

International Nuclear Information System (INIS)

Bartel, T.J.; Dingreville, R.; Littlewood, D.; Tikare, V.; Bertolus, M.; Blanc, V.; Bouineau, V.; Carlot, G.; Desgranges, C.; Dorado, B.; Dumas, J.C.; Freyss, M.; Garcia, P.; Gatt, J.M.; Gueneau, C.; Julien, J.; Maillard, S.; Martin, G.; Masson, R.; Michel, B.; Piron, J.P.; Sabathier, C.; Skorek, R.; Toffolon, C.; Valot, C.; Van Brutzel, L.; Besmann, Theodore M.; Chernatynskiy, A.; Clarno, K.; Gorti, S.B.; Radhakrishnan, B.; Devanathan, R.; Dumont, M.; Maugis, P.; El-Azab, A.; Iglesias, F.C.; Lewis, B.J.; Krack, M.; Yun, Y.; Kurata, M.; Kurosaki, K.; Largenton, R.; Lebensohn, R.A.; Malerba, L.; Oh, J.Y.; Phillpot, S.R.; Tulenko, J. S.; Rachid, J.; Stan, M.; Sundman, B.; Tonks, M.R.; Williamson, R.; Van Uffelen, P.; Welland, M.J.; Valot, Carole; Stan, Marius; Massara, Simone; Tarsi, Reka

2015-10-01

The Nuclear Science Committee (NSC) of the Nuclear Energy Agency (NEA) has undertaken an ambitious programme to document state-of-the-art of modelling for nuclear fuels and structural materials. The project is being performed under the Working Party on Multi-Scale Modelling of Fuels and Structural Material for Nuclear Systems (WPMM), which has been established to assess the scientific and engineering aspects of fuels and structural materials, describing multi-scale models and simulations as validated predictive tools for the design of nuclear systems, fuel fabrication and performance. The WPMM's objective is to promote the exchange of information on models and simulations of nuclear materials, theoretical and computational methods, experimental validation and related topics. It also provides member countries with up-to-date information, shared data, models, and expertise. The goal is also to assess needs for improvement and address them by initiating joint efforts. The WPMM reviews and evaluates multi-scale modelling and simulation techniques currently employed in the selection of materials used in nuclear systems. It serves to provide advice to the nuclear community on the developments needed to meet the requirements of modelling for the design of different nuclear systems. The original WPMM mandate had three components (Figure 1), with the first component currently completed, delivering a report on the state-of-the-art of modelling of structural materials. The work on modelling was performed by three expert groups, one each on Multi-Scale Modelling Methods (M3), Multi-Scale Modelling of Fuels (M2F) and Structural Materials Modelling (SMM). WPMM is now composed of three expert groups and two task forces providing contributions on multi-scale methods, modelling of fuels and modelling of structural materials. This structure will be retained, with the addition of task forces as new topics are developed. The mandate of the Expert Group on Multi-Scale Modelling of
Regional and landscape-scale variability of Landsat-observed vegetation dynamics in northwest Siberian tundra

International Nuclear Information System (INIS)

Frost, Gerald V; Epstein, Howard E; Walker, Donald A

2014-01-01

Widespread increases in Arctic tundra productivity have been documented for decades using coarse-scale satellite observations, but finer-scale observations indicate that changes have been very uneven, with a high degree of landscape- and regional-scale heterogeneity. Here we analyze time-series of the Normalized Difference Vegetation Index (NDVI) observed by Landsat (1984–2012), to assess landscape- and regional-scale variability of tundra vegetation dynamics in the northwest Siberian Low Arctic, a little-studied region with varied soils, landscape histories, and permafrost attributes. We also estimate spatio-temporal rates of land-cover change associated with expansion of tall alder (Alnus) shrublands, by integrating Landsat time-series with very-high-resolution imagery dating to the mid-1960s. We compiled Landsat time-series for eleven widely-distributed landscapes, and performed linear regression of NDVI values on a per-pixel basis. We found positive net NDVI trends (‘greening’) in nine of eleven landscapes. Net greening occurred in alder shrublands in all landscapes, and strong greening tended to correspond to shrublands that developed since the 1960s. Much of the spatial variability of greening within landscapes was linked to landscape physiography and permafrost attributes, while between-landscape variability largely corresponded to differences in surficial geology. We conclude that continued increases in tundra productivity in the region are likely in upland tundra landscapes with fine-textured, cryoturbated soils; these areas currently tend to support discontinuous vegetation cover, but are highly susceptible to rapid increases in vegetation cover, as well as land-cover changes associated with the development of tall shrublands. (paper)
Multi-scale approximation of Vlasov equation

International Nuclear Information System (INIS)

Mouton, A.

2009-09-01

One of the most important difficulties of numerical simulation of magnetized plasmas is the existence of multiple time and space scales, which can be very different. In order to produce good simulations of these multi-scale phenomena, it is recommended to develop some models and numerical methods which are adapted to these problems. Nowadays, the two-scale convergence theory introduced by G. Nguetseng and G. Allaire is one of the tools which can be used to rigorously derive multi-scale limits and to obtain new limit models which can be discretized with a usual numerical method: this procedure is so-called a two-scale numerical method. The purpose of this thesis is to develop a two-scale semi-Lagrangian method and to apply it on a gyrokinetic Vlasov-like model in order to simulate a plasma submitted to a large external magnetic field. However, the physical phenomena we have to simulate are quite complex and there are many questions without answers about the behaviour of a two-scale numerical method, especially when such a method is applied on a nonlinear model. In a first part, we develop a two-scale finite volume method and we apply it on the weakly compressible 1D isentropic Euler equations. Even if this mathematical context is far from a Vlasov-like model, it is a relatively simple framework in order to study the behaviour of a two-scale numerical method in front of a nonlinear model. In a second part, we develop a two-scale semi-Lagrangian method for the two-scale model developed by E. Frenod, F. Salvarani et E. Sonnendrucker in order to simulate axisymmetric charged particle beams. Even if the studied physical phenomena are quite different from magnetic fusion experiments, the mathematical context of the one-dimensional paraxial Vlasov-Poisson model is very simple for establishing the basis of a two-scale semi-Lagrangian method. In a third part, we use the two-scale convergence theory in order to improve M. Bostan's weak-* convergence results about the finite
Multi-function nuclear weight scale system

International Nuclear Information System (INIS)

Zheng Mingquan; Sun Jinhua; Jia Changchun; Wang Mingqian; Tang Ke

1998-01-01

The author introduces the methods to contrive the hardware and software of a Multi-function Nuclear Weight Scale System based on the communication contract in compliance with RS485 between a master (industrial control computer 386) and a slave (single chip 8098) and its main functions
A Multi-Scale Settlement Matching Algorithm Based on ARG

Science.gov (United States)

Yue, Han; Zhu, Xinyan; Chen, Di; Liu, Lingjia

2016-06-01

Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.
Multi-objective optimization and exergetic-sustainability of an irreversible nano scale Braysson cycle operating with Ma

Directory of Open Access Journals (Sweden)

Mohammad H. Ahmadi

2016-06-01

Full Text Available Nano technology is developed in this decade and changes the way of life. Moreover, developing nano technology has effect on the performance of the materials and consequently improves the efficiency and robustness of them. So, nano scale thermal cycles will be probably engaged in the near future. In this paper, a nano scale irreversible Braysson cycle is studied thermodynamically for optimizing the performance of the Braysson cycle. In the aforementioned cycle an ideal Maxwell–Boltzmann gas is used as a working fluid. Furthermore, three different plans are used for optimizing with multi-objectives; though, the outputs of the abovementioned plans are assessed autonomously. Throughout the first plan, with the purpose of maximizing the ecological coefficient of performance and energy efficiency of the system, multi-objective optimization algorithms are used. Furthermore, in the second plan, two objective functions containing the ecological coefficient of performance and the dimensionless Maximum available work are maximized synchronously by utilizing multi-objective optimization approach. Finally, throughout the third plan, three objective functions involving the dimensionless Maximum available work, the ecological coefficient of performance and energy efficiency of the system are maximized synchronously by utilizing multi-objective optimization approach. The multi-objective evolutionary approach based on the non-dominated sorting genetic algorithm approach is used in this research. Making a decision is performed by three different decision makers comprising linear programming approaches for multidimensional analysis of preference and an approach for order of preference by comparison with ideal answer and Bellman–Zadeh. Lastly, analysis of error is employed to determine deviation of the outcomes gained from each plan.
Variational Multi-Scale method with spectral approximation of the sub-scales.

KAUST Repository

Dia, Ben Mansour

2015-01-07

A variational multi-scale method where the sub-grid scales are computed by spectral approximations is presented. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base of eigenfunctions which are orthonormal in weighted L2 spaces. We propose a feasible VMS-spectral method by truncation of this spectral expansion to a nite number of modes.

Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach

International Nuclear Information System (INIS)

Wei, F.; Wu, Q.H.; Jing, Z.X.; Chen, J.J.; Zhou, X.X.

2016-01-01

This paper proposes a comprehensive framework including a multi-objective interval optimization model and evidential reasoning (ER) approach to solve the unit sizing problem of small-scale integrated energy systems, with uncertain wind and solar energies integrated. In the multi-objective interval optimization model, interval variables are introduced to tackle the uncertainties of the optimization problem. Aiming at simultaneously considering the cost and risk of a business investment, the average and deviation of life cycle cost (LCC) of the integrated energy system are formulated. In order to solve the problem, a novel multi-objective optimization algorithm, MGSOACC (multi-objective group search optimizer with adaptive covariance matrix and chaotic search), is developed, employing adaptive covariance matrix to make the search strategy adaptive and applying chaotic search to maintain the diversity of group. Furthermore, ER approach is applied to deal with multiple interests of an investor at the business decision making stage and to determine the final unit sizing solution from the Pareto-optimal solutions. This paper reports on the simulation results obtained using a small-scale direct district heating system (DH) and a small-scale district heating and cooling system (DHC) optimized by the proposed framework. The results demonstrate the superiority of the multi-objective interval optimization model and ER approach in tackling the unit sizing problem of integrated energy systems considering the integration of uncertian wind and solar energies. - Highlights: • Cost and risk of investment in small-scale integrated energy systems are considered. • A multi-objective interval optimization model is presented. • A novel multi-objective optimization algorithm (MGSOACC) is proposed. • The evidential reasoning (ER) approach is used to obtain the final optimal solution. • The MGSOACC and ER can tackle the unit sizing problem efficiently.
Biointerface dynamics--Multi scale modeling considerations.

Science.gov (United States)

Pajic-Lijakovic, Ivana; Levic, Steva; Nedovic, Viktor; Bugarski, Branko

2015-08-01

Irreversible nature of matrix structural changes around the immobilized cell aggregates caused by cell expansion is considered within the Ca-alginate microbeads. It is related to various effects: (1) cell-bulk surface effects (cell-polymer mechanical interactions) and cell surface-polymer surface effects (cell-polymer electrostatic interactions) at the bio-interface, (2) polymer-bulk volume effects (polymer-polymer mechanical and electrostatic interactions) within the perturbed boundary layers around the cell aggregates, (3) cumulative surface and volume effects within the parts of the microbead, and (4) macroscopic effects within the microbead as a whole based on multi scale modeling approaches. All modeling levels are discussed at two time scales i.e. long time scale (cell growth time) and short time scale (cell rearrangement time). Matrix structural changes results in the resistance stress generation which have the feedback impact on: (1) single and collective cell migrations, (2) cell deformation and orientation, (3) decrease of cell-to-cell separation distances, and (4) cell growth. Herein, an attempt is made to discuss and connect various multi scale modeling approaches on a range of time and space scales which have been proposed in the literature in order to shed further light to this complex course-consequence phenomenon which induces the anomalous nature of energy dissipation during the structural changes of cell aggregates and matrix quantified by the damping coefficients (the orders of the fractional derivatives). Deeper insight into the matrix partial disintegration within the boundary layers is useful for understanding and minimizing the polymer matrix resistance stress generation within the interface and on that base optimizing cell growth. Copyright © 2015 Elsevier B.V. All rights reserved.
Multi-scale simulation of droplet-droplet interactions and coalescence

CSIR Research Space (South Africa)

Musehane, Ndivhuwo M

2016-10-01

Full Text Available Conference on Computational and Applied Mechanics Potchefstroom 3–5 October 2016 Multi-scale simulation of droplet-droplet interactions and coalescence 1,2Ndivhuwo M. Musehane?, 1Oliver F. Oxtoby and 2Daya B. Reddy 1. Aeronautic Systems, Council... topology changes that result when droplets interact. This work endeavours to eliminate the need to use empirical correlations based on phenomenological models by developing a multi-scale model that predicts the outcome of a collision between droplets from...
Natural climate variability in a coupled model

International Nuclear Information System (INIS)

Zebiak, S.E.; Cane, M.A.

1990-01-01

Multi-century simulations with a simplified coupled ocean-atmosphere model are described. These simulations reveal an impressive range of variability on decadal and longer time scales, in addition to the dominant interannual el Nino/Southern Oscillation signal that the model originally was designed to simulate. Based on a very large sample of century-long simulations, it is nonetheless possible to identify distinct model parameter sensitivities that are described here in terms of selected indices. Preliminary experiments motivated by general circulation model results for increasing greenhouse gases suggest a definite sensitivity to model global warming. While these results are not definitive, they strongly suggest that coupled air-sea dynamics figure prominently in global change and must be included in models for reliable predictions
Addressing the multi-scale lapsus of landscape : multi-scale landscape process modelling to support sustainable land use : a case study for the Lower Guadalhorce valley South Spain

NARCIS (Netherlands)

Schoorl, J.M.

2002-01-01

"Addressing the Multi-scale Lapsus of Landscape" with the sub-title "Multi-scale landscape process modelling to support sustainable land use: A case study for the Lower Guadalhorce valley South Spain" focuses on the role of

Evaluation of convergence behavior of metamodeling techniques for bridging scales in multi-scale multimaterial simulation

International Nuclear Information System (INIS)

Sen, Oishik; Davis, Sean; Jacobs, Gustaaf; Udaykumar, H.S.

2015-01-01

The effectiveness of several metamodeling techniques, viz. the Polynomial Stochastic Collocation method, Adaptive Stochastic Collocation method, a Radial Basis Function Neural Network, a Kriging Method and a Dynamic Kriging Method is evaluated. This is done with the express purpose of using metamodels to bridge scales between micro- and macro-scale models in a multi-scale multimaterial simulation. The rate of convergence of the error when used to reconstruct hypersurfaces of known functions is studied. For sufficiently large number of training points, Stochastic Collocation methods generally converge faster than the other metamodeling techniques, while the DKG method converges faster when the number of input points is less than 100 in a two-dimensional parameter space. Because the input points correspond to computationally expensive micro/meso-scale computations, the DKG is favored for bridging scales in a multi-scale solver

Hydroclimate variability in NE Brazil over the last 2K

Science.gov (United States)

Giselle, Utida; Ioanna, Bouloubassi; Francisco, Cruz; Enno, Schefuβ; Abdel, Sifeddine; Vincent, Klein; Johan, Etourneau; Renata, Zocatelli; André, Zular; Hai, Cheng; Laurence, Edwards R.

2016-04-01

Precipitation associated with the South American Summer Monsoon (SASM) and the Intertropical Convergence Zone (ITCZ) supplies more than 70% of tropical South America's annual precipitation and is fundamental in sustaining the water regime for regional socioeconomic activities. Motivated by the fact that the greatest uncertainty in model projections of future precipitation trends lies in the tropics, and particularly in South America, a number of recent proxy and modeling studies have aimed at understanding SASM spatiotemporal variability regarding its dynamics, driving mechanisms and teleconnections. Exact reconstructions of past meridional ITCZ displacements (timing, sign, amplitude), however, are currently lacking, mainly because of the paucity of suited high-resolution archives. This restricts our ability to assess regional rainfall variability at decadal to centennial timescales, especially in the hydroclimatic-sensitive semi-arid Nordeste, needed to understand the interactions between SASM and ITCZ and to evaluate the impact of Pacific-Atlantic climate interactions on the regional rainfall variability at decadal/multi-decadal scale. Here we present two new and complementary high-resolution records of past precipitation over the last 2K from the north area of Nordeste, an area ideally located to track fluctuations in the southernmost edge of ITCZ movement. We present a new δO18 record from a local speleothem and combine it, for the first time, with δD analyses of wax lipids in well-dated sediments from a nearby lake. The two independent records show a remarkable similarity and are characterized by strong decadal to multidecadal variability as well as century-scale changes. The period 250-450 yrs CE appears as the wettest phase over the last 2K, while the Medieval Climate Anomaly (MCA) is characterized by extremely dry conditions. Following the MCA, the Little Ice Age (LIA) is a relatively wetter phase. The data document fluctuations of southern meridional

Testing the Effectiveness of Environmental Variables to Explain European Terrestrial Vertebrate Species Richness across Biogeographical Scales.

Directory of Open Access Journals (Sweden)

Maud Mouchet

Full Text Available We compared the effectiveness of environmental variables, and in particular of land-use indicators, to explain species richness patterns across taxonomic groups and biogeographical scales (i.e. overall pan-Europe and ecoregions within pan-Europe. Using boosted regression trees that handle non-linear relationships, we compared the relative influence (as a measure of effectiveness of environmental variables related to climate, landscape (or habitat heterogeneity, land-use intensity or energy availability to explain European vertebrate species richness (birds, amphibians, and mammals at the continental and ecoregion scales. We found that dominant land cover and actual evapotranspiration that relate to energy availability were the main correlates of vertebrate species richness over Europe. At the ecoregion scale, we identified four distinct groups of ecoregions where species richness was essentially associated to (i seasonality of temperature, (ii actual evapotranspiration and/or mean annual temperature, (iii seasonality of precipitation, actual evapotranspiration and land cover and (iv and an even combination of the environmental variables. This typology of ecoregions remained valid for total vertebrate richness and the three vertebrate groups taken separately. Despite the overwhelming influence of land cover and actual evapotranspiration to explain vertebrate species richness patterns at European scale, the ranking of the main correlates of species richness varied between regions. Interestingly, landscape and land-use indicators did not stand out at the continental scale but their influence greatly increased in southern ecoregions, revealing the long-lasting human footprint on land-use-land-cover changes. Our study provides one of the first multi-scale descriptions of the variability in the ranking of correlates across several taxa.

Decadal-scale teleconnection between South Atlantic SST and southeast Australia surface air temperature in austral summer

Science.gov (United States)

Xue, Jiaqing; Li, Jianping; Sun, Cheng; Zhao, Sen; Mao, Jiangyu; Dong, Di; Li, Yanjie; Feng, Juan

2018-04-01

Austral summer (December-February) surface air temperature over southeast Australia (SEA) is found to be remotely influenced by sea surface temperature (SST) in the South Atlantic at decadal time scales. In austral summer, warm SST anomalies in the southwest South Atlantic induce concurrent above-normal surface air temperature over SEA. This decadal-scale teleconnection occurs through the eastward propagating South Atlantic-Australia (SAA) wave train triggered by SST anomalies in the southwest South Atlantic. The excitation of the SAA wave train is verified by forcing experiments based on both linear barotropic and baroclinic models, propagation pathway and spatial scale of the observed SAA wave train are further explained by the Rossby wave ray tracing analysis in non-uniform basic flow. The SAA wave train forced by southwest South Atlantic warming is characterized by an anomalous anticyclone off the eastern coast of the Australia. Temperature diagnostic analyses based on the thermodynamic equation suggest anomalous northerly flows on western flank of this anticyclone can induce low-level warm advection anomaly over SEA, which thus lead to the warming of surface air temperature there. Finally, SST-forced atmospheric general circulation model ensemble experiments also demonstrate that SST forcing in the South Atlantic is associated with the SAA teleconnection wave train in austral summer, this wave train then modulate surface air temperature over SEA on decadal timescales. Hence, observations combined with numerical simulations consistently demonstrate the decadal-scale teleconnection between South Atlantic SST and summertime surface air temperature over SEA.

A rate-dependent multi-scale crack model for concrete

NARCIS (Netherlands)

Karamnejad, A.; Nguyen, V.P.; Sluys, L.J.

2013-01-01

A multi-scale numerical approach for modeling cracking in heterogeneous quasi-brittle materials under dynamic loading is presented. In the model, a discontinuous crack model is used at macro-scale to simulate fracture and a gradient-enhanced damage model has been used at meso-scale to simulate

Development of multi-dimensional body image scale for malaysian female adolescents.

Science.gov (United States)

Chin, Yit Siew; Taib, Mohd Nasir Mohd; Shariff, Zalilah Mohd; Khor, Geok Lin

2008-01-01

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs.

Assessing large-scale weekly cycles in meteorological variables: a review

Directory of Open Access Journals (Sweden)

A. Sanchez-Lorenzo

2012-07-01

Full Text Available Several studies have claimed to have found significant weekly cycles of meteorological variables appearing over large domains, which can hardly be related to urban effects exclusively. Nevertheless, there is still an ongoing scientific debate whether these large-scale weekly cycles exist or not, and some other studies fail to reproduce them with statistical significance. In addition to the lack of the positive proof for the existence of these cycles, their possible physical explanations have been controversially discussed during the last years. In this work we review the main results about this topic published during the recent two decades, including a summary of the existence or non-existence of significant weekly weather cycles across different regions of the world, mainly over the US, Europe and Asia. In addition, some shortcomings of common statistical methods for analyzing weekly cycles are listed. Finally, a brief summary of supposed causes of the weekly cycles, focusing on the aerosol-cloud-radiation interactions and their impact on meteorological variables as a result of the weekly cycles of anthropogenic activities, and possible directions for future research, is presented.

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

Science.gov (United States)

Kou, Jisheng; Sun, Shuyu

2016-08-01

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

KAUST Repository

Kou, Jisheng

2016-05-10

A Multi-Scale Settlement Matching Algorithm Based on ARG

Directory of Open Access Journals (Sweden)

H. Yue

2016-06-01

Full Text Available Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.

Classification of high-resolution remote sensing images based on multi-scale superposition

Science.gov (United States)

Wang, Jinliang; Gao, Wenjie; Liu, Guangjie

2017-07-01

Landscape structures and process on different scale show different characteristics. In the study of specific target landmarks, the most appropriate scale for images can be attained by scale conversion, which improves the accuracy and efficiency of feature identification and classification. In this paper, the authors carried out experiments on multi-scale classification by taking the Shangri-la area in the north-western Yunnan province as the research area and the images from SPOT5 HRG and GF-1 Satellite as date sources. Firstly, the authors upscaled the two images by cubic convolution, and calculated the optimal scale for different objects on the earth shown in images by variation functions. Then the authors conducted multi-scale superposition classification on it by Maximum Likelyhood, and evaluated the classification accuracy. The results indicates that: (1) for most of the object on the earth, the optimal scale appears in the bigger scale instead of the original one. To be specific, water has the biggest optimal scale, i.e. around 25-30m; farmland, grassland, brushwood, roads, settlement places and woodland follows with 20-24m. The optimal scale for shades and flood land is basically as the same as the original one, i.e. 8m and 10m respectively. (2) Regarding the classification of the multi-scale superposed images, the overall accuracy of the ones from SPOT5 HRG and GF-1 Satellite is 12.84% and 14.76% higher than that of the original multi-spectral images, respectively, and Kappa coefficient is 0.1306 and 0.1419 higher, respectively. Hence, the multi-scale superposition classification which was applied in the research area can enhance the classification accuracy of remote sensing images .

Natural climate variability inferred from cosmogenic isotopes and other geophysical data and its impact on human activity

International Nuclear Information System (INIS)

Creer, K.M.

2001-01-01

The way how natural climate changes may have influenced anthropological development is discussed. The main characteristics of solar variability are reviewed: (1) as measured in detail over recent decades by instruments on-board artificial satellites; (2) as recorded in historical documents on the time-scale of centuries; and (3) as inferred on millennial time-scales from archived records of the cosmogenically generated isotopes 14 C and 10 Be. The older, proxy data comprise temperature changes reconstructed from tree ring studies and environmental changes deduced from multi-disciplinary studies of lake sediments. The effects of changes in ocean circulation and the sporadic influence of volcanic activity are also considered briefly. (author)

Small-scale variability in tropical tropopause layer humidity

Science.gov (United States)

Jensen, E. J.; Ueyama, R.; Pfister, L.; Karcher, B.; Podglajen, A.; Diskin, G. S.; DiGangi, J. P.; Thornberry, T. D.; Rollins, A. W.; Bui, T. V.; Woods, S.; Lawson, P.

2016-12-01

Recent advances in statistical parameterizations of cirrus cloud processes for use in global models are highlighting the need for information about small-scale fluctuations in upper tropospheric humidity and the physical processes that control the humidity variability. To address these issues, we have analyzed high-resolution airborne water vapor measurements obtained in the Airborne Tropical TRopopause EXperiment over the tropical Pacific between 14 and 20 km. Using accurate and precise 1-Hz water vapor measurements along approximately-level aircraft flight legs, we calculate structure functions spanning horizontal scales ranging from about 0.2 to 50 km, and we compare the water vapor variability in the lower (about 14 km) and upper (16-19 km) Tropical Tropopause Layer (TTL). We also compare the magnitudes and scales of variability inside TTL cirrus versus in clear-sky regions. The measurements show that in the upper TTL, water vapor concentration variance is stronger inside cirrus than in clear-sky regions. Using simulations of TTL cirrus formation, we show that small variability in clear-sky humidity is amplified by the strong sensitivity of ice nucleation rate to supersaturation, which results in highly-structured clouds that subsequently drive variability in the water vapor field. In the lower TTL, humidity variability is correlated with recent detrainment from deep convection. The structure functions indicate approximately power-law scaling with spectral slopes ranging from about -5/3 to -2.

Multi-scale graphene patterns on arbitrary substrates via laser-assisted transfer-printing process

KAUST Repository

Park, J. B.

2012-01-01

A laser-assisted transfer-printing process is developed for multi-scale graphene patterns on arbitrary substrates using femtosecond laser scanning on a graphene/metal substrate and transfer techniques without using multi-step patterning processes. The short pulse nature of a femtosecond laser on a graphene/copper sheet enables fabrication of high-resolution graphene patterns. Thanks to the scale up, fast, direct writing, multi-scale with high resolution, and reliable process characteristics, it can be an alternative pathway to the multi-step photolithography methods for printing arbitrary graphene patterns on desired substrates. We also demonstrate transparent strain devices without expensive photomasks and multi-step patterning process. © 2012 American Institute of Physics.

Flatfish recruitment response to decadal climatic variability and ocean conditions in the eastern Bering Sea

Science.gov (United States)

Wilderbuer, T. K.; Hollowed, A. B.; Ingraham, W. J.; Spencer, P. D.; Conners, M. E.; Bond, N. A.; Walters, G. E.

2002-10-01

This paper provides a retrospective analysis of the relationship of physical oceanography and biology and recruitment of three Eastern Bering Sea flatfish stocks: flathead sole ( Hippoglossoides elassodon), northern rock sole ( Lepidopsetta polyxystra), and arrowtooth flounder ( Atheresthes stomias) for the period 1978-1996. Temporal trends in flatfish production in the Eastern Bering Sea are consistent with the hypothesis that decadal scale climate variability influences marine survival during the early life history period. Density-dependence (spawning stock size) is statistically significant in a Ricker model of flatfish recruitment, which includes environmental terms. Wind-driven advection of flatfish larvae to favorable nursery grounds was also found to coincide with years of above-average recruitment through the use of an ocean surface current simulation model (OSCURS). Ocean forcing of Bristol Bay surface waters during springtime was mostly shoreward (eastward) during the 1980s and seaward (westerly) during the 1990s, corresponding with periods of good and poor recruitment. Distance from shore and water depth at the endpoint of 90-day drift periods (estimated time of settlement) were also found to correspond with flatfish productivity.

Multi-decadal analysis reveals contrasting patterns of resilience and decline in coral assemblages

Science.gov (United States)

Tanner, Jason E.

2017-12-01

A 50-yr study of coral dynamics at Heron Island, on Australia's Great Barrier Reef, shows that community change on a single reef is highly variable and that while some areas of the reef are in decline, others are recovering well 40 yr after a major cyclonic disturbance that eliminated all corals in the study plot. At one site, the genus-level composition in 2012 was identical to that before the cyclone, although it took around 30 yr to recover, and there were still differences at the species level. The colony size structure of some species at this site, notably the dominant Acropora digitifera, which had over 40% cover in 2012, also recovered after 30 yr, although sub-dominant species still lacked large colonies even after 40 yr. Given the small scale of the individual study plots (1 m2), this shows an unexpected degree of determinism in assemblage structure. At a second site, however, both composition and size structure changed dramatically over the last 40 yr of the study as both external and internal factors altered local environmental conditions. At both sites, major changes in composition appear to be related to drying out of the reef crest due to changes in flow regimes and/or natural accretion. At the site that has recovered, erosion has reversed this drying out, whereas no such erosion has occurred at the second site. If such erosion occurs, or sea levels increase due to global warming, then the second site may also prove to be resilient over decadal time scales.
A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

Science.gov (United States)

Tao, W. K.

2017-12-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.
Reactor scale modeling of multi-walled carbon nanotube growth

International Nuclear Information System (INIS)

Lombardo, Jeffrey J.; Chiu, Wilson K.S.

2011-01-01

As the mechanisms of carbon nanotube (CNT) growth becomes known, it becomes important to understand how to implement this knowledge into reactor scale models to optimize CNT growth. In past work, we have reported fundamental mechanisms and competing deposition regimes that dictate single wall carbon nanotube growth. In this study, we will further explore the growth of carbon nanotubes with multiple walls. A tube flow chemical vapor deposition reactor is simulated using the commercial software package COMSOL, and considered the growth of single- and multi-walled carbon nanotubes. It was found that the limiting reaction processes for multi-walled carbon nanotubes change at different temperatures than the single walled carbon nanotubes and it was shown that the reactions directly governing CNT growth are a limiting process over certain parameters. This work shows that the optimum conditions for CNT growth are dependent on temperature, chemical concentration, and the number of nanotube walls. Optimal reactor conditions have been identified as defined by (1) a critical inlet methane concentration that results in hydrogen abstraction limited versus hydrocarbon adsorption limited reaction kinetic regime, and (2) activation energy of reaction for a given reactor temperature and inlet methane concentration. Successful optimization of a CNT growth processes requires taking all of those variables into account.
Cloud Detection by Fusing Multi-Scale Convolutional Features

Science.gov (United States)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.
Interannual to Decadal Variability of Atlantic Water in the Nordic and Adjacent Seas

Science.gov (United States)

Carton, James A.; Chepurin, Gennady A.; Reagan, James; Haekkinen, Sirpa

2011-01-01

Warm salty Atlantic Water is the main source water for the Arctic Ocean and thus plays an important role in the mass and heat budget of the Arctic. This study explores interannual to decadal variability of Atlantic Water properties in the Nordic Seas area where Atlantic Water enters the Arctic, based on a reexamination of the historical hydrographic record for the years 1950-2009, obtained by combining multiple data sets. The analysis shows a succession of four multi-year warm events where temperature anomalies at 100m depth exceed 0.4oC, and three cold events. Three of the four warm events lasted 3-4 years, while the fourth began in 1999 and persists at least through 2009. This most recent warm event is anomalous in other ways as well, being the strongest, having the broadest geographic extent, being surface-intensified, and occurring under exceptional meteorological conditions. Three of the four warm events were accompanied by elevated salinities consistent with enhanced ocean transport into the Nordic Seas, with the exception of the event spanning July 1989-July 1993. Of the three cold events, two lasted for four years, while the third lasted for nearly 14 years. Two of the three cold events are associated with reduced salinities, but the cold event of the 1960s had elevated salinities. The relationship of these events to meteorological conditions is examined. The results show that local surface heat flux variations act in some cases to reinforce the anomalies, but are too weak to be the sole cause.
Multi-scale habitat selection modeling: A review and outlook

Science.gov (United States)

Kevin McGarigal; Ho Yi Wan; Kathy A. Zeller; Brad C. Timm; Samuel A. Cushman

2016-01-01

Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.
Decadal variability of Subtropical Mode Water subduction and its impact on biogeochemistry

Science.gov (United States)

Oka, E.; Qiu, B.; Takatani, Y.; Enyo, K.; Sasano, D.; Kosugi, N.; Ishii, M.; Nakano, T.; Suga, T.

2016-02-01

Temperature and salinity data from Argo profiling floats during 2005-2014 were analyzed to examine the decadal variability of the North Pacific Subtropical Mode Water (STMW) in relation to that of the Kuroshio Extension (KE) system. The formation volume of STMW in the southern recirculation gyre of KE in the cooling season was larger during the stable KE period after 2010 than the unstable KE period of 2006-2009 by 50%. As a result, the volume and spatial extent of STMW increased (decreased) in the formation region during the stable (unstable) KE period, as well as in the southern, downstream region with a time lag of 1-2 years. The decadal expansion and contraction of STMW were also detected by shipboard observations conducted routinely in the most downstream region near the western boundary, in terms of not only physical but also biogeochemical parameters. After 2010, enhanced subduction of STMW consistently increased dissolved oxygen, pH, and aragonite saturation state and decreased potential vorticity, apparent oxygen utilization, nitrate, and dissolved inorganic carbon, among which changes of dissolved inorganic carbon, pH, and aragonite saturation state were against their long-term trends. These results indicate a new mechanism consisting of westward sea surface height anomaly propagation, the KE state transition, and the STMW formation and subduction, by which the climate variability affects physical and biogeochemical structures in the ocean's interior and potentially impacts the surface ocean acidification trend and biological production.
Evaluating the Performance of the Goddard Multi-Scale Modeling Framework against GPM, TRMM and CloudSat/CALIPSO Products

Science.gov (United States)

Chern, J. D.; Tao, W. K.; Lang, S. E.; Matsui, T.; Mohr, K. I.

2014-12-01

Four six-month (March-August 2014) experiments with the Goddard Multi-scale Modeling Framework (MMF) were performed to study the impacts of different Goddard one-moment bulk microphysical schemes and large-scale forcings on the performance of the MMF. Recently a new Goddard one-moment bulk microphysics with four-ice classes (cloud ice, snow, graupel, and frozen drops/hail) has been developed based on cloud-resolving model simulations with large-scale forcings from field campaign observations. The new scheme has been successfully implemented to the MMF and two MMF experiments were carried out with this new scheme and the old three-ice classes (cloud ice, snow graupel) scheme. The MMF has global coverage and can rigorously evaluate microphysics performance for different cloud regimes. The results show MMF with the new scheme outperformed the old one. The MMF simulations are also strongly affected by the interaction between large-scale and cloud-scale processes. Two MMF sensitivity experiments with and without nudging large-scale forcings to those of ERA-Interim reanalysis were carried out to study the impacts of large-scale forcings. The model simulated mean and variability of surface precipitation, cloud types, cloud properties such as cloud amount, hydrometeors vertical profiles, and cloud water contents, etc. in different geographic locations and climate regimes are evaluated against GPM, TRMM, CloudSat/CALIPSO satellite observations. The Goddard MMF has also been coupled with the Goddard Satellite Data Simulation Unit (G-SDSU), a system with multi-satellite, multi-sensor, and multi-spectrum satellite simulators. The statistics of MMF simulated radiances and backscattering can be directly compared with satellite observations to assess the strengths and/or deficiencies of MMF simulations and provide guidance on how to improve the MMF and microphysics.
Multi-Site and Multi-Variables Statistical Downscaling Technique in the Monsoon Dominated Region of Pakistan

Science.gov (United States)

Khan, Firdos; Pilz, Jürgen

2016-04-01

South Asia is under the severe impacts of changing climate and global warming. The last two decades showed that climate change or global warming is happening and the first decade of 21st century is considered as the warmest decade over Pakistan ever in history where temperature reached 53 0C in 2010. Consequently, the spatio-temporal distribution and intensity of precipitation is badly effected and causes floods, cyclones and hurricanes in the region which further have impacts on agriculture, water, health etc. To cope with the situation, it is important to conduct impact assessment studies and take adaptation and mitigation remedies. For impact assessment studies, we need climate variables at higher resolution. Downscaling techniques are used to produce climate variables at higher resolution; these techniques are broadly divided into two types, statistical downscaling and dynamical downscaling. The target location of this study is the monsoon dominated region of Pakistan. One reason for choosing this area is because the contribution of monsoon rains in this area is more than 80 % of the total rainfall. This study evaluates a statistical downscaling technique which can be then used for downscaling climatic variables. Two statistical techniques i.e. quantile regression and copula modeling are combined in order to produce realistic results for climate variables in the area under-study. To reduce the dimension of input data and deal with multicollinearity problems, empirical orthogonal functions will be used. Advantages of this new method are: (1) it is more robust to outliers as compared to ordinary least squares estimates and other estimation methods based on central tendency and dispersion measures; (2) it preserves the dependence among variables and among sites and (3) it can be used to combine different types of distributions. This is important in our case because we are dealing with climatic variables having different distributions over different meteorological
Past climate variability between 97 and 7 ka reconstructed from a multi proxy speleothem record from Western Cuba

Science.gov (United States)

Winterhalder, Sophie; Scholz, Denis; Mangini, Augusto; Spötl, Christoph; Jochum, Klaus Peter; Pajón, Jesús M.

2016-04-01

. Due to the competing influence of the NA, the Gulf of Mexico and the Pacific Ocean, the proposed severe changes in the tropical hydrological cycle during that time (such as variations of the ITCZ, insolation and the thermohaline circulation (THC)) have potentially lead to significant changes in sources and trajectories of precipitation in Western Cuba. Our record, thus, provides an important contribution towards understanding and differentiating these parameters on Caribbean climate during glacial climate changes. References: Fensterer, C., Scholz, D., Hoffmann, D., Spötl, C., Pajón, J.M., Mangini, A., 2012. Cuban stalagmite suggests relationship between Caribbean precipitation and the Atlantic Multidecadal Oscillation during the past 1.3 ka. The Holocene, 0959683612449759. Fensterer, C., Scholz, D., Hoffmann, D.L., Spötl, C., Schröder-Ritzrau, A., Horn, C., Pajón, J.M., Mangini, A., 2013. Millennial-scale climate variability during the last 12.5 ka recorded in a Caribbean speleothem. Earth and Planetary Science Letters 361, 143-151. Winter, A., Miller, T., Kushnir, Y., Sinha, A., Timmermann, A., Jury, M.R., Gallup, C., Cheng, H., Edwards, R.L., 2011. Evidence for 800years of North Atlantic multi-decadal variability from a Puerto Rican speleothem. Earth and Planetary Science Letters 308, 23-28.
What is at stake in multi-scale approaches

International Nuclear Information System (INIS)

Jamet, Didier

2008-01-01

Full text of publication follows: Multi-scale approaches amount to analyzing physical phenomena at small space and time scales in order to model their effects at larger scales. This approach is very general in physics and engineering; one of the best examples of success of this approach is certainly statistical physics that allows to recover classical thermodynamics and to determine the limits of application of classical thermodynamics. Getting access to small scale information aims at reducing the models' uncertainty but it has a cost: fine scale models may be more complex than larger scale models and their resolution may require the development of specific and possibly expensive methods, numerical simulation techniques and experiments. For instance, in applications related to nuclear engineering, the application of computational fluid dynamics instead of cruder models is a formidable engineering challenge because it requires resorting to high performance computing. Likewise, in two-phase flow modeling, the techniques of direct numerical simulation, where all the interfaces are tracked individually and where all turbulence scales are captured, are getting mature enough to be considered for averaged modeling purposes. However, resolving small scale problems is a necessary step but it is not sufficient in a multi-scale approach. An important modeling challenge is to determine how to treat small scale data in order to get relevant information for larger scale models. For some applications, such as single-phase turbulence or transfers in porous media, this up-scaling approach is known and is now used rather routinely. However, in two-phase flow modeling, the up-scaling approach is not as mature and specific issues must be addressed that raise fundamental questions. This will be discussed and illustrated. (author)
Multi-Scale Multi-physics Methods Development for the Calculation of Hot-Spots in the NGNP

International Nuclear Information System (INIS)

Downar, Thomas; Seker, Volkan

2013-01-01

Radioactive gaseous fission products are released out of the fuel element at a significantly higher rate when the fuel temperature exceeds 1600°C in high-temperature gas-cooled reactors (HTGRs). Therefore, it is of paramount importance to accurately predict the peak fuel temperature during all operational and design-basis accident conditions. The current methods used to predict the peak fuel temperature in HTGRs, such as the Next-Generation Nuclear Plant (NGNP), estimate the average fuel temperature in a computational mesh modeling hundreds of fuel pebbles or a fuel assembly in a pebble-bed reactor (PBR) or prismatic block type reactor (PMR), respectively. Experiments conducted in operating HTGRs indicate considerable uncertainty in the current methods and correlations used to predict actual temperatures. The objective of this project is to improve the accuracy in the prediction of local 'hot' spots by developing multi-scale, multi-physics methods and implementing them within the framework of established codes used for NGNP analysis.The multi-scale approach which this project will implement begins with defining suitable scales for a physical and mathematical model and then deriving and applying the appropriate boundary conditions between scales. The macro scale is the greatest length that describes the entire reactor, whereas the meso scale models only a fuel block in a prismatic reactor and ten to hundreds of pebbles in a pebble bed reactor. The smallest scale is the micro scale--the level of a fuel kernel of the pebble in a PBR and fuel compact in a PMR--which needs to be resolved in order to calculate the peak temperature in a fuel kernel.
Multi-Scale Multi-physics Methods Development for the Calculation of Hot-Spots in the NGNP

Energy Technology Data Exchange (ETDEWEB)

Downar, Thomas [Univ. of Michigan, Ann Arbor, MI (United States); Seker, Volkan [Univ. of Michigan, Ann Arbor, MI (United States)

2013-04-30

Radioactive gaseous fission products are released out of the fuel element at a significantly higher rate when the fuel temperature exceeds 1600°C in high-temperature gas-cooled reactors (HTGRs). Therefore, it is of paramount importance to accurately predict the peak fuel temperature during all operational and design-basis accident conditions. The current methods used to predict the peak fuel temperature in HTGRs, such as the Next-Generation Nuclear Plant (NGNP), estimate the average fuel temperature in a computational mesh modeling hundreds of fuel pebbles or a fuel assembly in a pebble-bed reactor (PBR) or prismatic block type reactor (PMR), respectively. Experiments conducted in operating HTGRs indicate considerable uncertainty in the current methods and correlations used to predict actual temperatures. The objective of this project is to improve the accuracy in the prediction of local "hot" spots by developing multi-scale, multi-physics methods and implementing them within the framework of established codes used for NGNP analysis.The multi-scale approach which this project will implement begins with defining suitable scales for a physical and mathematical model and then deriving and applying the appropriate boundary conditions between scales. The macro scale is the greatest length that describes the entire reactor, whereas the meso scale models only a fuel block in a prismatic reactor and ten to hundreds of pebbles in a pebble bed reactor. The smallest scale is the micro scale--the level of a fuel kernel of the pebble in a PBR and fuel compact in a PMR--which needs to be resolved in order to calculate the peak temperature in a fuel kernel.
Macroweather Predictions and Climate Projections using Scaling and Historical Observations

Science.gov (United States)

Hébert, R.; Lovejoy, S.; Del Rio Amador, L.

2017-12-01

There are two fundamental time scales that are pertinent to decadal forecasts and multidecadal projections. The first is the lifetime of planetary scale structures, about 10 days (equal to the deterministic predictability limit), and the second is - in the anthropocene - the scale at which the forced anthropogenic variability exceeds the internal variability (around 16 - 18 years). These two time scales define three regimes of variability: weather, macroweather and climate that are respectively characterized by increasing, decreasing and then increasing varibility with scale.We discuss how macroweather temperature variability can be skilfully predicted to its theoretical stochastic predictability limits by exploiting its long-range memory with the Stochastic Seasonal and Interannual Prediction System (StocSIPS). At multi-decadal timescales, the temperature response to forcing is approximately linear and this can be exploited to make projections with a Green's function, or Climate Response Function (CRF). To make the problem tractable, we exploit the temporal scaling symmetry and restrict our attention to global mean forcing and temperature response using a scaling CRF characterized by the scaling exponent H and an inner scale of linearity τ. An aerosol linear scaling factor α and a non-linear volcanic damping exponent ν were introduced to account for the large uncertainty in these forcings. We estimate the model and forcing parameters by Bayesian inference using historical data and these allow us to analytically calculate a median (and likely 66% range) for the transient climate response, and for the equilibrium climate sensitivity: 1.6K ([1.5,1.8]K) and 2.4K ([1.9,3.4]K) respectively. Aerosol forcing typically has large uncertainty and we find a modern (2005) forcing very likely range (90%) of [-1.0, -0.3] Wm-2 with median at -0.7 Wm-2. Projecting to 2100, we find that to keep the warming below 1.5 K, future emissions must undergo cuts similar to Representative
Natural variability in the surface ocean carbonate ion concentration

OpenAIRE

N. S. Lovenduski; M. C. Long; K. Lindsay

2015-01-01

We investigate variability in the surface ocean carbonate ion concentration ([CO32−]) on the basis of a long control simulation with a fully-coupled Earth System Model. The simulation is run with a prescribed, pre-industrial atmospheric CO2 concentration for 1000 years, permitting investigation of natural [CO32−] variability on interannual to multi-decadal timescales. We find high interannual variability in surface [CO32−] in the tropical...
Natural variability in the surface ocean carbonate ion concentration

OpenAIRE

Lovenduski, N. S.; Long, M. C.; Lindsay, K.

2015-01-01

We investigate variability in the surface ocean carbonate ion concentration ([CO32−]) on the basis of a~long control simulation with an Earth System Model. The simulation is run with a prescribed, pre-industrial atmospheric CO2 concentration for 1000 years, permitting investigation of natural [CO32−] variability on interannual to multi-decadal timescales. We find high interannual variability in surface [CO32−] in the tropical Pacific and ...
Mixing in 3D Sparse Multi-Scale Grid Generated Turbulence

Science.gov (United States)

Usama, Syed; Kopec, Jacek; Tellez, Jackson; Kwiatkowski, Kamil; Redondo, Jose; Malik, Nadeem

2017-04-01

Flat 2D fractal grids are known to alter turbulence characteristics downstream of the grid as compared to the regular grids with the same blockage ratio and the same mass inflow rates [1]. This has excited interest in the turbulence community for possible exploitation for enhanced mixing and related applications. Recently, a new 3D multi-scale grid design has been proposed [2] such that each generation of length scale of turbulence grid elements is held in its own frame, the overall effect is a 3D co-planar arrangement of grid elements. This produces a 'sparse' grid system whereby each generation of grid elements produces a turbulent wake pattern that interacts with the other wake patterns downstream. A critical motivation here is that the effective blockage ratio in the 3D Sparse Grid Turbulence (3DSGT) design is significantly lower than in the flat 2D counterpart - typically the blockage ratio could be reduced from say 20% in 2D down to 4% in the 3DSGT. If this idea can be realized in practice, it could potentially greatly enhance the efficiency of turbulent mixing and transfer processes clearly having many possible applications. Work has begun on the 3DSGT experimentally using Surface Flow Image Velocimetry (SFIV) [3] at the European facility in the Max Planck Institute for Dynamics and Self-Organization located in Gottingen, Germany and also at the Technical University of Catalonia (UPC) in Spain, and numerically using Direct Numerical Simulation (DNS) at King Fahd University of Petroleum & Minerals (KFUPM) in Saudi Arabia and in University of Warsaw in Poland. DNS is the most useful method to compare the experimental results with, and we are studying different types of codes such as Imcompact3d, and OpenFoam. Many variables will eventually be investigated for optimal mixing conditions. For example, the number of scale generations, the spacing between frames, the size ratio of grid elements, inflow conditions, etc. We will report upon the first set of findings
Continental-Scale Temperature Reconstructions from the PAGES 2k Network

Science.gov (United States)

Kaufman, D. S.

2012-12-01

We present a major new synthesis of seven regional temperature reconstructions to elucidate the global pattern of variations and their association with climate-forcing mechanisms over the past two millennia. To coordinate the integration of new and existing data of all proxy types, the Past Global Changes (PAGES) project developed the 2k Network. It comprises nine working groups representing eight continental-scale regions and the oceans. The PAGES 2k Consortium, authoring this paper, presently includes 79 representatives from 25 countries. For this synthesis, each of the PAGES 2k working groups identified the proxy climate records for reconstructing past temperature and associated uncertainty using the data and methodologies that they deemed most appropriate for their region. The datasets are from 973 sites where tree rings, pollen, corals, lake and marine sediment, glacier ice, speleothems, and historical documents record changes in biologically and physically mediated processes that are sensitive to temperature change, among other climatic factors. The proxy records used for this synthesis are available through the NOAA World Data Center for Paleoclimatology. On long time scales, the temperature reconstructions display similarities among regions, and a large part of this common behavior can be explained by known climate forcings. Reconstructed temperatures in all regions show an overall long-term cooling trend until around 1900 C.E., followed by strong warming during the 20th century. On the multi-decadal time scale, we assessed the variability among the temperature reconstructions using principal component (PC) analysis of the standardized decadal mean temperatures over the period of overlap among the reconstructions (1200 to 1980 C.E.). PC1 explains 35% of the total variability and is strongly correlated with temperature reconstructions from the four Northern Hemisphere regions, and with the sum of external forcings including solar, volcanic, and greenhouse
Can intraseasonal to decadal forecasts benefit from from consideration of lunar forcing?

CSIR Research Space (South Africa)

Malherbe, J

2014-10-01

Full Text Available A possible forcing mechanism for intra-seasonal rainfall distribution to bi-decadal climate variability is explored. The atmospheric response to external forcing is demonstrated at a daily and annual time scale by noting variation in the Southern...
Simulated European stalagmite record and its relation to a quasi-decadal climate mode

Directory of Open Access Journals (Sweden)

G. Lohmann

2013-01-01

Full Text Available A synthetic stalagmite δ18O record for the Bunker Cave (51° N, 7° E is constructed using a combined climate–stalagmite modelling approach where we combine an atmospheric circulation model equipped with water isotopes and a model simulating stalagmite calcite δ18O values. Mixing processes in the soil and karst above the cave represent a natural low-pass filter of the speleothem climate archive. Stalagmite δ18O values at Bunker Cave lag the regional surface climate by 3–4 yr. The power spectrum of the simulated speleothem calcite δ18O record has a pronounced peak at quasi-decadal time scale, which is associated with a large-scale climate variability pattern in the North Atlantic. Our modelling study suggests that stalagmite records from Bunker Cave are representative for large-scale teleconnections and can be used to obtain information about the North Atlantic and its decadal variability.

Lens-Aided Multi-Angle Spectroscopy (LAMAS) Reveals Small-Scale Outflow Structure in Quasars

Science.gov (United States)

Green, Paul J.

2006-06-01

Spectral differences between lensed quasar image components are common. Since lensing is intrinsically achromatic, these differences are typically explained as the effect of either microlensing, or as light path time delays sampling intrinsic quasar spectral variability. Here we advance a novel third hypothesis: some spectral differences are due to small line-of-sight differences through quasar disk wind outflows. In particular, we propose that variable spectral differences seen only in component A of the widest separation lens SDSS J1004+4112 are due to differential absorption along the sight lines. The absorber properties required by this hypothesis are akin to known broad absorption line (BAL) outflows but must have a broader, smoother velocity profile. We interpret the observed C IV emission-line variability as further evidence for spatial fine structure transverse to the line of sight. Since outflows are likely to be rotating, such absorber fine structure can consistently explain some of the UV and X-ray variability seen in AGNs. The implications are many: (1) Spectroscopic differences in other lensed objects may be due to this ``lens-aided multi-angle spectroscopy'' (LAMAS). (2) Outflows have fine structure on size scales of arcseconds, as seen from the nucleus. (3) Assuming either broad absorption line region sizes proposed in recent wind models, or typically assumed continuum emission region sizes, LAMAS and/or variability provide broadly consistent absorber size scale estimates of ~1015 cm. (4) Very broad smooth absorption may be ubiquitous in quasar spectra, even when no obvious troughs are seen.
A multi-scale, multi-disciplinary approach for assessing the technological, economic and environmental performance of bio-based chemicals.

Science.gov (United States)

Herrgård, Markus; Sukumara, Sumesh; Campodonico, Miguel; Zhuang, Kai

2015-12-01

In recent years, bio-based chemicals have gained interest as a renewable alternative to petrochemicals. However, there is a significant need to assess the technological, biological, economic and environmental feasibility of bio-based chemicals, particularly during the early research phase. Recently, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain and the de novo prediction of metabolic pathways connecting existing host metabolism to desirable chemical products. This multi-scale, multi-disciplinary framework for quantitative assessment of bio-based chemicals will play a vital role in supporting engineering, strategy and policy decisions as we progress towards a sustainable chemical industry. © 2015 Authors; published by Portland Press Limited.
Multi-scale evaluations of submarine groundwater discharge

Directory of Open Access Journals (Sweden)

M. Taniguchi

2015-03-01

Full Text Available Multi-scale evaluations of submarine groundwater discharge (SGD have been made in Saijo, Ehime Prefecture, Shikoku Island, Japan, by using seepage meters for point scale, 222Rn tracer for point and coastal scales, and a numerical groundwater model (SEAWAT for coastal and basin scales. Daily basis temporal changes in SGD are evaluated by continuous seepage meter and 222Rn mooring measurements, and depend on sea level changes. Spatial evaluations of SGD were also made by 222Rn along the coast in July 2010 and November 2011. The area with larger 222Rn concentration during both seasons agreed well with the area with larger SGD calculated by 3D groundwater numerical simulations.
Heat and mass transfer intensification and shape optimization a multi-scale approach

CERN Document Server

2013-01-01

Is the heat and mass transfer intensification defined as a new paradigm of process engineering, or is it just a common and old idea, renamed and given the current taste? Where might intensification occur? How to achieve intensification? How the shape optimization of thermal and fluidic devices leads to intensified heat and mass transfers? To answer these questions, Heat & Mass Transfer Intensification and Shape Optimization: A Multi-scale Approach clarifies the definition of the intensification by highlighting the potential role of the multi-scale structures, the specific interfacial area, the distribution of driving force, the modes of energy supply and the temporal aspects of processes. A reflection on the methods of process intensification or heat and mass transfer enhancement in multi-scale structures is provided, including porous media, heat exchangers, fluid distributors, mixers and reactors. A multi-scale approach to achieve intensification and shape optimization is developed and clearly expla...
Restoring Natural Streamflow Variability by Modifying Multi-purpose Reservoir Operation

Science.gov (United States)

Shiau, J.

2010-12-01

Multi-purpose reservoirs typically provide benefits of water supply, hydroelectric power, and flood mitigation. Hydroelectric power generations generally do not consume water. However, temporal distribution of downstream flows is highly changed due to hydro-peaking effects. Associated with offstream diversion of water supplies for municipal, industrial, and agricultural requirements, natural streamflow characteristics of magnitude, duration, frequency, timing, and rate of change is significantly altered by multi-purpose reservoir operation. Natural flow regime has long been recognized a master factor for ecosystem health and biodiversity. Restoration of altered flow regime caused by multi-purpose reservoir operation is the main objective of this study. This study presents an optimization framework that modifying reservoir operation to seeking balance between human and environmental needs. The methodology presented in this study is applied to the Feitsui Reservoir, located in northern Taiwan, with main purpose of providing stable water-supply and auxiliary purpose of electricity generation and flood-peak attenuation. Reservoir releases are dominated by two decision variables, i.e., duration of water releases for each day and percentage of daily required releases within the duration. The current releasing policy of the Feitsui Reservoir releases water for water-supply and hydropower purposes during 8:00 am to 16:00 pm each day and no environmental flows releases. Although greater power generation is obtained by 100% releases distributed within 8-hour period, severe temporal alteration of streamflow is observed downstream of the reservoir. Modifying reservoir operation by relaxing these two variables and reserve certain ratio of streamflow as environmental flow to maintain downstream natural variability. The optimal reservoir releasing policy is searched by the multi-criterion decision making technique for considering reservoir performance in terms of shortage ratio
Multi-scale Modelling of Segmentation

DEFF Research Database (Denmark)

Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri

2016-01-01

pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary......While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects...
visPIG--a web tool for producing multi-region, multi-track, multi-scale plots of genetic data.

Directory of Open Access Journals (Sweden)

Matthew Scales

Full Text Available We present VISual Plotting Interface for Genetics (visPIG; http://vispig.icr.ac.uk, a web application to produce multi-track, multi-scale, multi-region plots of genetic data. visPIG has been designed to allow users not well versed with mathematical software packages and/or programming languages such as R, Matlab®, Python, etc., to integrate data from multiple sources for interpretation and to easily create publication-ready figures. While web tools such as the UCSC Genome Browser or the WashU Epigenome Browser allow custom data uploads, such tools are primarily designed for data exploration. This is also true for the desktop-run Integrative Genomics Viewer (IGV. Other locally run data visualisation software such as Circos require significant computer skills of the user. The visPIG web application is a menu-based interface that allows users to upload custom data tracks and set track-specific parameters. Figures can be downloaded as PDF or PNG files. For sensitive data, the underlying R code can also be downloaded and run locally. visPIG is multi-track: it can display many different data types (e.g association, functional annotation, intensity, interaction, heat map data,…. It also allows annotation of genes and other custom features in the plotted region(s. Data tracks can be plotted individually or on a single figure. visPIG is multi-region: it supports plotting multiple regions, be they kilo- or megabases apart or even on different chromosomes. Finally, visPIG is multi-scale: a sub-region of particular interest can be 'zoomed' in. We describe the various features of visPIG and illustrate its utility with examples. visPIG is freely available through http://vispig.icr.ac.uk under a GNU General Public License (GPLv3.
Research on climate change and variability at the Ab dus Salam International Centre for Theoretical Physics

International Nuclear Information System (INIS)

Giorgi, F.; Molteni, F.

2002-01-01

The Physics of Weather and Climate Section at the Abdus Salam International Centre for Theoretical Physics, established in 1998, is currently performing research on different aspects of climate variability, dealing with both natural and anthropogenic aspects of climate changes. In addition to performing diagnostic work on multi-decadal observational datasets and climate simulations carried out in major research centres, the PWC section has been developing its own climate modeling capability, which is focused on three main areas: a) modeling of regional climate change; b) seasonal forecasting at global and regional scale; c) development of simplified models of the general circulation. On topic a), research on different aspects of anthropogenic climate change is being carried out using the Regional Climate (RegCM) developed by Giorgi and collaborators at the National Centre for Atmospheric Research. Time-slice experiments with a high-resolution atmospheric GCM, comparing current climate conditions with future climate scenarios in selected decades, are also planned for the near future. On topic b), a strategy based on ensembles of high-resolution simulations with atmospheric GCM's, using sea surface temperature anomalies predicted by lower-resolution coupled models from other institutions, is currently under experimentation. A one-way nesting of RegCM into the GCM simulations will also be tested. On item c), a 5-layer atmospheric GCM with simplified physical parameterizations has been developed. This model has a very small computational cost compared with state-of-the-art GCMs, and is suitable for studies of natural climate variability on inter-decadal and intercentennial time scales. It is planned to couple this model to simplified ocean models of different complexity, from a simple, static mixed layer model, to simplified models of the tropical Pacific circulation suited to the simulation of the El Nino phenomenon. A joint project with the IAEA-MEL Laboratory in
Precipitation variability assessment of northeast China: Songhua ...

Indian Academy of Sciences (India)

Variability in precipitation is critical for the management of water resources. ... applied on precipitation data on a monthly, seasonally, annually, decade scale and the number of rainy ... 2015). As a result, such irregularities in precipitation,. i.e., droughts and floods can affect the ... (January–December), years and decades.
A model for AGN variability on multiple time-scales

Science.gov (United States)

Sartori, Lia F.; Schawinski, Kevin; Trakhtenbrot, Benny; Caplar, Neven; Treister, Ezequiel; Koss, Michael J.; Urry, C. Megan; Zhang, C. E.

2018-05-01

We present a framework to link and describe active galactic nuclei (AGN) variability on a wide range of time-scales, from days to billions of years. In particular, we concentrate on the AGN variability features related to changes in black hole fuelling and accretion rate. In our framework, the variability features observed in different AGN at different time-scales may be explained as realisations of the same underlying statistical properties. In this context, we propose a model to simulate the evolution of AGN light curves with time based on the probability density function (PDF) and power spectral density (PSD) of the Eddington ratio (L/LEdd) distribution. Motivated by general galaxy population properties, we propose that the PDF may be inspired by the L/LEdd distribution function (ERDF), and that a single (or limited number of) ERDF+PSD set may explain all observed variability features. After outlining the framework and the model, we compile a set of variability measurements in terms of structure function (SF) and magnitude difference. We then combine the variability measurements on a SF plot ranging from days to Gyr. The proposed framework enables constraints on the underlying PSD and the ability to link AGN variability on different time-scales, therefore providing new insights into AGN variability and black hole growth phenomena.
Multi-resolution and multi-scale simulation of the thermal hydraulics in fast neutron reactor assemblies

International Nuclear Information System (INIS)

Angeli, P.-E.

2011-01-01

The present work is devoted to a multi-scale numerical simulation of an assembly of fast neutron reactor. In spite of the rapid growth of the computer power, the fine complete CFD of a such system remains out of reach in a context of research and development. After the determination of the thermalhydraulic behaviour of the assembly at the macroscopic scale, we propose to carry out a local reconstruction of the fine scale information. The complete approach will require a much lower CPU time than the CFD of the entire structure. The macro-scale description is obtained using either the volume averaging formalism in porous media, or an alternative modeling historically developed for the study of fast neutron reactor assemblies. It provides some information used as constraint of a down-scaling problem, through a penalization technique of the local conservation equations. This problem lean on the periodic nature of the structure by integrating periodic boundary conditions for the required microscale fields or their spatial deviation. After validating the methodologies on some model applications, we undertake to perform them on 'industrial' configurations which demonstrate the viability of this multi-scale approach. (author) [fr
Multi Scale Models for Flexure Deformation in Sheet Metal Forming

Directory of Open Access Journals (Sweden)

Di Pasquale Edmondo

2016-01-01

Full Text Available This paper presents the application of multi scale techniques to the simulation of sheet metal forming using the one-step method. When a blank flows over the die radius, it undergoes a complex cycle of bending and unbending. First, we describe an original model for the prediction of residual plastic deformation and stresses in the blank section. This model, working on a scale about one hundred times smaller than the element size, has been implemented in SIMEX, one-step sheet metal forming simulation code. The utilisation of this multi-scale modeling technique improves greatly the accuracy of the solution. Finally, we discuss the implications of this analysis on the prediction of springback in metal forming.
Quantifying multi-dimensional attributes of human activities at various geographic scales based on smartphone tracking.

Science.gov (United States)

Zhou, Xiaolu; Li, Dongying

2018-05-09

Advancement in location-aware technologies, and information and communication technology in the past decades has furthered our knowledge of the interaction between human activities and the built environment. An increasing number of studies have collected data regarding individual activities to better understand how the environment shapes human behavior. Despite this growing interest, some challenges exist in collecting and processing individual's activity data, e.g., capturing people's precise environmental contexts and analyzing data at multiple spatial scales. In this study, we propose and implement an innovative system that integrates smartphone-based step tracking with an app and the sequential tile scan techniques to collect and process activity data. We apply the OpenStreetMap tile system to aggregate positioning points at various scales. We also propose duration, step and probability surfaces to quantify the multi-dimensional attributes of activities. Results show that, by running the app in the background, smartphones can measure multi-dimensional attributes of human activities, including space, duration, step, and location uncertainty at various spatial scales. By coordinating Global Positioning System (GPS) sensor with accelerometer sensor, this app can save battery which otherwise would be drained by GPS sensor quickly. Based on a test dataset, we were able to detect the recreational center and sports center as the space where the user was most active, among other places visited. The methods provide techniques to address key issues in analyzing human activity data. The system can support future studies on behavioral and health consequences related to individual's environmental exposure.
Multi-scale modeling of dispersed gas-liquid two-phase flow

NARCIS (Netherlands)

Deen, N.G.; Sint Annaland, van M.; Kuipers, J.A.M.

2004-01-01

In this work the concept of multi-scale modeling is demonstrated. The idea of this approach is to use different levels of modeling, each developed to study phenomena at a certain length scale. Information obtained at the level of small length scales can be used to provide closure information at the
Variability of sea ice deformation rates in the Arctic and their relationship with basin-scale wind forcing

Directory of Open Access Journals (Sweden)

A. Herman

2012-12-01

Full Text Available The temporal variability of the moments of probability distribution functions (pdfs of total sea ice deformation rates in the Arctic is analyzed in the context of the basin-scale wind forcing acting on the ice. The pdfs are estimated for 594 satellite-derived sea ice deformation maps from 11 winter seasons between 1996/1997 and 2007/2008, provided by the RADARSAT Geophysical Processor System. The temporal scale analyzed equals 3 days. The moments of the pdfs, calculated for a range of spatial scales (12.5–900 km, have two dominating components of variability: a seasonal cycle, with deformation rates decreasing throughout winter towards a minimum in March; and a short-term, synoptic variability, strongly correlated with the area-averaged magnitude of the wind stress over the Arctic, estimated based on the NCEP-DOE Reanalysis-2 data (correlation coefficient of 0.71 for the mean deformation rate. Due to scaling properties of the moments, logarithms of higher moments are strongly correlated with the wind stress as well. Exceptions are observed only at small spatial scales, as a result of extreme deformation events, not directly associated with large-scale wind forcing. By repeating the analysis within regions of different sizes and locations, we show that the wind–ice deformation correlation is largest at the basin scale and decreases with decreasing size of the area of study. Finally, we suggest that a positive trend in seasonally averaged correlation between sea ice deformation rates and the wind forcing, present in the analyzed data, may be related to an observed decrease in the multi-year ice area in the Arctic, indicating possibly even stronger correlations in the future.
Multi-scale approach for predicting fish species distributions across coral reef seascapes.

Directory of Open Access Journals (Sweden)

Simon J Pittman

Full Text Available Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5-300 m radii surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT and Maximum Entropy Species Distribution Modelling (MaxEnt. The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided 'outstanding' model predictions (AUC = >0.9 for three of five fish species. MaxEnt provided 'outstanding' model predictions for two of five species, with the remaining three models considered 'excellent' (AUC = 0.8-0.9. In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy than BRT (68% map accuracy. We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support
Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

International Nuclear Information System (INIS)

Cruz, Roberto de la; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-01-01

of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth. - Highlights: • A hybrid method for stochastic multi-scale models of cells populations that extends existing hybrid methods for reaction–diffusion system. • Our analysis unveils non-trivial macroscopic effects triggered by noise at the level of structuring variables. • Our hybrid method hugely speeds up age-structured SSA simulations while preserving stochastic effects.
Morphology Dependent Flow Stress in Nickel-Based Superalloys in the Multi-Scale Crystal Plasticity Framework

Directory of Open Access Journals (Sweden)

Shahriyar Keshavarz

2017-11-01

Full Text Available This paper develops a framework to obtain the flow stress of nickel-based superalloys as a function of γ-γ’ morphology. The yield strength is a major factor in the design of these alloys. This work provides additional effects of γ’ morphology in the design scope that has been adopted for the model developed by authors. In general, the two-phase γ-γ’ morphology in nickel-based superalloys can be divided into three variables including γ’ shape, γ’ volume fraction and γ’ size in the sub-grain microstructure. In order to obtain the flow stress, non-Schmid crystal plasticity constitutive models at two length scales are employed and bridged through a homogenized multi-scale framework. The multi-scale framework includes two sub-grain and homogenized grain scales. For the sub-grain scale, a size-dependent, dislocation-density-based finite element model (FEM of the representative volume element (RVE with explicit depiction of the γ-γ’ morphology is developed as a building block for the homogenization. For the next scale, an activation-energy-based crystal plasticity model is developed for the homogenized single crystal of Ni-based superalloys. The constitutive models address the thermo-mechanical behavior of nickel-based superalloys for a large temperature range and include orientation dependencies and tension-compression asymmetry. This homogenized model is used to obtain the morphology dependence on the flow stress in nickel-based superalloys and can significantly expedite crystal plasticity FE simulations in polycrystalline microstructures, as well as higher scale FE models in order to cast and design superalloys.
Coupled decadal variability of the North Atlantic Oscillation, regional rainfall and karst spring discharges in the Campania region (southern Italy

Directory of Open Access Journals (Sweden)

P. De Vita

2012-05-01

different European countries and Mediterranean areas, the results of this study allow for the establishment of a link between a large-scale atmospheric cycle and the groundwater recharge of carbonate karst aquifers. Consequently, the winter NAO index could also be considered as a proxy to forecast the decadal variability of groundwater flow in Mediterranean karst areas.
Advanced computational workflow for the multi-scale modeling of the bone metabolic processes.

Science.gov (United States)

Dao, Tien Tuan

2017-06-01

Multi-scale modeling of the musculoskeletal system plays an essential role in the deep understanding of complex mechanisms underlying the biological phenomena and processes such as bone metabolic processes. Current multi-scale models suffer from the isolation of sub-models at each anatomical scale. The objective of this present work was to develop a new fully integrated computational workflow for simulating bone metabolic processes at multi-scale levels. Organ-level model employs multi-body dynamics to estimate body boundary and loading conditions from body kinematics. Tissue-level model uses finite element method to estimate the tissue deformation and mechanical loading under body loading conditions. Finally, cell-level model includes bone remodeling mechanism through an agent-based simulation under tissue loading. A case study on the bone remodeling process located on the human jaw was performed and presented. The developed multi-scale model of the human jaw was validated using the literature-based data at each anatomical level. Simulation outcomes fall within the literature-based ranges of values for estimated muscle force, tissue loading and cell dynamics during bone remodeling process. This study opens perspectives for accurately simulating bone metabolic processes using a fully integrated computational workflow leading to a better understanding of the musculoskeletal system function from multiple length scales as well as to provide new informative data for clinical decision support and industrial applications.

Multi-scale modeling strategies in materials science—The ...

Indian Academy of Sciences (India)

Unknown

Multi-scale models; quasicontinuum method; finite elements. 1. Introduction ... boundary with external stresses, and the interaction of a lattice dislocation with a grain ..... mum value of se over the elements that touch node α. The acceleration of ...
Long-term Observations of Intense Precipitation Small-scale Spatial Variability in a Semi-arid Catchment

Science.gov (United States)

Cropp, E. L.; Hazenberg, P.; Castro, C. L.; Demaria, E. M.

2017-12-01

In the southwestern US, the summertime North American Monsoon (NAM) provides about 60% of the region's annual precipitation. Recent research using high-resolution atmospheric model simulations and retrospective predictions has shown that since the 1950's, and more specifically in the last few decades, the mean daily precipitation in the southwestern U.S. during the NAM has followed a decreasing trend. Furthermore, days with more extreme precipitation have intensified. The current work focuses the impact of these long-term changes on the observed small-scale spatial variability of intense precipitation. Since limited long-term high-resolution observational data exist to support such climatological-induced spatial changes in precipitation frequency and intensity, the current work utilizes observations from the USDA-ARS Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Within this 150 km^2 catchment over 90 rain gauges have been installed since the 1950s, measuring at sub-hourly resolution. We have applied geospatial analyses and the kriging interpolation technique to identify long-term changes in the spatial and temporal correlation and anisotropy of intense precipitation. The observed results will be compared with the previously model simulated results, as well as related to large-scale variations in climate patterns, such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO).
Variable cycle control model for intersection based on multi-source information

Science.gov (United States)

Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

2018-05-01

In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.
Using synchronization in multi-model ensembles to improve prediction

Science.gov (United States)

Hiemstra, P.; Selten, F.

2012-04-01

In recent decades, many climate models have been developed to understand and predict the behavior of the Earth's climate system. Although these models are all based on the same basic physical principles, they still show different behavior. This is for example caused by the choice of how to parametrize sub-grid scale processes. One method to combine these imperfect models, is to run a multi-model ensemble. The models are given identical initial conditions and are integrated forward in time. A multi-model estimate can for example be a weighted mean of the ensemble members. We propose to go a step further, and try to obtain synchronization between the imperfect models by connecting the multi-model ensemble, and exchanging information. The combined multi-model ensemble is also known as a supermodel. The supermodel has learned from observations how to optimally exchange information between the ensemble members. In this study we focused on the density and formulation of the onnections within the supermodel. The main question was whether we could obtain syn-chronization between two climate models when connecting only a subset of their state spaces. Limiting the connected subspace has two advantages: 1) it limits the transfer of data (bytes) between the ensemble, which can be a limiting factor in large scale climate models, and 2) learning the optimal connection strategy from observations is easier. To answer the research question, we connected two identical quasi-geostrohic (QG) atmospheric models to each other, where the model have different initial conditions. The QG model is a qualitatively realistic simulation of the winter flow on the Northern hemisphere, has three layers and uses a spectral imple-mentation. We connected the models in the original spherical harmonical state space, and in linear combinations of these spherical harmonics, i.e. Empirical Orthogonal Functions (EOFs). We show that when connecting through spherical harmonics, we only need to connect 28% of
Plant trait detection with multi-scale spectrometry

Science.gov (United States)

Gamon, J. A.; Wang, R.

2017-12-01

Proximal and remote sensing using imaging spectrometry offers new opportunities for detecting plant traits, with benefits for phenotyping, productivity estimation, stress detection, and biodiversity studies. Using proximal and airborne spectrometry, we evaluated variation in plant optical properties at various spatial and spectral scales with the goal of identifying optimal scales for distinguishing plant traits related to photosynthetic function. Using directed approaches based on physiological vegetation indices, and statistical approaches based on spectral information content, we explored alternate ways of distinguishing plant traits with imaging spectrometry. With both leaf traits and canopy structure contributing to the signals, results exhibit a strong scale dependence. Our results demonstrate the benefits of multi-scale experimental approaches within a clear conceptual framework when applying remote sensing methods to plant trait detection for phenotyping, productivity, and biodiversity studies.
Multi-scale semi-ideal magnetohydrodynamics of a tokamak plasma

International Nuclear Information System (INIS)

Bazdenkov, S.; Sato, Tetsuya; Watanabe, Kunihiko.

1995-09-01

An analytical model of fast spatial flattening of the toroidal current density and q-profile at the nonlinear stage of (m = 1/n = 1) kink instability of a tokamak plasma is presented. The flattening is shown to be an essentially multi-scale phenomenon which is characterized by, at least, two magnetic Reynolds numbers. The ordinary one, R m , is related with a characteristic radial scale-length, while the other, R m * , corresponds to a characteristic scale-length of plasma inhomogeneity along the magnetic field line. In a highly conducting plasma inside the q = 1 magnetic surface, where q value does not much differ from unity, plasma evolution is governed by a multi-scale non-ideal dynamics characterized by two well-separated magnetic Reynolds numbers, R m and R m * ≡ (1 - q) R m , where R m * - O(1) and R m >> 1. This dynamics consistently explains two seemingly contradictory features recently observed in a numerical simulation [Watanabe et al., 1995]: i) the current profile (q-profile) is flattened in the magnetohydrodynamic time scale within the q = 1 rational surface; ii) the magnetic surface keeps its initial circular shape during this evolution. (author)
Geoelectrical Measurement of Multi-Scale Mass Transfer Parameters

Energy Technology Data Exchange (ETDEWEB)

Day-Lewis, Frederick; Singha, Kamini; Haggerty, Roy; Johnson, Tim; Binley, Andrew; Lane, John

2014-01-16

measure mass transfer in-situ and estimate multi-scale and spatially variable mass-transfer parameters. The current lack of such techniques results in large parameter uncertainty, which in turn translates into enormous prediction uncertainty and cost to DOE. In this project, we considered three hydrogeophysical approaches for providing information about mass-transfer parameters: (1) the combination of electrical-resistivity tomography (ERT) and ionic tracer experiments to explore rates of exchange and relative mobile and immobile porosities; (2) complex resistivity (CR) measurements to infer the distribution of diffusive length scales active in a porous medium; and (3) nuclear magnetic resonance (NMR) to estimate mobile and immobile porosity.
Variability in population abundance is associated with thresholds between scaling regimes

Science.gov (United States)

Wardwell, D.; Allen, Craig R.

2009-01-01

Discontinuous structure in landscapes may result in discontinuous, aggregated species body-mass patterns, reflecting the scales of structure available to animal communities within a landscape. The edges of these body-mass aggregations reflect transitions between available scales of landscape structure. Such transitions, or scale breaks, are theoretically associated with increased biological variability. We hypothesized that variability in population abundance is greater in animal species near the edge of body-mass aggregations than it is in species that are situated in the interior of body-mass aggregations. We tested this hypothesis by examining both temporal and spatial variability in the abundance of species in the bird community of the Florida Everglades sub-ecoregion, USA. Analyses of both temporal and spatial variability in population abundance supported our hypothesis. Our results indicate that variability within complex systems may be non-random, and is heightened where transitions in scales of process and structure occur. This is the first explicit test of the hypothetical relationship between increased population variability and scale breaks. ?? 2009 by the author(s).
Orbit-related sea level errors for TOPEX altimetry at seasonal to decadal timescales

Science.gov (United States)

Esselborn, Saskia; Rudenko, Sergei; Schöne, Tilo

2018-03-01

Interannual to decadal sea level trends are indicators of climate variability and change. A major source of global and regional sea level data is satellite radar altimetry, which relies on precise knowledge of the satellite's orbit. Here, we assess the error budget of the radial orbit component for the TOPEX/Poseidon mission for the period 1993 to 2004 from a set of different orbit solutions. The errors for seasonal, interannual (5-year), and decadal periods are estimated on global and regional scales based on radial orbit differences from three state-of-the-art orbit solutions provided by different research teams: the German Research Centre for Geosciences (GFZ), the Groupe de Recherche de Géodésie Spatiale (GRGS), and the Goddard Space Flight Center (GSFC). The global mean sea level error related to orbit uncertainties is of the order of 1 mm (8 % of the global mean sea level variability) with negligible contributions on the annual and decadal timescales. In contrast, the orbit-related error of the interannual trend is 0.1 mm yr-1 (27 % of the corresponding sea level variability) and might hamper the estimation of an acceleration of the global mean sea level rise. For regional scales, the gridded orbit-related error is up to 11 mm, and for about half the ocean the orbit error accounts for at least 10 % of the observed sea level variability. The seasonal orbit error amounts to 10 % of the observed seasonal sea level signal in the Southern Ocean. At interannual and decadal timescales, the orbit-related trend uncertainties reach regionally more than 1 mm yr-1. The interannual trend errors account for 10 % of the observed sea level signal in the tropical Atlantic and the south-eastern Pacific. For decadal scales, the orbit-related trend errors are prominent in a several regions including the South Atlantic, western North Atlantic, central Pacific, South Australian Basin, and the Mediterranean Sea. Based on a set of test orbits calculated at GFZ, the sources of the
Orbit-related sea level errors for TOPEX altimetry at seasonal to decadal timescales

Directory of Open Access Journals (Sweden)

S. Esselborn

2018-03-01

Full Text Available Interannual to decadal sea level trends are indicators of climate variability and change. A major source of global and regional sea level data is satellite radar altimetry, which relies on precise knowledge of the satellite's orbit. Here, we assess the error budget of the radial orbit component for the TOPEX/Poseidon mission for the period 1993 to 2004 from a set of different orbit solutions. The errors for seasonal, interannual (5-year, and decadal periods are estimated on global and regional scales based on radial orbit differences from three state-of-the-art orbit solutions provided by different research teams: the German Research Centre for Geosciences (GFZ, the Groupe de Recherche de Géodésie Spatiale (GRGS, and the Goddard Space Flight Center (GSFC. The global mean sea level error related to orbit uncertainties is of the order of 1 mm (8 % of the global mean sea level variability with negligible contributions on the annual and decadal timescales. In contrast, the orbit-related error of the interannual trend is 0.1 mm yr−1 (27 % of the corresponding sea level variability and might hamper the estimation of an acceleration of the global mean sea level rise. For regional scales, the gridded orbit-related error is up to 11 mm, and for about half the ocean the orbit error accounts for at least 10 % of the observed sea level variability. The seasonal orbit error amounts to 10 % of the observed seasonal sea level signal in the Southern Ocean. At interannual and decadal timescales, the orbit-related trend uncertainties reach regionally more than 1 mm yr−1. The interannual trend errors account for 10 % of the observed sea level signal in the tropical Atlantic and the south-eastern Pacific. For decadal scales, the orbit-related trend errors are prominent in a several regions including the South Atlantic, western North Atlantic, central Pacific, South Australian Basin, and the Mediterranean Sea. Based on a set of test
Multi-scale structural community organisation of the human genome.

Science.gov (United States)

Boulos, Rasha E; Tremblay, Nicolas; Arneodo, Alain; Borgnat, Pierre; Audit, Benjamin

2017-04-11

Structural interaction frequency matrices between all genome loci are now experimentally achievable thanks to high-throughput chromosome conformation capture technologies. This ensues a new methodological challenge for computational biology which consists in objectively extracting from these data the structural motifs characteristic of genome organisation. We deployed the fast multi-scale community mining algorithm based on spectral graph wavelets to characterise the networks of intra-chromosomal interactions in human cell lines. We observed that there exist structural domains of all sizes up to chromosome length and demonstrated that the set of structural communities forms a hierarchy of chromosome segments. Hence, at all scales, chromosome folding predominantly involves interactions between neighbouring sites rather than the formation of links between distant loci. Multi-scale structural decomposition of human chromosomes provides an original framework to question structural organisation and its relationship to functional regulation across the scales. By construction the proposed methodology is independent of the precise assembly of the reference genome and is thus directly applicable to genomes whose assembly is not fully determined.
Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

Science.gov (United States)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2017-09-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.
Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

Science.gov (United States)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2018-06-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.
Multi-symplectic variational integrators for nonlinear Schrödinger equations with variable coefficients

International Nuclear Information System (INIS)

Liao Cui-Cui; Cui Jin-Chao; Liang Jiu-Zhen; Ding Xiao-Hua

2016-01-01

In this paper, we propose a variational integrator for nonlinear Schrödinger equations with variable coefficients. It is shown that our variational integrator is naturally multi-symplectic. The discrete multi-symplectic structure of the integrator is presented by a multi-symplectic form formula that can be derived from the discrete Lagrangian boundary function. As two examples of nonlinear Schrödinger equations with variable coefficients, cubic nonlinear Schrödinger equations and Gross–Pitaevskii equations are extensively studied by the proposed integrator. Our numerical simulations demonstrate that the integrator is capable of preserving the mass, momentum, and energy conservation during time evolutions. Convergence tests are presented to verify that our integrator has second-order accuracy both in time and space. (paper)
A multi-resolution analysis of lidar-DTMs to identify geomorphic processes from characteristic topographic length scales

Science.gov (United States)

Sangireddy, H.; Passalacqua, P.; Stark, C. P.

2013-12-01

Characteristic length scales are often present in topography, and they reflect the driving geomorphic processes. The wide availability of high resolution lidar Digital Terrain Models (DTMs) allows us to measure such characteristic scales, but new methods of topographic analysis are needed in order to do so. Here, we explore how transitions in probability distributions (pdfs) of topographic variables such as (log(area/slope)), defined as topoindex by Beven and Kirkby[1979], can be measured by Multi-Resolution Analysis (MRA) of lidar DTMs [Stark and Stark, 2001; Sangireddy et al.,2012] and used to infer dominant geomorphic processes such as non-linear diffusion and critical shear. We show this correlation between dominant geomorphic processes to characteristic length scales by comparing results from a landscape evolution model to natural landscapes. The landscape evolution model MARSSIM Howard[1994] includes components for modeling rock weathering, mass wasting by non-linear creep, detachment-limited channel erosion, and bedload sediment transport. We use MARSSIM to simulate steady state landscapes for a range of hillslope diffusivity and critical shear stresses. Using the MRA approach, we estimate modal values and inter-quartile ranges of slope, curvature, and topoindex as a function of resolution. We also construct pdfs at each resolution and identify and extract characteristic scale breaks. Following the approach of Tucker et al.,[2001], we measure the average length to channel from ridges, within the GeoNet framework developed by Passalacqua et al.,[2010] and compute pdfs for hillslope lengths at each scale defined in the MRA. We compare the hillslope diffusivity used in MARSSIM against inter-quartile ranges of topoindex and hillslope length scales, and observe power law relationships between the compared variables for simulated landscapes at steady state. We plot similar measures for natural landscapes and are able to qualitatively infer the dominant geomorphic
North-South precipitation patterns in western North America on interannual-to-decadal timescales

Science.gov (United States)

Dettinger, M.D.; Cayan, D.R.; Diaz, Henry F.; Meko, D.M.

1998-01-01

The overall amount of precipitation deposited along the West Coast and western cordillera of North America from 25??to 55??N varies from year to year, and superimposed on this domain-average variability are varying north-south contrasts on timescales from at least interannual to interdecadal. In order to better understand the north-south precipitation contrasts, their interannual and decadal variations are studied in terms of how much they affect overall precipitation amounts and how they are related to large-scale climatic patterns. Spatial empirical orthogonal functions (EOFs) and spatial moments (domain average, central latitude, and latitudinal spread) of zonally averaged precipitation anomalies along the westernmost parts of North America are analyzed, and each is correlated with global sea level pressure (SLP) and sea surface temperature series, on interannual (defined here as 3-7 yr) and decadal (>7 yr) timescales. The interannual band considered here corresponds to timescales that are particularly strong in tropical climate variations and thus is expected to contain much precipitation variability that is related to El Nino-Southern Oscillation; the decadal scale is defined so as to capture the whole range of long-term climatic variations affecting western North America. Zonal EOFs of the interannual and decadal filtered versions of the zonal-precipitation series are remarkably similar. At both timescales, two leading EOFs describe 1) a north-south seesaw of precipitation pivoting near 40??N and 2) variations in precipitation near 40??N, respectively. The amount of overall precipitation variability is only about 10% of the mean and is largely determined by precipitation variations around 40??-45??N and most consistently influenced by nearby circulation patterns; in this sense, domain-average precipitation is closely related to the second EOF. The central latitude and latitudinal spread of precipitation distributions are strongly influenced by precipitation
Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

Science.gov (United States)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to
Quantifying the increasing sensitivity of power systems to climate variability

Science.gov (United States)

Bloomfield, H. C.; Brayshaw, D. J.; Shaffrey, L. C.; Coker, P. J.; Thornton, H. E.

2016-12-01

Large quantities of weather-dependent renewable energy generation are expected in power systems under climate change mitigation policies, yet little attention has been given to the impact of long term climate variability. By combining state-of-the-art multi-decadal meteorological records with a parsimonious representation of a power system, this study characterises the impact of year-to-year climate variability on multiple aspects of the power system of Great Britain (including coal, gas and nuclear generation), demonstrating why multi-decadal approaches are necessary. All aspects of the example system are impacted by inter-annual climate variability, with the impacts being most pronounced for baseload generation. The impacts of inter-annual climate variability increase in a 2025 wind-power scenario, with a 4-fold increase in the inter-annual range of operating hours for baseload such as nuclear. The impacts on peak load and peaking-plant are comparably small. Less than 10 years of power supply and demand data are shown to be insufficient for providing robust power system planning guidance. This suggests renewable integration studies—widely used in policy, investment and system design—should adopt a more robust approach to climate characterisation.
Two Decades (almost) of Keck Observations of Io

Science.gov (United States)

De Pater, I.; Davies, A. G.; de Kleer, K.

2015-12-01

We have regularly observed Io with the 10-m Keck Telescope since 1998, initially using the speckle imaging technique, and switching to Adaptive Optics techniques when this became available in 2001. In this talk we will discuss several eruptions that we witnessed, and present 20-30 year timelines of thermal emission from Pele, Pillan, Janus Patera, Kanehekili Fluctus, and Loki Patera, updating timelines in recent publications [1, 2] with additional Keck adaptive optics data obtained between 2002 and 2015. These new timelines are the most comprehensive plots ever produced of the volcanic thermal emission variability for these or any other locations on Io, utilizing data from multiple ground- and space-based assets. Our continuing multi-decadal observing program forms the basis for charting the variability of Io's volcanic activity, of great importance for understanding the evolution of the Galilean satellite system, and with the expectation of new missions to the jovian system in the next decade. Acknowledgements: This research is in part supported by NSF grant AST-1313485 to UC Berkeley. AGD is supported by a grant from the NASA OPR Program. References: [1] Davies et al. (2012) Icarus, 221, 466-470. [2] Rathbun and Spencer (2010) Icarus, 209, 625-630.
Multi-scale Regions from Edge Fragments

DEFF Research Database (Denmark)

Kazmi, Wajahat; Andersen, Hans Jørgen

2014-01-01

In this article we introduce a novel method for detecting multi-scale salient regions around edges using a graph based image compression algorithm. Images are recursively decomposed into triangles arranged into a binary tree using linear interpolation. The entropy of any local region of the image......), their performance is comparable to SIFT (Lowe, 2004).We also show that when they are used together with MSERs (Matas et al., 2002), the performance of MSERs is boosted....

Temporal Changes in Forest Contexts at Multiple Extents: Three Decades of Fragmentation in the Gran Chaco (1979-2010), Central Argentina

Science.gov (United States)

Frate, Ludovico; Acosta, Alicia T. R.; Cabido, Marcelo; Hoyos, Laura; Carranza, Maria Laura

2015-01-01

The context in which a forest exists strongly influences its function and sustainability. Unveiling the multi-scale nature of forest fragmentation context is crucial to understand how human activities affect the spatial patterns of forests across a range of scales. However, this issue remains almost unexplored in subtropical ecosystems. In this study, we analyzed temporal changes (1979–2010) in forest contexts in the Argentinean dry Chaco at multiple extents. We classified forests over the last three decades based on forest context amount (P f) and structural connectivity (P ff), which were measured using a moving window approach fixed at eight different extents (from local, ~ 6 ha, to regional, ~ 8300 ha). Specific multi-scale forest context profiles (for the years 1979 and 2010) were defined by projecting P f vs. P ff mean values and were compared across spatial extents. The distributions of P f across scales were described by scalograms and their shapes over time were compared. The amount of agricultural land and rangelands across the scales were also analyzed. The dry Chaco has undergone an intensive process of fragmentation, resulting in a shift from landscapes dominated by forests with gaps of rangelands to landscapes where small forest patches are embedded in agricultural lands. Multi-scale fragmentation analysis depicted landscapes in which local exploitation, which perforates forest cover, occurs alongside extensive forest clearings, reducing forests to small and isolated patches surrounded by agricultural lands. In addition, the temporal diminution of P f’s variability along with the increment of the mean slope of the P f ‘s scalograms, indicate a simplification of the spatial pattern of forest over time. The observed changes have most likely been the result of the interplay between human activities and environmental constraints, which have shaped the spatial patterns of forests across scales. Based on our results, strategies for the conservation
Improved anomaly detection using multi-scale PLS and generalized likelihood ratio test

KAUST Repository

Madakyaru, Muddu

2017-02-16

Process monitoring has a central role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. In this paper, a statistical approach that exploit the advantages of multiscale PLS models (MSPLS) and those of a generalized likelihood ratio (GLR) test to better detect anomalies is proposed. Specifically, to consider the multivariate and multi-scale nature of process dynamics, a MSPLS algorithm combining PLS and wavelet analysis is used as modeling framework. Then, GLR hypothesis testing is applied using the uncorrelated residuals obtained from MSPLS model to improve the anomaly detection abilities of these latent variable based fault detection methods even further. Applications to a simulated distillation column data are used to evaluate the proposed MSPLS-GLR algorithm.
Improved anomaly detection using multi-scale PLS and generalized likelihood ratio test

KAUST Repository

Madakyaru, Muddu; Harrou, Fouzi; Sun, Ying

2017-01-01

Process monitoring has a central role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. In this paper, a statistical approach that exploit the advantages of multiscale PLS models (MSPLS) and those of a generalized likelihood ratio (GLR) test to better detect anomalies is proposed. Specifically, to consider the multivariate and multi-scale nature of process dynamics, a MSPLS algorithm combining PLS and wavelet analysis is used as modeling framework. Then, GLR hypothesis testing is applied using the uncorrelated residuals obtained from MSPLS model to improve the anomaly detection abilities of these latent variable based fault detection methods even further. Applications to a simulated distillation column data are used to evaluate the proposed MSPLS-GLR algorithm.
Magnetic Multi-Scale Mapping to Characterize Anthropogenic Targets

Science.gov (United States)

Le Maire, P.; Munschy, M.

2017-12-01

The discovery of buried anthropic objects on construction sites can cause delays and/or dangers for workers and for the public. Indeed, every year 500 tons of Unexploded-ordnance are discovered in France. Magnetic measurements are useful to localize magnetized objects. Moreover, it is the cheapest geophysical method which does not impact environment and which is relatively fast to perform. Fluxgate magnetometers (three components) are used to measure magnetic properties bellow the ground. These magnetic sensors are not absolute, so they need to be calibrated before the onset of the measurements. The advantage is that they allow magnetic compensation of the equipment attached to the sensor. So the choice of this kind sensor gives the opportunity to install the equipment aboard different magnetized supports: boat, quad bike, unmanned aerial vehicle, aircraft,... Indeed, this methodology permits to perform magnetic mapping with different scale and different elevation above ground level. An old French aerial military plant was chosen to perform this multi-scale approach. The advantage of the site is that it contains a lot of different targets with variable sizes and depth, e.g. buildings, unexploded-ordnances of the two world wars, trenches, pipes,… By comparison between the different magnetic anomaly maps at different elevations some of the geometric parameters of the magnetic sources can be characterized. The comparison between measured maps at different elevations and the prolonged map highlights the maximum distance for the target's detection (figure).
Simulated variability of the Atlantic meridional overturning circulation

Science.gov (United States)

Bentsen, M.; Drange, H.; Furevik, T.; Zhou, T.

To examine the multi-annual to decadal scale variability of the Atlantic Meridional Overturning Circulation (AMOC) we conducted a four-member ensemble with a daily reanalysis forced, medium-resolution global version of the isopycnic coordinate ocean model MICOM, and a 300-years integration with the fully coupled Bergen Climate Model (BCM). The simulations of the AMOC with both model systems yield a long-term mean value of 18 Sv and decadal variability with an amplitude of 1-3 Sv. The power spectrum of the inter-annual to decadal scale variability of the AMOC in BCM generally follows the theoretical red noise spectrum, with indications of increased power near the 20-years period. Comparison with observational proxy indices for the AMOC, e.g. the thickness of the Labrador Sea Water, the strength of the baroclinic gyre circulation in the North Atlantic Ocean, and the surface temperature anomalies along the mean path of the Gulf Stream, shows similar trends and phasing of the variability, indicating that the simulated AMOC variability is robust and real. Mixing indices have been constructed for the Labrador, the Irminger and the Greenland-Iceland-Norwegian (GIN) seas. While convective mixing in the Labrador and the GIN seas are in opposite phase, and linked to the NAO as observations suggest, the convective mixing in the Irminger Sea is in phase with or leads the Labrador Sea. Newly formed deep water is seen as a slow, anomalous cold and fresh, plume flowing southward along the western continental slope of the Atlantic Ocean, with a return flow of warm and saline water on the surface. In addition, fast-travelling topographically trapped waves propagate southward along the continental slope towards equator, where they go east and continue along the eastern rim of the Atlantic. For both types of experiments, the Northern Hemisphere sea level pressure and 2 m temperature anomaly patterns computed based on the difference between climate states with strong and weak AMOC
Multi-scale Mexican spotted owl (Strix occidentalis lucida) nest/roost habitat selection in Arizona and a comparison with single-scale modeling results

Science.gov (United States)

Brad C. Timm; Kevin McGarigal; Samuel A. Cushman; Joseph L. Ganey

2016-01-01

Efficacy of future habitat selection studies will benefit by taking a multi-scale approach. In addition to potentially providing increased explanatory power and predictive capacity, multi-scale habitat models enhance our understanding of the scales at which species respond to their environment, which is critical knowledge required to implement effective...
Diagnosing Disaster Resilience of Communities as Multi-scale Complex Socio-ecological Systems

Science.gov (United States)

Liu, Wei; Mochizuki, Junko; Keating, Adriana; Mechler, Reinhard; Williges, Keith; Hochrainer, Stefan

2014-05-01

Global environmental change, growing anthropogenic influence, and increasing globalisation of society have made it clear that disaster vulnerability and resilience of communities cannot be understood without knowledge on the broader social-ecological system in which they are embedded. We propose a framework for diagnosing community resilience to disasters, as a form of disturbance to social-ecological systems, with feedbacks from the local to the global scale. Inspired by iterative multi-scale analysis employed by Resilience Alliance, the related socio-ecological systems framework of Ostrom, and the sustainable livelihood framework, we developed a multi-tier framework for thinking of communities as multi-scale social-ecological systems and analyzing communities' disaster resilience and also general resilience. We highlight the cross-scale influences and feedbacks on communities that exist from lower (e.g., household) to higher (e.g., regional, national) scales. The conceptual framework is then applied to a real-world resilience assessment situation, to illustrate how key components of socio-ecological systems, including natural hazards, natural and man-made environment, and community capacities can be delineated and analyzed.
Multi-scale structural similarity index for motion detection

Directory of Open Access Journals (Sweden)

M. Abdel-Salam Nasr

2017-07-01

Full Text Available The most recent approach for measuring the image quality is the structural similarity index (SSI. This paper presents a novel algorithm based on the multi-scale structural similarity index for motion detection (MS-SSIM in videos. The MS-SSIM approach is based on modeling of image luminance, contrast and structure at multiple scales. The MS-SSIM has resulted in much better performance than the single scale SSI approach but at the cost of relatively lower processing speed. The major advantages of the presented algorithm are both: the higher detection accuracy and the quasi real-time processing speed.
Revisiting drought impact on tropical forest photosynthesis: a novel multi-scale integrated approach reveals new insights

Science.gov (United States)

Detto, M.; Wu, J.; Xu, X.; Serbin, S.; Rogers, A.

2017-12-01

A fundamental unanswered question for global change ecology is to determine the vulnerability of tropical forests to climate change, particularly with increasing intensity and frequency of drought events. This question, despite its apparent simplicity, remains difficult for earth system models to answer, and is controversial in remote sensing literature. Here, we leverage unique multi-scale remote sensing measurements (from leaf to crown) in conjunction with four-continuous-year (2013-2017) eddy covariance measurements of ecosystem carbon fluxes in a tropical forest in Panama to revisit this question. We hypothesize that drought impacts tropical forest photosynthesis through variation in abiotic drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with physiological traits that govern photosynthesis, and biotic variation in ecosystem photosynthetic capacity associated with changes in the traits themselves. Our study site, located in a seasonal tropical forest on Barro Colorado Island (BCI), Panama, experienced a significant drought in 2015. Local eddy covariance derived photosynthesis shows an abrupt increase during the drought year. Our specific goal here is to assess the relative impact of abiotic and biotic drivers of such photosynthesis response to interannual drought. To this goal, we derived abiotic drivers from eddy tower-based meteorological measurements. We will derive the biotic drivers using a recently developed leaf demography-ontogeny model, where ecosystem photosynthetic capacity can be described as the product of field measured, age-dependent leaf photosynthetic capacity and local tower-camera derived ecosystem-scale inter-annual variability in leaf age demography of the same time period (2013-2017). Lastly, we will use a process-based model to assess the separate and joint effects of abiotic and biotic drivers on eddy covariance derive photosynthetic interannual variability. Collectively, this novel multi-scale
Emergence of multi-scaling in fluid turbulence

Science.gov (United States)

Donzis, Diego; Yakhot, Victor

2017-11-01

We present new theoretical and numerical results on the transition to strong turbulence in an infinite fluid stirred by a Gaussian random force. The transition is defined as a first appearance of anomalous scaling of normalized moments of velocity derivatives (or dissipation rates) emerging from the low-Reynolds-number Gaussian background. It is shown that due to multi-scaling, strongly intermittent rare events can be quantitatively described in terms of an infinite number of different ``Reynolds numbers'' reflecting a multitude of anomalous scaling exponents. We found that anomalous scaling for high order moments emerges at very low Reynolds numbers implying that intense dissipative-range fluctuations are established at even lower Reynolds number than that required for an inertial range. Thus, our results suggest that information about inertial range dynamics can be obtained from dissipative scales even when the former does not exit. We discuss our further prediction that transition to fully anomalous turbulence disappears at Rλ < 3 . Support from NSF is acknowledged.
Precipitation variability increases in a warmer climate.

Science.gov (United States)

Pendergrass, Angeline G; Knutti, Reto; Lehner, Flavio; Deser, Clara; Sanderson, Benjamin M

2017-12-21

Understanding changes in precipitation variability is essential for a complete explanation of the hydrologic cycle's response to warming and its impacts. While changes in mean and extreme precipitation have been studied intensively, precipitation variability has received less attention, despite its theoretical and practical importance. Here, we show that precipitation variability in most climate models increases over a majority of global land area in response to warming (66% of land has a robust increase in variability of seasonal-mean precipitation). Comparing recent decades to RCP8.5 projections for the end of the 21 st century, we find that in the global, multi-model mean, precipitation variability increases 3-4% K -1 globally, 4-5% K -1 over land and 2-4% K -1 over ocean, and is remarkably robust on a range of timescales from daily to decadal. Precipitation variability increases by at least as much as mean precipitation and less than moisture and extreme precipitation for most models, regions, and timescales. We interpret this as being related to an increase in moisture which is partially mitigated by weakening circulation. We show that changes in observed daily variability in station data are consistent with increased variability.
High-resolution time-frequency representation of EEG data using multi-scale wavelets

Science.gov (United States)

Li, Yang; Cui, Wei-Gang; Luo, Mei-Lin; Li, Ke; Wang, Lina

2017-09-01

An efficient time-varying autoregressive (TVAR) modelling scheme that expands the time-varying parameters onto the multi-scale wavelet basis functions is presented for modelling nonstationary signals and with applications to time-frequency analysis (TFA) of electroencephalogram (EEG) signals. In the new parametric modelling framework, the time-dependent parameters of the TVAR model are locally represented by using a novel multi-scale wavelet decomposition scheme, which can allow the capability to capture the smooth trends as well as track the abrupt changes of time-varying parameters simultaneously. A forward orthogonal least square (FOLS) algorithm aided by mutual information criteria are then applied for sparse model term selection and parameter estimation. Two simulation examples illustrate that the performance of the proposed multi-scale wavelet basis functions outperforms the only single-scale wavelet basis functions or Kalman filter algorithm for many nonstationary processes. Furthermore, an application of the proposed method to a real EEG signal demonstrates the new approach can provide highly time-dependent spectral resolution capability.
The development and validation of an urbanicity scale in a multi-country study.

Science.gov (United States)

Novak, Nicole L; Allender, Steven; Scarborough, Peter; West, Douglas

2012-07-20

Although urban residence is consistently identified as one of the primary correlates of non-communicable disease in low- and middle-income countries, it is not clear why or how urban settings predispose individuals and populations to non-communicable disease (NCD), or how this relationship could be modified to slow the spread of NCD. The urban-rural dichotomy used in most population health research lacks the nuance and specificity necessary to understand the complex relationship between urbanicity and NCD risk. Previous studies have developed and validated quantitative tools to measure urbanicity continuously along several dimensions but all have been isolated to a single country. The purposes of this study were 1) To assess the feasibility and validity of a multi-country urbanicity scale; 2) To report some of the considerations that arise in applying such a scale in different countries; and, 3) To assess how this scale compares with previously validated scales of urbanicity. Household and community-level data from the Young Lives longitudinal study of childhood poverty in 59 communities in Ethiopia, India and Peru collected in 2006/2007 were used. Household-level data include parents' occupations and education level, household possessions and access to resources. Community-level data include population size, availability of health facilities and types of roads. Variables were selected for inclusion in the urbanicity scale based on inspection of the data and a review of literature on urbanicity and health. Seven domains were constructed within the scale: Population Size, Economic Activity, Built Environment, Communication, Education, Diversity and Health Services. The scale ranged from 11 to 61 (mean 35) with significant between country differences in mean urbanicity; Ethiopia (30.7), India (33.2), Peru (39.4). Construct validity was supported by factor analysis and high corrected item-scale correlations suggest good internal consistency. High agreement was
Multi-Frequency Blazar Micro-Variability as a Tool to Investigate Relativistic Jets

Directory of Open Access Journals (Sweden)

James R. Webb

2016-08-01

Full Text Available For the past 12 years we have been studying optical micro-variability of a sample of 15 Blazars. We summarize the results of this study and draw some basic conclusions about the characteristics of micro-variability. The intermittency, the stochastic nature, and the similar profile shapes seen in micro-variations at different times and in different objects have led us to a possible model to explain the observed micro-variations. The model is based on a strong shock propagating down a relativistic jet and encountering turbulence which causes density or magnetic field enhancements. We use the theory of Kirk, Reiger, and Mastichiadis (1998 to describe the pulse of synchrotron emission emanating from individual density enhancements energized by the shock. By fitting these “pulses” to micro-variability observations, we obtain excellent fits to actual micro-variations. The model predicts that the spectral index changes as a function of pulse duration. This effect should be observable in multi-frequency micro-variability data. We present the theoretical model, model fits of our micro-variability light curves, and preliminary multi-frequency micro-variability observations that support this model. A further test that has yet to be carried out involves observing polarization changes in different pulses.
Multi-scale semi-ideal magnetohydrodynamics of a tokamak plasma

Energy Technology Data Exchange (ETDEWEB)

Bazdenkov, S.; Sato, Tetsuya; Watanabe, Kunihiko

1995-09-01

An analytical model of fast spatial flattening of the toroidal current density and q-profile at the nonlinear stage of (m = 1/n = 1) kink instability of a tokamak plasma is presented. The flattening is shown to be an essentially multi-scale phenomenon which is characterized by, at least, two magnetic Reynolds numbers. The ordinary one, R{sub m}, is related with a characteristic radial scale-length, while the other, R{sub m}{sup *}, corresponds to a characteristic scale-length of plasma inhomogeneity along the magnetic field line. In a highly conducting plasma inside the q = 1 magnetic surface, where q value does not much differ from unity, plasma evolution is governed by a multi-scale non-ideal dynamics characterized by two well-separated magnetic Reynolds numbers, R{sub m} and R{sub m}{sup *} {identical_to} (1 - q) R{sub m}, where R{sub m}{sup *} - O(1) and R{sub m} >> 1. This dynamics consistently explains two seemingly contradictory features recently observed in a numerical simulation [Watanabe et al., 1995]: (i) the current profile (q-profile) is flattened in the magnetohydrodynamic time scale within the q = 1 rational surface; (ii) the magnetic surface keeps its initial circular shape during this evolution. (author).
Multi-Scale Simulation of High Energy Density Ionic Liquids

National Research Council Canada - National Science Library

Voth, Gregory A

2007-01-01

The focus of this AFOSR project was the molecular dynamics (MD) simulation of ionic liquid structure, dynamics, and interfacial properties, as well as multi-scale descriptions of these novel liquids (e.g...
Joint Multi-scale Convolution Neural Network for Scene Classification of High Resolution Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

ZHENG Zhuo

2018-05-01

Full Text Available High resolution remote sensing imagery scene classification is important for automatic complex scene recognition, which is the key technology for military and disaster relief, etc. In this paper, we propose a novel joint multi-scale convolution neural network (JMCNN method using a limited amount of image data for high resolution remote sensing imagery scene classification. Different from traditional convolutional neural network, the proposed JMCNN is an end-to-end training model with joint enhanced high-level feature representation, which includes multi-channel feature extractor, joint multi-scale feature fusion and Softmax classifier. Multi-channel and scale convolutional extractors are used to extract scene middle features, firstly. Then, in order to achieve enhanced high-level feature representation in a limit dataset, joint multi-scale feature fusion is proposed to combine multi-channel and scale features using two feature fusions. Finally, enhanced high-level feature representation can be used for classification by Softmax. Experiments were conducted using two limit public UCM and SIRI datasets. Compared to state-of-the-art methods, the JMCNN achieved improved performance and great robustness with average accuracies of 89.3% and 88.3% on the two datasets.
Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging

Science.gov (United States)

Lee, Jongpil; Nam, Juhan

2017-08-01

Music auto-tagging is often handled in a similar manner to image classification by regarding the 2D audio spectrogram as image data. However, music auto-tagging is distinguished from image classification in that the tags are highly diverse and have different levels of abstractions. Considering this issue, we propose a convolutional neural networks (CNN)-based architecture that embraces multi-level and multi-scaled features. The architecture is trained in three steps. First, we conduct supervised feature learning to capture local audio features using a set of CNNs with different input sizes. Second, we extract audio features from each layer of the pre-trained convolutional networks separately and aggregate them altogether given a long audio clip. Finally, we put them into fully-connected networks and make final predictions of the tags. Our experiments show that using the combination of multi-level and multi-scale features is highly effective in music auto-tagging and the proposed method outperforms previous state-of-the-arts on the MagnaTagATune dataset and the Million Song Dataset. We further show that the proposed architecture is useful in transfer learning.
The development and validation of an urbanicity scale in a multi-country study

Directory of Open Access Journals (Sweden)

Novak Nicole L

2012-07-01

Full Text Available Abstract Background Although urban residence is consistently identified as one of the primary correlates of non-communicable disease in low- and middle-income countries, it is not clear why or how urban settings predispose individuals and populations to non-communicable disease (NCD, or how this relationship could be modified to slow the spread of NCD. The urban–rural dichotomy used in most population health research lacks the nuance and specificity necessary to understand the complex relationship between urbanicity and NCD risk. Previous studies have developed and validated quantitative tools to measure urbanicity continuously along several dimensions but all have been isolated to a single country. The purposes of this study were 1 To assess the feasibility and validity of a multi-country urbanicity scale; 2 To report some of the considerations that arise in applying such a scale in different countries; and, 3 To assess how this scale compares with previously validated scales of urbanicity. Methods Household and community-level data from the Young Lives longitudinal study of childhood poverty in 59 communities in Ethiopia, India and Peru collected in 2006/2007 were used. Household-level data include parents’ occupations and education level, household possessions and access to resources. Community-level data include population size, availability of health facilities and types of roads. Variables were selected for inclusion in the urbanicity scale based on inspection of the data and a review of literature on urbanicity and health. Seven domains were constructed within the scale: Population Size, Economic Activity, Built Environment, Communication, Education, Diversity and Health Services. Results The scale ranged from 11 to 61 (mean 35 with significant between country differences in mean urbanicity; Ethiopia (30.7, India (33.2, Peru (39.4. Construct validity was supported by factor analysis and high corrected item-scale correlations suggest
The Jack mackerel Trachurus murphyiand the environmental macro-scale variables

Directory of Open Access Journals (Sweden)

Marco Espino

2013-10-01

Full Text Available This paper analyses information on various macro environmental variables available since 1876 for the Southeast Pacific and more recent data on Jack mackerel Trachurus murphyi (Nichols, 1920 landings and biomass in the Peruvian sea, relating them to probable areas of water masses equivalent to Cold Coastal Waters (CCW and Subtropical Surface Waters (SSW. It is concluded that the index of the Pacific Decadal Oscillation (PDO presents expressions of variability that are consistent with those found for the Southern Oscillation Index (SOI and that the detected changes in biomass of Jack mackerel T. murphyiin the Peruvian sea reflect changes in the availability of the fish stock associated with secular (SOI and decadal (PDO variability patterns. These fluctuations in stock availability impact fisheries in Ecuador, Peru and northern Chile, which show significant variations in their landings and would have given a biased picture of the state of abundance, leading to wrong diagnoses of the real situation of the exploited stocks. These patterns of variability would also affect the appearance of El Niño, making them start in the southern hemisphere autumn or spring depending on whether the current PDO is positive or negative. Periods of high (1876 – 1925 and 1976 – 2012 and low (1926 – 1975 variability are also identified in relation to the Euclidean distance of the variances of the SOI; and in relation to the PDO a distinction is made between warm (1925 – 1944 and 1975 – 1994, cold (1945 – 1974 and tempered or interface periods (1895 – 1924 and 1995 – 2012, the latter being explained by the interaction between periods of high variability.

Evaluation of the multi-sums for large scale problems

International Nuclear Information System (INIS)

Bluemlein, J.; Hasselhuhn, A.; Schneider, C.

2012-02-01

A big class of Feynman integrals, in particular, the coefficients of their Laurent series expansion w.r.t. the dimension parameter ε can be transformed to multi-sums over hypergeometric terms and harmonic sums. In this article, we present a general summation method based on difference fields that simplifies these multi--sums by transforming them from inside to outside to representations in terms of indefinite nested sums and products. In particular, we present techniques that assist in the task to simplify huge expressions of such multi-sums in a completely automatic fashion. The ideas are illustrated on new calculations coming from 3-loop topologies of gluonic massive operator matrix elements containing two fermion lines, which contribute to the transition matrix elements in the variable flavor scheme. (orig.)
Evaluation of the multi-sums for large scale problems

Energy Technology Data Exchange (ETDEWEB)

Bluemlein, J.; Hasselhuhn, A. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Schneider, C. [Johannes Kepler Univ., Linz (Austria). Research Inst. for Symbolic Computation

2012-02-15

A big class of Feynman integrals, in particular, the coefficients of their Laurent series expansion w.r.t. the dimension parameter {epsilon} can be transformed to multi-sums over hypergeometric terms and harmonic sums. In this article, we present a general summation method based on difference fields that simplifies these multi--sums by transforming them from inside to outside to representations in terms of indefinite nested sums and products. In particular, we present techniques that assist in the task to simplify huge expressions of such multi-sums in a completely automatic fashion. The ideas are illustrated on new calculations coming from 3-loop topologies of gluonic massive operator matrix elements containing two fermion lines, which contribute to the transition matrix elements in the variable flavor scheme. (orig.)
Observations and 3D hydrodynamics-based modeling of decadal-scale shoreline change along the Outer Banks, North Carolina

Science.gov (United States)

Safak, Ilgar; List, Jeffrey; Warner, John C.; Kumar, Nirnimesh

2017-01-01

Long-term decadal-scale shoreline change is an important parameter for quantifying the stability of coastal systems. The decadal-scale coastal change is controlled by processes that occur on short time scales (such as storms) and long-term processes (such as prevailing waves). The ability to predict decadal-scale shoreline change is not well established and the fundamental physical processes controlling this change are not well understood. Here we investigate the processes that create large-scale long-term shoreline change along the Outer Banks of North Carolina, an uninterrupted 60 km stretch of coastline, using both observations and a numerical modeling approach. Shoreline positions for a 24-yr period were derived from aerial photographs of the Outer Banks. Analysis of the shoreline position data showed that, although variable, the shoreline eroded an average of 1.5 m/yr throughout this period. The modeling approach uses a three-dimensional hydrodynamics-based numerical model coupled to a spectral wave model and simulates the full 24-yr time period on a spatial grid running on a short (second scale) time-step to compute the sediment transport patterns. The observations and the model results show similar magnitudes (O(105 m3/yr)) and patterns of alongshore sediment fluxes. Both the observed and the modeled alongshore sediment transport rates have more rapid changes at the north of our section due to continuously curving coastline, and possible effects of alongshore variations in shelf bathymetry. The southern section with a relatively uniform orientation, on the other hand, has less rapid transport rate changes. Alongshore gradients of the modeled sediment fluxes are translated into shoreline change rates that have agreement in some locations but vary in others. Differences between observations and model results are potentially influenced by geologic framework processes not included in the model. Both the observations and the model results show higher rates of
Variability Extraction and Synthesis via Multi-Resolution Analysis using Distribution Transformer High-Speed Power Data

Energy Technology Data Exchange (ETDEWEB)

Chamana, Manohar [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Mather, Barry A [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-10-19

A library of load variability classes is created to produce scalable synthetic data sets using historical high-speed raw data. These data are collected from distribution monitoring units connected at the secondary side of a distribution transformer. Because of the irregular patterns and large volume of historical high-speed data sets, the utilization of current load characterization and modeling techniques are challenging. Multi-resolution analysis techniques are applied to extract the necessary components and eliminate the unnecessary components from the historical high-speed raw data to create the library of classes, which are then utilized to create new synthetic load data sets. A validation is performed to ensure that the synthesized data sets contain the same variability characteristics as the training data sets. The synthesized data sets are intended to be utilized in quasi-static time-series studies for distribution system planning studies on a granular scale, such as detailed PV interconnection studies.
A Multi-scale, Multi-disciplinary Approach for Assessing the Technological, Economic, and Environmental Performance of Bio-based Chemicals

DEFF Research Database (Denmark)

Herrgard, Markus; Sukumara, Sumesh; Campodonico Alt, Miguel Angel

2015-01-01

, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain...... towards a sustainable chemical industry....
Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

Science.gov (United States)

Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.
Multi-wheat-model ensemble responses to interannual climatic variability

DEFF Research Database (Denmark)

Ruane, A C; Hudson, N I; Asseng, S

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and ......-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.......We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and we...... evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal...
Multi-scale modeling with cellular automata: The complex automata approach

NARCIS (Netherlands)

Hoekstra, A.G.; Falcone, J.-L.; Caiazzo, A.; Chopard, B.

2008-01-01

Cellular Automata are commonly used to describe complex natural phenomena. In many cases it is required to capture the multi-scale nature of these phenomena. A single Cellular Automata model may not be able to efficiently simulate a wide range of spatial and temporal scales. It is our goal to
Detecting Multi-scale Structures in Chandra Images of Centaurus A

Science.gov (United States)

Karovska, M.; Fabbiano, G.; Elvis, M. S.; Evans, I. N.; Kim, D. W.; Prestwich, A. H.; Schwartz, D. A.; Murray, S. S.; Forman, W.; Jones, C.; Kraft, R. P.; Isobe, T.; Cui, W.; Schreier, E. J.

1999-12-01

Centaurus A (NGC 5128) is a giant early-type galaxy with a merger history, containing the nearest radio-bright AGN. Recent Chandra High Resolution Camera (HRC) observations of Cen A reveal X-ray multi-scale structures in this object with unprecedented detail and clarity. We show the results of an analysis of the Chandra data with smoothing and edge enhancement techniques that allow us to enhance and quantify the multi-scale structures present in the HRC images. These techniques include an adaptive smoothing algorithm (Ebeling et al 1999), and a multi-directional gradient detection algorithm (Karovska et al 1994). The Ebeling et al adaptive smoothing algorithm, which is incorporated in the CXC analysis s/w package, is a powerful tool for smoothing images containing complex structures at various spatial scales. The adaptively smoothed images of Centaurus A show simultaneously the high-angular resolution bright structures at scales as small as an arcsecond and the extended faint structures as large as several arc minutes. The large scale structures suggest complex symmetry, including a component possibly associated with the inner radio lobes (as suggested by the ROSAT HRI data, Dobereiner et al 1996), and a separate component with an orthogonal symmetry that may be associated with the galaxy as a whole. The dust lane and the x-ray ridges are very clearly visible. The adaptively smoothed images and the edge-enhanced images also suggest several filamentary features including a large filament-like structure extending as far as about 5 arcminutes to North-West.
Analysis of variability in multi-day GPS imputed activity-travel diaries using multi-dimensional sequence alignment and panel effects regression models

NARCIS (Netherlands)

Xianyu, J.; Rasouli, S.; Timmermans, H.J.P.

The use of GPS devices and smartphones has made feasible the collection of multi-day activity-travel diaries. In turn, the availability of multi-day travel diary data opens up new avenues for analyzing dynamics of individual travel behavior. This paper addresses the issue of day-to-day variability
Evaluating the Impact of Localized GCM Grid Refinement on Regional Tropical Cyclone Climatology and Synoptic Variability using Variable-Resolution CAM-SE

Science.gov (United States)

Zarzycki, C.; Jablonowski, C.

2013-12-01

Using General Circulation Models (GCMs) to resolve sub-synoptic features in climate simulations has traditionally been difficult due to a multitude of atmospheric processes operating at subgrid scales requiring significant parameterization. For example, at traditional GCM horizontal grid resolutions of 50-300 km, tropical cyclones are generally under-resolved. This paper explores a novel variable-resolution global modeling approach that allows for high spatial resolutions in areas of interest, such as low-latitude ocean basins where tropical cyclogenesis occurs. Such multi-resolution GCM designs allow for targeted use of computing resources at the regional level while maintaining a globally-continuous model domain and may serve to bridge the gap between GCMs with uniform grids and boundary-forced limited area models. A statically-nested, variable-resolution option has recently been introduced into the Community Atmosphere Model's (CAM) Spectral Element (SE) dynamical core. A 110 km CAM-SE grid with a 28 km nest over the Atlantic Ocean has been coupled to land, ocean, and ice components within the Community Earth System Model (CESM). We present the results of a multi-decadal climate simulation using Atmospheric Model Intercomparison Project (AMIP) protocols, which force the model with historical sea surface temperatures and airborne chemical species. To investigate whether refinement improves the representation of tropical cyclones, we compare Atlantic storm statistics to observations with specific focus paid to intensity profiles and track densities. The resolution dependance of both cyclone structure and objective detection between refined and unrefined basins is explored. In addition, we discuss the potential impact of using variable-resolution grids on the large-scale synoptic interannual variability by comparing refined grid simulations to reanalysis data as well as an unrefined, globally-uniform CAM-SE simulation with identical forcing. We also evaluate the
Multi-Scale Initial Conditions For Cosmological Simulations

Energy Technology Data Exchange (ETDEWEB)

Hahn, Oliver; /KIPAC, Menlo Park; Abel, Tom; /KIPAC, Menlo Park /ZAH, Heidelberg /HITS, Heidelberg

2011-11-04

We discuss a new algorithm to generate multi-scale initial conditions with multiple levels of refinements for cosmological 'zoom-in' simulations. The method uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). The new algorithm achieves rms relative errors of the order of 10{sup -4} for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier-space-induced interference ringing. An optional hybrid multi-grid and Fast Fourier Transform (FFT) based scheme is introduced which has identical Fourier-space behaviour as traditional approaches. Using a suite of re-simulations of a galaxy cluster halo our real-space-based approach is found to reproduce correlation functions, density profiles, key halo properties and subhalo abundances with per cent level accuracy. Finally, we generalize our approach for two-component baryon and dark-matter simulations and demonstrate that the power spectrum evolution is in excellent agreement with linear perturbation theory. For initial baryon density fields, it is suggested to use the local Lagrangian approximation in order to generate a density field for mesh-based codes that is consistent with the Lagrangian perturbation theory instead of the current practice of using the Eulerian linearly scaled densities.
Multi-Scale Entropy Analysis as a Method for Time-Series Analysis of Climate Data

Directory of Open Access Journals (Sweden)

Heiko Balzter

2015-03-01

Full Text Available Evidence is mounting that the temporal dynamics of the climate system are changing at the same time as the average global temperature is increasing due to multiple climate forcings. A large number of extreme weather events such as prolonged cold spells, heatwaves, droughts and floods have been recorded around the world in the past 10 years. Such changes in the temporal scaling behaviour of climate time-series data can be difficult to detect. While there are easy and direct ways of analysing climate data by calculating the means and variances for different levels of temporal aggregation, these methods can miss more subtle changes in their dynamics. This paper describes multi-scale entropy (MSE analysis as a tool to study climate time-series data and to identify temporal scales of variability and their change over time in climate time-series. MSE estimates the sample entropy of the time-series after coarse-graining at different temporal scales. An application of MSE to Central European, variance-adjusted, mean monthly air temperature anomalies (CRUTEM4v is provided. The results show that the temporal scales of the current climate (1960–2014 are different from the long-term average (1850–1960. For temporal scale factors longer than 12 months, the sample entropy increased markedly compared to the long-term record. Such an increase can be explained by systems theory with greater complexity in the regional temperature data. From 1961 the patterns of monthly air temperatures are less regular at time-scales greater than 12 months than in the earlier time period. This finding suggests that, at these inter-annual time scales, the temperature variability has become less predictable than in the past. It is possible that climate system feedbacks are expressed in altered temporal scales of the European temperature time-series data. A comparison with the variance and Shannon entropy shows that MSE analysis can provide additional information on the
Multi-scale calculation based on dual domain material point method combined with molecular dynamics

Energy Technology Data Exchange (ETDEWEB)

Dhakal, Tilak Raj [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-02-27

This dissertation combines the dual domain material point method (DDMP) with molecular dynamics (MD) in an attempt to create a multi-scale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically non-equilibrium state, and conventional constitutive relations are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a MD simulation of a group of atoms surrounding the material point. Rather than restricting the multi-scale simulation in a small spatial region, such as phase interfaces, or crack tips, this multi-scale method can be used to consider non-equilibrium thermodynamic e ects in a macroscopic domain. This method takes advantage that the material points only communicate with mesh nodes, not among themselves; therefore MD simulations for material points can be performed independently in parallel. First, using a one-dimensional shock problem as an example, the numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the DDMP method are investigated. Among these methods, only the DDMP method converges as the number of particles increases, but the large number of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the
A multi-scale relevance vector regression approach for daily urban water demand forecasting

Science.gov (United States)

Bai, Yun; Wang, Pu; Li, Chuan; Xie, Jingjing; Wang, Yin

2014-09-01

Water is one of the most important resources for economic and social developments. Daily water demand forecasting is an effective measure for scheduling urban water facilities. This work proposes a multi-scale relevance vector regression (MSRVR) approach to forecast daily urban water demand. The approach uses the stationary wavelet transform to decompose historical time series of daily water supplies into different scales. At each scale, the wavelet coefficients are used to train a machine-learning model using the relevance vector regression (RVR) method. The estimated coefficients of the RVR outputs for all of the scales are employed to reconstruct the forecasting result through the inverse wavelet transform. To better facilitate the MSRVR forecasting, the chaos features of the daily water supply series are analyzed to determine the input variables of the RVR model. In addition, an adaptive chaos particle swarm optimization algorithm is used to find the optimal combination of the RVR model parameters. The MSRVR approach is evaluated using real data collected from two waterworks and is compared with recently reported methods. The results show that the proposed MSRVR method can forecast daily urban water demand much more precisely in terms of the normalized root-mean-square error, correlation coefficient, and mean absolute percentage error criteria.
Resolving meso-scale seabed variability using reflection measurements from an autonomous underwater vehicle.

Science.gov (United States)

Holland, Charles W; Nielsen, Peter L; Dettmer, Jan; Dosso, Stan

2012-02-01

Seabed geoacoustic variability is driven by geological processes that occur over a wide spectrum of space-time scales. While the acoustics community has some understanding of horizontal fine-scale geoacoustic variability, less than O(10(0)) m, and large-scale variability, greater than O(10(3)) m, there is a paucity of data resolving the geoacoustic meso-scale O(10(0)-10(3)) m. Measurements of the meso-scale along an ostensibly "benign" portion of the outer shelf reveal three classes of variability. The first class was expected and is due to horizontal variability of layer thicknesses: this was the only class that could be directly tied to seismic reflection data. The second class is due to rapid changes in layer properties and/or boundaries, occurring over scales of meters to hundreds of meters. The third class was observed as rapid variations of the angle/frequency dependent reflection coefficient within a single observation and is suggestive of variability at scales of meter or less. Though generally assumed to be negligible in acoustic modeling, the second and third classes are indicative of strong horizontal geoacoustic variability within a given layer. The observations give early insight into possible effects of horizontal geoacoustic variability on long-range acoustic propagation and reverberation. © 2012 Acoustical Society of America
A multi-scale correlative investigation of ductile fracture

International Nuclear Information System (INIS)

Daly, M.; Burnett, T.L.; Pickering, E.J.; Tuck, O.C.G.; Léonard, F.; Kelley, R.; Withers, P.J.; Sherry, A.H.

2017-01-01

The use of novel multi-scale correlative methods, which involve the coordinated characterisation of matter across a range of length scales, are becoming of increasing value to materials scientists. Here, we describe for the first time how a multi-scale correlative approach can be used to investigate the nature of ductile fracture in metals. Specimens of a nuclear pressure vessel steel, SA508 Grade 3, are examined following ductile fracture using medium and high-resolution 3D X-ray computed tomography (CT) analyses, and a site-specific analysis using a dual beam plasma focused ion beam scanning electron microscope (PFIB-SEM). The methods are employed sequentially to characterise damage by void nucleation and growth in one volume of interest, allowing for the imaging of voids that ranged in size from less than 100 nm to over 100 μm. This enables the examination of voids initiated at carbide particles to be detected, as well as the large voids initiated at inclusions. We demonstrate that this multi-scale correlative approach is a powerful tool, which not only enhances our understanding of ductile failure through detailed characterisation of microstructure, but also provides quantitative information about the size, volume fractions and spatial distributions of voids that can be used to inform models of failure. It is found that the vast majority of large voids nucleated at MnS inclusions, and that the volume of a void varied according to the volume of its initiating inclusion raised to the power 3/2. The most severe voiding was concentrated within 500 μm of the fracture surface, but measurable damage was found to extend to a depth of at least 3 mm. Microvoids associated with carbides (carbide-initiated voids) were found to be concentrated around larger inclusion-initiated voids at depths of at least 400 μm. Methods for quantifying X-ray CT void data are discussed, and a procedure for using this data to calibrate parameters in the Gurson-Tvergaard Needleman (GTN
Gowdy phenomenology in scale-invariant variables

International Nuclear Information System (INIS)

Andersson, Lars; Elst, Henk van; Uggla, Claes

2004-01-01

The dynamics of Gowdy vacuum spacetimes is considered in terms of Hubble-normalized scale-invariant variables, using the timelike area temporal gauge. The resulting state space formulation provides for a simple mechanism for the formation of 'false' and 'true spikes' in the approach to the singularity, and a geometrical formulation for the local attractor
A multi-scale health impact assessment of air pollution over the 21st century.

Science.gov (United States)

Likhvar, Victoria N; Pascal, Mathilde; Markakis, Konstantinos; Colette, Augustin; Hauglustaine, Didier; Valari, Myrto; Klimont, Zbigniew; Medina, Sylvia; Kinney, Patrick

2015-05-01

Ozone and PM₂.₅ are current risk factors for premature death all over the globe. In coming decades, substantial improvements in public health may be achieved by reducing air pollution. To better understand the potential of emissions policies, studies are needed that assess possible future health impacts under alternative assumptions about future emissions and climate across multiple spatial scales. We used consistent climate-air-quality-health modeling framework across three geographical scales (World, Europe and Ile-de-France) to assess future (2030-2050) health impacts of ozone and PM₂.₅ under two emissions scenarios (Current Legislation Emissions, CLE, and Maximum Feasible Reductions, MFR). Consistently across the scales, we found more reductions in deaths under MFR scenario compared to CLE. 1.5 [95% CI: 0.4, 2.4] million CV deaths could be delayed each year in 2030 compared to 2010 under MFR scenario, 84% of which would occur in Asia, especially in China. In Europe, the benefits under MFR scenario (219000 CV deaths) are noticeably larger than those under CLE (109,000 CV deaths). In Ile-de-France, under MFR more than 2830 annual CV deaths associated with PM₂.₅ changes could be delayed in 2050 compared to 2010. In Paris, ozone-related respiratory mortality should increase under both scenarios. Multi-scale HIAs can illustrate the difference in direct consequences of costly mitigation policies and provide results that may help decision-makers choose between different policy alternatives at different scales. Copyright © 2015 Elsevier B.V. All rights reserved.
A statistical methodology to derive the scaling law for the H-mode power threshold using a large multi-machine database

International Nuclear Information System (INIS)

Murari, A.; Lupelli, I.; Gaudio, P.; Gelfusa, M.; Vega, J.

2012-01-01

In this paper, a refined set of statistical techniques is developed and then applied to the problem of deriving the scaling law for the threshold power to access the H-mode of confinement in tokamaks. This statistical methodology is applied to the 2010 version of the ITPA International Global Threshold Data Base v6b(IGDBTHv6b). To increase the engineering and operative relevance of the results, only macroscopic physical quantities, measured in the vast majority of experiments, have been considered as candidate variables in the models. Different principled methods, such as agglomerative hierarchical variables clustering, without assumption about the functional form of the scaling, and nonlinear regression, are implemented to select the best subset of candidate independent variables and to improve the regression model accuracy. Two independent model selection criteria, based on the classical (Akaike information criterion) and Bayesian formalism (Bayesian information criterion), are then used to identify the most efficient scaling law from candidate models. The results derived from the full multi-machine database confirm the results of previous analysis but emphasize the importance of shaping quantities, elongation and triangularity. On the other hand, the scaling laws for the different machines and at different currents are different from each other at the level of confidence well above 95%, suggesting caution in the use of the global scaling laws for both interpretation and extrapolation purposes. (paper)

Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

Directory of Open Access Journals (Sweden)

Naveed ur Rehman

2015-05-01

Full Text Available A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA, discrete wavelet transform (DWT and non-subsampled contourlet transform (NCT. A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.
Multi-scale characterization of surface blistering morphology of helium irradiated W thin films

International Nuclear Information System (INIS)

Yang, J.J.; Zhu, H.L.; Wan, Q.; Peng, M.J.; Ran, G.; Tang, J.; Yang, Y.Y.; Liao, J.L.; Liu, N.

2015-01-01

Highlights: • Multi-scale blistering morphology of He irradiated W film was studied. • This complex morphology was first characterized by wavelet transform approach. - Abstract: Surface blistering morphologies of W thin films irradiated by 30 keV He ion beam were studied quantitatively. It was found that the blistering morphology strongly depends on He fluence. For lower He fluence, the accumulation and growth of He bubbles induce the intrinsic surface blisters with mono-modal size distribution feature. When the He fluence is higher, the film surface morphology exhibits a multi-scale property, including two kinds of surface blisters with different characteristic sizes. In addition to the intrinsic He blisters, film/substrate interface delamination also induces large-sized surface blisters. A strategy based on wavelet transform approach was proposed to distinguish and extract the multi-scale surface blistering morphologies. Then the density, the lateral size and the height of these different blisters were estimated quantitatively, and the effect of He fluence on these geometrical parameters was investigated. Our method could provide a potential tool to describe the irradiation induced surface damage morphology with a multi-scale property
Multi-scale analysis of the European airspace using network community detection.

Directory of Open Access Journals (Sweden)

Gérald Gurtner

Full Text Available We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspace and improve it by guiding the design of new ones. Specifically, we compare the performance of several community detection algorithms, both with fixed and variable resolution, and also by using a null model which takes into account the spatial distance between nodes, and we discuss their ability to find communities that could be used to define new control units of the airspace.
Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain

2017-01-01

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive
Simulating the Agulhas system in global ocean models - nesting vs. multi-resolution unstructured meshes

Science.gov (United States)

Biastoch, Arne; Sein, Dmitry; Durgadoo, Jonathan V.; Wang, Qiang; Danilov, Sergey

2018-01-01

Many questions in ocean and climate modelling require the combined use of high resolution, global coverage and multi-decadal integration length. For this combination, even modern resources limit the use of traditional structured-mesh grids. Here we compare two approaches: A high-resolution grid nested into a global model at coarser resolution (NEMO with AGRIF) and an unstructured-mesh grid (FESOM) which allows to variably enhance resolution where desired. The Agulhas system around South Africa is used as a testcase, providing an energetic interplay of a strong western boundary current and mesoscale dynamics. Its open setting into the horizontal and global overturning circulations also requires global coverage. Both model configurations simulate a reasonable large-scale circulation. Distribution and temporal variability of the wind-driven circulation are quite comparable due to the same atmospheric forcing. However, the overturning circulation differs, owing each model's ability to represent formation and spreading of deep water masses. In terms of regional, high-resolution dynamics, all elements of the Agulhas system are well represented. Owing to the strong nonlinearity in the system, Agulhas Current transports of both configurations and in comparison with observations differ in strength and temporal variability. Similar decadal trends in Agulhas Current transport and Agulhas leakage are linked to the trends in wind forcing.
A Poisson regression approach to model monthly hail occurrence in Northern Switzerland using large-scale environmental variables

Science.gov (United States)

Madonna, Erica; Ginsbourger, David; Martius, Olivia

2018-05-01

In Switzerland, hail regularly causes substantial damage to agriculture, cars and infrastructure, however, little is known about its long-term variability. To study the variability, the monthly number of days with hail in northern Switzerland is modeled in a regression framework using large-scale predictors derived from ERA-Interim reanalysis. The model is developed and verified using radar-based hail observations for the extended summer season (April-September) in the period 2002-2014. The seasonality of hail is explicitly modeled with a categorical predictor (month) and monthly anomalies of several large-scale predictors are used to capture the year-to-year variability. Several regression models are applied and their performance tested with respect to standard scores and cross-validation. The chosen model includes four predictors: the monthly anomaly of the two meter temperature, the monthly anomaly of the logarithm of the convective available potential energy (CAPE), the monthly anomaly of the wind shear and the month. This model well captures the intra-annual variability and slightly underestimates its inter-annual variability. The regression model is applied to the reanalysis data back in time to 1980. The resulting hail day time series shows an increase of the number of hail days per month, which is (in the model) related to an increase in temperature and CAPE. The trend corresponds to approximately 0.5 days per month per decade. The results of the regression model have been compared to two independent data sets. All data sets agree on the sign of the trend, but the trend is weaker in the other data sets.
The Multi-Scale Model Approach to Thermohydrology at Yucca Mountain

International Nuclear Information System (INIS)

Glascoe, L; Buscheck, T A; Gansemer, J; Sun, Y

2002-01-01

The Multi-Scale Thermo-Hydrologic (MSTH) process model is a modeling abstraction of them1 hydrology (TH) of the potential Yucca Mountain repository at multiple spatial scales. The MSTH model as described herein was used for the Supplemental Science and Performance Analyses (BSC, 2001) and is documented in detail in CRWMS M and O (2000) and Glascoe et al. (2002). The model has been validated to a nested grid model in Buscheck et al. (In Review). The MSTH approach is necessary for modeling thermal hydrology at Yucca Mountain for two reasons: (1) varying levels of detail are necessary at different spatial scales to capture important TH processes and (2) a fully-coupled TH model of the repository which includes the necessary spatial detail is computationally prohibitive. The MSTH model consists of six ''submodels'' which are combined in a manner to reduce the complexity of modeling where appropriate. The coupling of these models allows for appropriate consideration of mountain-scale thermal hydrology along with the thermal hydrology of drift-scale discrete waste packages of varying heat load. Two stages are involved in the MSTH approach, first, the execution of submodels, and second, the assembly of submodels using the Multi-scale Thermohydrology Abstraction Code (MSTHAC). MSTHAC assembles the submodels in a five-step process culminating in the TH model output of discrete waste packages including a mountain-scale influence
Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics Approach

Directory of Open Access Journals (Sweden)

Junjun Yin

2016-10-01

Full Text Available Understanding human mobility patterns is of great importance for urban planning, traffic management, and even marketing campaign. However, the capability of capturing detailed human movements with fine-grained spatial and temporal granularity is still limited. In this study, we extracted high-resolution mobility data from a collection of over 1.3 billion geo-located Twitter messages. Regarding the concerns of infringement on individual privacy, such as the mobile phone call records with restricted access, the dataset is collected from publicly accessible Twitter data streams. In this paper, we employed a visual-analytics approach to studying multi-scale spatiotemporal Twitter user mobility patterns in the contiguous United States during the year 2014. Our approach included a scalable visual-analytics framework to deliver efficiency and scalability in filtering large volume of geo-located tweets, modeling and extracting Twitter user movements, generating space-time user trajectories, and summarizing multi-scale spatiotemporal user mobility patterns. We performed a set of statistical analysis to understand Twitter user mobility patterns across multi-level spatial scales and temporal ranges. In particular, Twitter user mobility patterns measured by the displacements and radius of gyrations of individuals revealed multi-scale or multi-modal Twitter user mobility patterns. By further studying such mobility patterns in different temporal ranges, we identified both consistency and seasonal fluctuations regarding the distance decay effects in the corresponding mobility patterns. At the same time, our approach provides a geo-visualization unit with an interactive 3D virtual globe web mapping interface for exploratory geo-visual analytics of the multi-level spatiotemporal Twitter user movements.
New Soliton-like Solutions and Multi-soliton Structures for Broer-Kaup System with Variable Coefficients

International Nuclear Information System (INIS)

Ji Mingjun; Lue Zhuosheng

2005-01-01

By using the further extended tanh method [Phys. Lett. A 307 (2003) 269; Chaos, Solitons and Fractals 17 (2003) 669] to the Broer-Kaup system with variable coefficients, abundant new soliton-like solutions and multi-soliton-like solutions are derived. Based on the derived multi-soliton-like solutions which contain arbitrary functions, some interesting multi-soliton structures are revealed.
Multi-decade biomass dynamics in an old-growth hemlock-northern hardwood forest, Michigan, USA

Directory of Open Access Journals (Sweden)

Kerry D. Woods

2014-09-01

Full Text Available Trends in living aboveground biomass and inputs to the pool of coarse woody debris (CWD in an undisturbed, old-growth hemlock-northern hardwood forest in northern MI were estimated from multi-decade observations of permanent plots. Growth and demographic data from seven plot censuses over 47 years (1962–2009, combined with one-time measurement of CWD pools, help assess biomass/carbon status of this landscape. Are trends consistent with traditional notions of late-successional forests as equilibrial ecosystems? Specifically, do biomass pools and CWD inputs show consistent long-term trends and relationships, and can living and dead biomass pools and trends be related to forest composition and history? Aboveground living biomass densities, estimated using standard allometric relationships, range from 360–450 Mg/ha among sampled stands and types; these values are among the highest recorded for northeastern North American forests. Biomass densities showed significant decade-scale variation, but no consistent trends over the full study period (one stand, originating following an 1830 fire, showed an aggrading trend during the first 25 years of the study. Even though total above-ground biomass pools are neither increasing nor decreasing, they have been increasingly dominated, over the full study period, by very large (>70 cm dbh stems and by the most shade-tolerant species (Acer saccharum and Tsuga canadensis.CWD pools measured in 2007 averaged 151 m3/ha, with highest values in Acer-dominated stands. Snag densities averaged 27/ha, but varied nearly ten-fold with canopy composition (highest in Tsuga-dominated stands, lowest in Acer-dominated; snags constituted 10–50% of CWD biomass. Annualized CWD inputs from tree mortality over the full study period averaged 1.9–3.2 Mg/ha/yr, depending on stand and species composition. CWD input rates tended to increase over the course of the study. Input rates may be expected to increase over longer
Multi-scale Modeling of Power Plant Plume Emissions and Comparisons with Observations

Science.gov (United States)

Costigan, K. R.; Lee, S.; Reisner, J.; Dubey, M. K.; Love, S. P.; Henderson, B. G.; Chylek, P.

2011-12-01

The Remote Sensing Verification Project (RSVP) test-bed located in the Four Corners region of Arizona, Utah, Colorado, and New Mexico offers a unique opportunity to develop new approaches for estimating emissions of CO2. Two major power plants located in this area produce very large signals of co-emitted CO2 and NO2 in this rural region. In addition to the Environmental Protection Agency (EPA) maintaining Continuous Emissions Monitoring Systems (CEMS) on each of the power plant stacks, the RSVP program has deployed an array of in-situ and remote sensing instruments, which provide both point and integrated measurements. To aid in the synthesis and interpretation of the measurements, a multi-scale atmospheric modeling approach is implemented, using two atmospheric numerical models: the Weather Research and Forecasting Model with chemistry (WRF-Chem; Grell et al., 2005) and the HIGRAD model (Reisner et al., 2003). The high fidelity HIGRAD model incorporates a multi-phase Lagrangian particle based approach to track individual chemical species of stack plumes at ultra-high resolution, using an adaptive mesh. It is particularly suited to model buoyancy effects and entrainment processes at the edges of the power plant plumes. WRF-Chem is a community model that has been applied to a number of air quality problems and offers several physical and chemical schemes that can be used to model the transport and chemical transformation of the anthropogenic plumes out of the local region. Multiple nested grids employed in this study allow the model to incorporate atmospheric variability ranging from synoptic scales to micro-scales (~200 m), while including locally developed flows influenced by the nearby complex terrain of the San Juan Mountains. The simulated local atmospheric dynamics are provided to force the HIGRAD model, which links mesoscale atmospheric variability to the small-scale simulation of the power plant plumes. We will discuss how these two models are applied and
Understanding hydraulic fracturing: a multi-scale problem

Science.gov (United States)

Hyman, J. D.; Jiménez-Martínez, J.; Viswanathan, H. S.; Carey, J. W.; Porter, M. L.; Rougier, E.; Karra, S.; Kang, Q.; Frash, L.; Chen, L.; Lei, Z.; O’Malley, D.; Makedonska, N.

2016-01-01

Despite the impact that hydraulic fracturing has had on the energy sector, the physical mechanisms that control its efficiency and environmental impacts remain poorly understood in part because the length scales involved range from nanometres to kilometres. We characterize flow and transport in shale formations across and between these scales using integrated computational, theoretical and experimental efforts/methods. At the field scale, we use discrete fracture network modelling to simulate production of a hydraulically fractured well from a fracture network that is based on the site characterization of a shale gas reservoir. At the core scale, we use triaxial fracture experiments and a finite-discrete element model to study dynamic fracture/crack propagation in low permeability shale. We use lattice Boltzmann pore-scale simulations and microfluidic experiments in both synthetic and shale rock micromodels to study pore-scale flow and transport phenomena, including multi-phase flow and fluids mixing. A mechanistic description and integration of these multiple scales is required for accurate predictions of production and the eventual optimization of hydrocarbon extraction from unconventional reservoirs. Finally, we discuss the potential of CO2 as an alternative working fluid, both in fracturing and re-stimulating activities, beyond its environmental advantages. This article is part of the themed issue ‘Energy and the subsurface’. PMID:27597789
Development of porous structure simulator for multi-scale simulation of irregular porous catalysts

International Nuclear Information System (INIS)

Koyama, Michihisa; Suzuki, Ai; Sahnoun, Riadh; Tsuboi, Hideyuki; Hatakeyama, Nozomu; Endou, Akira; Takaba, Hiromitsu; Kubo, Momoji; Del Carpio, Carlos A.; Miyamoto, Akira

2008-01-01

Efficient development of highly functional porous materials, used as catalysts in the automobile industry, demands a meticulous knowledge of the nano-scale interface at the electronic and atomistic scale. However, it is often difficult to correlate the microscopic interfacial interactions with macroscopic characteristics of the materials; for instance, the interaction between a precious metal and its support oxide with long-term sintering properties of the catalyst. Multi-scale computational chemistry approaches can contribute to bridge the gap between micro- and macroscopic characteristics of these materials; however this type of multi-scale simulations has been difficult to apply especially to porous materials. To overcome this problem, we have developed a novel mesoscopic approach based on a porous structure simulator. This simulator can construct automatically irregular porous structures on a computer, enabling simulations with complex meso-scale structures. Moreover, in this work we have developed a new method to simulate long-term sintering properties of metal particles on porous catalysts. Finally, we have applied the method to the simulation of sintering properties of Pt on alumina support. This newly developed method has enabled us to propose a multi-scale simulation approach for porous catalysts
Intelligent control for large-scale variable speed variable pitch wind turbines

Institute of Scientific and Technical Information of China (English)

Xinfang ZHANG; Daping XU; Yibing LIU

2004-01-01

Large-scale wind turbine generator systems have strong nonlinear multivariable characteristics with many uncertain factors and disturbances.Automatic control is crucial for the efficiency and reliability of wind turbines.On the basis of simplified and proper model of variable speed variable pitch wind turbines,the effective wind speed is estimated using extended Kalman filter.Intelligent control schemes proposed in the paper include two loops which operate in synchronism with each other.At below-rated wind speed,the inner loop adopts adaptive fuzzy control based on variable universe for generator torque regulation to realize maximum wind energy capture.At above-rated wind speed, a controller based on least square support vector machine is proposed to adjust pitch angle and keep rated output power.The simulation shows the effectiveness of the intelligent control.
Elephant overflows: Multi-annual variability in Weddell Sea Deep Water driven by surface forcing

Science.gov (United States)

Meijers, Andrew; Meredith, Michael; Abrahamsen, Povl; Naviera-Garabato, Alberto; Ángel Morales Maqueda, Miguel; Polzin, Kurt

2015-04-01

The volume of the deepest and densest water mass in Drake Passage, Lower Weddell Sea Deep Water (LWSDW), is shown to have been decreasing over the last 20 years of observations, with an associated reduction in density driven by freshening. Superimposed on this long term trend is a multi-annual oscillation with a period of 3-5 years. This variability only appears in Drake Passage; observations in the east of the Scotia Sea show a similar long term trend, but with no apparent multi-annual variability. Clues as to the source of this variability may be found on the continental slope at approximately 1000 m immediately north of Elephant Island on the northern tip of the Antarctic Peninsula. Here there is an intermittent westward flowing cold/fresh slope current whose volume and properties are strongly correlated with the LWSDW multi-annual variability, although leading the LWSDW by around one year. As the slope current and LWSDW are separated from each other both geographically and in water mass characteristics, their co-variability implies that they are responding to a common forcing, while the lag between deep LWSDW and shallow slope current provides information on the timescale of this response. A newly available high resolution temperature and salinity multi-year time series from the Elephant Island slope at 1000 m is compared with reanalysis and model derived surface fluxes, sea ice extent and wind stress. We find that there are strong positive relationships between the surface wind stress and heat flux over the shelf at the tip of the Antarctic Peninsula and the properties of the slope current at 1000 m on seasonal to annual timescales. We use tracer release experiments in the Southern Ocean State Estimate (SOSE) model to investigate the lag between the slope current and LWSDW timeseries and hypothesise that the observed multi-annual variability in both water masses is driven by surface forcing over the shelf and the overflow of modified water from the slope in
Bias and Bias Correction in Multi-Site Instrumental Variables Analysis of Heterogeneous Mediator Effects

Science.gov (United States)

Reardon, Sean F.; Unlu, Faith; Zhu, Pei; Bloom, Howard

2013-01-01

We explore the use of instrumental variables (IV) analysis with a multi-site randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, as assumption known in the instrumental variables literature as the…
Multi-scale Modeling of Arctic Clouds

Science.gov (United States)

Hillman, B. R.; Roesler, E. L.; Dexheimer, D.

2017-12-01

The presence and properties of clouds are critically important to the radiative budget in the Arctic, but clouds are notoriously difficult to represent in global climate models (GCMs). The challenge stems partly from a disconnect in the scales at which these models are formulated and the scale of the physical processes important to the formation of clouds (e.g., convection and turbulence). Because of this, these processes are parameterized in large-scale models. Over the past decades, new approaches have been explored in which a cloud system resolving model (CSRM), or in the extreme a large eddy simulation (LES), is embedded into each gridcell of a traditional GCM to replace the cloud and convective parameterizations to explicitly simulate more of these important processes. This approach is attractive in that it allows for more explicit simulation of small-scale processes while also allowing for interaction between the small and large-scale processes. The goal of this study is to quantify the performance of this framework in simulating Arctic clouds relative to a traditional global model, and to explore the limitations of such a framework using coordinated high-resolution (eddy-resolving) simulations. Simulations from the global model are compared with satellite retrievals of cloud fraction partioned by cloud phase from CALIPSO, and limited-area LES simulations are compared with ground-based and tethered-balloon measurements from the ARM Barrow and Oliktok Point measurement facilities.
Multi-level discriminative dictionary learning with application to large scale image classification.

Science.gov (United States)

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.
Uncertainty quantification of fast sodium current steady-state inactivation for multi-scale models of cardiac electrophysiology.

Science.gov (United States)

Pathmanathan, Pras; Shotwell, Matthew S; Gavaghan, David J; Cordeiro, Jonathan M; Gray, Richard A

2015-01-01

Perhaps the most mature area of multi-scale systems biology is the modelling of the heart. Current models are grounded in over fifty years of research in the development of biophysically detailed models of the electrophysiology (EP) of cardiac cells, but one aspect which is inadequately addressed is the incorporation of uncertainty and physiological variability. Uncertainty quantification (UQ) is the identification and characterisation of the uncertainty in model parameters derived from experimental data, and the computation of the resultant uncertainty in model outputs. It is a necessary tool for establishing the credibility of computational models, and will likely be expected of EP models for future safety-critical clinical applications. The focus of this paper is formal UQ of one major sub-component of cardiac EP models, the steady-state inactivation of the fast sodium current, INa. To better capture average behaviour and quantify variability across cells, we have applied for the first time an 'individual-based' statistical methodology to assess voltage clamp data. Advantages of this approach over a more traditional 'population-averaged' approach are highlighted. The method was used to characterise variability amongst cells isolated from canine epi and endocardium, and this variability was then 'propagated forward' through a canine model to determine the resultant uncertainty in model predictions at different scales, such as of upstroke velocity and spiral wave dynamics. Statistically significant differences between epi and endocardial cells (greater half-inactivation and less steep slope of steady state inactivation curve for endo) was observed, and the forward propagation revealed a lack of robustness of the model to underlying variability, but also surprising robustness to variability at the tissue scale. Overall, the methodology can be used to: (i) better analyse voltage clamp data; (ii) characterise underlying population variability; (iii) investigate
Decadal- to Orbital-Scale Links Between Climate, Productivity and Denitrification on the Peru Margin

Science.gov (United States)

Higginson, M. J.; Altabet, M. A.; Herbert, T. D.

2002-12-01

Denitrification is the predominant global loss term for combined nitrogen and can exert a major control on its oceanic inventory, global productivity and atmospheric CO2. Our prior work demonstrates that proxy records for changing denitrification, oxygenation and productivity in the recent geological past in the Arabian Sea exhibit unprecedented similarity with abrupt climate fluctuations recorded in high-latitude ice-cores. Since the Peru Margin and Arabian Sea together constitute almost two-thirds of global marine water-column denitrification, changes in concert in these two regions could potentially have effected rapid global climate changes through an oceanic mechanism. The Peru Margin is intimately coupled to the Equatorial Pacific, source of El Ni&ño-La Niña SST, productivity and precipitation anomalies. Here, biogeochemical cycles are especially sensitive to abrupt climatic changes on decadal time-scales by virtue of this ENSO coupling. The purpose of our research is to investigate whether longer changes in tropical Pacific oceanography represent a 'scaling up' of anomalous ENSO conditions, modulated by both internal (e.g. nutrient inventory or WPWP heat budget) and external (e.g. orbital) forcing throughout the last glacial/inter-glacial cycle. Here we present first results of a detailed investigation of recently-recovered sediments from ODP Site 1228 on the Peru margin upper continental slope, in an attempt to capture some of the essential aspects of ENSO-like variability. Despite the existing availability of high quality sediment cores from this margin, little detailed paleoclimatic information currently exists because of poor sedimentary carbonate preservation (exacerbated post-recovery) which has limited generation of essential chronostratigraphic controls. Instead, we rely on the development and novel application of compound-specific AMS dating verified and supplemented by intermittent foraminiferal and bulk-carbon AMS dates, a magnetic paleo

Spatial variability of the dose rate from "1"3"7Cs fallout in settlements in Russia and Belarus more than two decades after the Chernobyl accident

International Nuclear Information System (INIS)

Bernhardsson, C.; Rääf, C.L.; Mattsson, S.

2015-01-01

Radionuclides from the 1986 Chernobyl accident were released and dispersed during a limited period of time, but under widely varying weather conditions. As a result, there was a high geographical variation in the deposited radioactive fallout per unit area over Europe, depending on the released composition of fission products and the weather during the 10 days of releases. If the plume from Chernobyl coincided with rain, then the radionuclides were unevenly distributed on the ground. However, large variations in the initial fallout also occurred locally or even on a meter scale. Over the ensuing years the initial deposition may have been altered further by different weathering processes or human activities such as agriculture, gardening, and decontamination measures. Using measurements taken more than two decades after the accident, we report on the inhomogeneous distribution of the ground deposition of the fission product "1"3"7Cs and its influence on the dose rate 1 m above ground, on both large and small scales (10"t"h"s of km"2 – 1 m"2), in the Gomel–Bryansk area close to the border between Belarus and Russia. The dose rate from the deposition was observed to vary by one order of magnitude depending on the size of the area considered, whether human processes were applied to the surface or not, and on location specific properties (e.g. radionuclide migration in soil). - Highlights: • We have surveyed the variability in dose rate after the Chernobyl accident. • A high dose rate variability is observed on both large- and small scales. • The intra-site variability is generally smaller than the inter-site variability. • The variability tend to reduce by human influence on the ground.
Small scale denitrification variability in riparian zones: Results from a high-resolution dataset

Science.gov (United States)

Gassen, Niklas; Knöller, Kay; Musolff, Andreas; Popp, Felix; Lüders, Tillmann; Stumpp, Christine

2017-04-01

Riparian zones are important compartments at the interface between groundwater and surface water where biogeochemical processes like denitrification are often enhanced. Nitrate loads of either groundwater entering a stream through the riparian zone or streamwater infiltrating into the riparian zone can be substantially reduced. These processes are spatially and temporally highly variable, making it difficult to capture solute variabilities, estimate realistic turnover rates and thus to quantify integral mass removal. A crucial step towards a more detailed characterization is to monitor solutes on a scale which adequately resemble the highly heterogeneous distribution and on a scale where processes occur. We measured biogeochemical parameters in a spatial high resolution within a riparian corridor of a German lowland river system over the course of one year. Samples were taken from three newly developed high-resolution multi-level wells with a maximum vertical resolution of 5 cm and analyzed for major ions, DOC and N-O isotopes. Sediment derived during installation of the wells was analyzed for specific denitrifying enzymes. Results showed a distinct depth zonation of hydrochemistry within the shallow alluvial aquifer, with a 1 m thick zone just below the water table with lower nitrate concentrations and EC values similar to the nearby river. Conservative parameters were consistent inbetween the three wells, but nitrate was highly variable. In addition, spots with low nitrate concentrations showed isotopic and microbial evidence for higher denitrification activities. The depth zonation was observed throughout the year, with stronger temporal variations of nitrate concentrations just below the water table compared to deeper layers. Nitrate isotopes showed a clear seasonal trend of denitrification activities (high in summer, low in winter). Our dataset gives new insight into river-groundwater exchange processes and shows the highly heterogeneous distribution of
Large-Scale Multi-Resolution Representations for Accurate Interactive Image and Volume Operations

KAUST Repository

Sicat, Ronell B.

2015-11-25

The resolutions of acquired image and volume data are ever increasing. However, the resolutions of commodity display devices remain limited. This leads to an increasing gap between data and display resolutions. To bridge this gap, the standard approach is to employ output-sensitive operations on multi-resolution data representations. Output-sensitive operations facilitate interactive applications since their required computations are proportional only to the size of the data that is visible, i.e., the output, and not the full size of the input. Multi-resolution representations, such as image mipmaps, and volume octrees, are crucial in providing these operations direct access to any subset of the data at any resolution corresponding to the output. Despite its widespread use, this standard approach has some shortcomings in three important application areas, namely non-linear image operations, multi-resolution volume rendering, and large-scale image exploration. This dissertation presents new multi-resolution representations for large-scale images and volumes that address these shortcomings. Standard multi-resolution representations require low-pass pre-filtering for anti- aliasing. However, linear pre-filters do not commute with non-linear operations. This becomes problematic when applying non-linear operations directly to any coarse resolution levels in standard representations. Particularly, this leads to inaccurate output when applying non-linear image operations, e.g., color mapping and detail-aware filters, to multi-resolution images. Similarly, in multi-resolution volume rendering, this leads to inconsistency artifacts which manifest as erroneous differences in rendering outputs across resolution levels. To address these issues, we introduce the sparse pdf maps and sparse pdf volumes representations for large-scale images and volumes, respectively. These representations sparsely encode continuous probability density functions (pdfs) of multi-resolution pixel
Defect detection in industrial radiography: a multi-scale approach; Detection de defauts en radiographie industrielle: approches multiechelles

Energy Technology Data Exchange (ETDEWEB)

Lefevre, M

1995-10-01

Radiography is used by Electricite de France for pipe inspection in nuclear power plant in order to detect defects. For several years, the RD Division of EDF has undertaken research to define image processing methods well adapted to radiographic images. The main issues raised by these images are their low contrast, their high level of noise, the presence of a trend and the variable size of the defects. A data base of digitized radiographs of pipes has been gathered and the statistical, topological and geometrical properties of all of these images have been analyzed. From this study, a global indicator of the presence of defects and local features, leading to a classification of images into areas with or without defects, have been extracted. The defect localisation problem has been considered in a multi-scale framework based on the creation of a family of images with increasing regularity and defined as a solution of a partial differential equation. From a choice of axioms, a set of equations may be deduced which define various multi-scale analyses. The survey of the properties of such analysed, when applied to images altered with different types of noise, has lead to the selection of the digitized radiographs best adapted multi-scale analysis. The segmentation process, uses the geodesic information attached to defects via connection cost concept. The final decision is based on a summary of the information extracted at several scales. A fuzzy logic approach has been proposed to solve this part. We then developed methods and tools for expertise guidance and validated them on a complete data base of images. Some global indicators have been extracted and a detection and localisation process has been achieved for large defects. (author). 117 refs., 73 figs.
Multi-Time Scale Coordinated Scheduling Strategy with Distributed Power Flow Controllers for Minimizing Wind Power Spillage

Directory of Open Access Journals (Sweden)

Yi Tang

2017-11-01

Full Text Available The inherent variability and randomness of large-scale wind power integration have brought great challenges to power flow control and dispatch. The distributed power flow controller (DPFC has the higher flexibility and capacity in power flow control in the system with wind generation. This paper proposes a multi-time scale coordinated scheduling model with DPFC to minimize wind power spillage. Configuration of DPFCs is initially determined by stochastic method. Afterward, two sequential procedures containing day-head and real-time scales are applied for determining maximum schedulable wind sources, optimal outputs of generating units and operation setting of DPFCs. The generating plan is obtained initially in day-ahead scheduling stage and modified in real-time scheduling model, while considering the uncertainty of wind power and fast operation of DPFC. Numerical simulation results in IEEE-RTS79 system illustrate that wind power is maximum scheduled with the optimal deployment and operation of DPFC, which confirms the applicability and effectiveness of the proposed method.
Multi-scale analysis to uncover habitat use of red-crowned cranes: Implications for conservation

Directory of Open Access Journals (Sweden)

Chunyue LIU, Hongxing JIANG, Shuqing ZHANG, Chunrong LI,Yunqiu HOU, Fawen QIAN

2013-10-01

Full Text Available A multi-scale approach is essential to assess the factors that limit avian habitat use. Numerous studies have examined habitat use by the red-crowned crane, but integrated multi-scale habitat use information is lacking. We evaluated the effects of several habitat variables quantified across many spatial scales on crane use and abundance in two periods (2000 and 2009 at Yancheng National Nature Reserve, China. The natural wetlands decreased in area by 30,601 ha (-6.9% from 2000 to 2009, predominantly as a result of conversion to aquaculture ponds and farmland, and the remaining was under degradation due to expansion of the exotic smooth cordgrass. The cranes are focusing in on either larger patches or those that are in close proximity to each other in both years, but occupied patches had smaller size, less proximity and more regular boundaries in 2009. At landscape scales, the area percentage of common seepweed, reed ponds and paddy fields had a greater positive impact on crane presence than the area percentage of aquaculture ponds. The cranes were more abundant in patches that had a greater percent area of common seepweed and reed ponds, while the percent area of paddy fields was inversely related to crane abundance in 2009 due to changing agricultural practices. In 2009, cranes tended to use less fragmented plots in natural wetlands and more fragmented plots in anthropogenic paddy fields, which were largely associated with the huge loss and degradation of natural habitats between the two years. Management should focus on restoration of large patches of natural wetlands, and formation of a relatively stable area of large paddy field and reed pond to mitigate the loss of natural wetlands [Current Zoology 59 (5: 604–617, 2013].
Systematic approximation of multi-scale Feynman integrals arXiv

CERN Document Server

Borowka, Sophia; Hulme, Daniel

An algorithm for the systematic analytical approximation of multi-scale Feynman integrals is presented. The algorithm produces algebraic expressions as functions of the kinematical parameters and mass scales appearing in the Feynman integrals, allowing for fast numerical evaluation. The results are valid in all kinematical regions, both above and below thresholds, up to in principle arbitrary orders in the dimensional regulator. The scope of the algorithm is demonstrated by presenting results for selected two-loop three-point and four-point integrals with an internal mass scale that appear in the two-loop amplitudes for Higgs+jet production.
Multi-scale process and supply chain modelling: from lignocellulosic feedstock to process and products.

Science.gov (United States)

Hosseini, Seyed Ali; Shah, Nilay

2011-04-06

There is a large body of literature regarding the choice and optimization of different processes for converting feedstock to bioethanol and bio-commodities; moreover, there has been some reasonable technological development in bioconversion methods over the past decade. However, the eventual cost and other important metrics relating to sustainability of biofuel production will be determined not only by the performance of the conversion process, but also by the performance of the entire supply chain from feedstock production to consumption. Moreover, in order to ensure world-class biorefinery performance, both the network and the individual components must be designed appropriately, and allocation of resources over the resulting infrastructure must effectively be performed. The goal of this work is to describe the key challenges in bioenergy supply chain modelling and then to develop a framework and methodology to show how multi-scale modelling can pave the way to answer holistic supply chain questions, such as the prospects for second generation bioenergy crops.
Multi-scale process and supply chain modelling: from lignocellulosic feedstock to process and products

Science.gov (United States)

Hosseini, Seyed Ali; Shah, Nilay

2011-01-01

There is a large body of literature regarding the choice and optimization of different processes for converting feedstock to bioethanol and bio-commodities; moreover, there has been some reasonable technological development in bioconversion methods over the past decade. However, the eventual cost and other important metrics relating to sustainability of biofuel production will be determined not only by the performance of the conversion process, but also by the performance of the entire supply chain from feedstock production to consumption. Moreover, in order to ensure world-class biorefinery performance, both the network and the individual components must be designed appropriately, and allocation of resources over the resulting infrastructure must effectively be performed. The goal of this work is to describe the key challenges in bioenergy supply chain modelling and then to develop a framework and methodology to show how multi-scale modelling can pave the way to answer holistic supply chain questions, such as the prospects for second generation bioenergy crops. PMID:22482032
Multi(scale)gravity: a telescope for the micro-world

International Nuclear Information System (INIS)

Kogan, I.I.

2001-01-01

A short review of modern status of multi-gravity, i.e. modification of gravity at both short and large distances is given. Usually embedding of standard model and general relativity into any multidimensional construction gives rise to all possible sorts of new effects in a micro-world but we can also get a very drastic modification of these laws of gravity at ultra-large scale. One of the reason why multi-gravity can modify CMB (cosmic microwave background) is that it leads to a large distance modification of the curvature. One of very striking features of multi-gravity is that it gives us a some sort of a dark matter whose origin is that it is just matter from other branes. The author shows that on a 5-dimensional case and at large distances, multi-gravity opens a window in extra dimensions and gravitationally matter which is localized on other branes can be felt. (A.C.)
Coralline algal barium as indicator for 20th century northwestern North Atlantic surface ocean freshwater variability.

Science.gov (United States)

Hetzinger, S; Halfar, J; Zack, T; Mecking, J V; Kunz, B E; Jacob, D E; Adey, W H

2013-01-01

During the past decades climate and freshwater dynamics in the northwestern North Atlantic have undergone major changes. Large-scale freshening episodes, related to polar freshwater pulses, have had a strong influence on ocean variability in this climatically important region. However, little is known about variability before 1950, mainly due to the lack of long-term high-resolution marine proxy archives. Here we present the first multidecadal-length records of annually resolved Ba/Ca variations from Northwest Atlantic coralline algae. We observe positive relationships between algal Ba/Ca ratios from two Newfoundland sites and salinity observations back to 1950. Both records capture episodical multi-year freshening events during the 20th century. Variability in algal Ba/Ca is sensitive to freshwater-induced changes in upper ocean stratification, which affect the transport of cold, Ba-enriched deep waters onto the shelf (highly stratified equals less Ba/Ca). Algal Ba/Ca ratios therefore may serve as a new resource for reconstructing past surface ocean freshwater changes.
Multi-scale graphene patterns on arbitrary substrates via laser-assisted transfer-printing process

KAUST Repository

Park, J. B.; Yoo, J.-H.; Grigoropoulos, C. P.

2012-01-01

A laser-assisted transfer-printing process is developed for multi-scale graphene patterns on arbitrary substrates using femtosecond laser scanning on a graphene/metal substrate and transfer techniques without using multi-step patterning processes
Preparation of a large-scale and multi-layer molybdenum crystal and its characteristics

International Nuclear Information System (INIS)

Fujii, Tadayuki

1989-01-01

In the present work, the secondary recrystallization method was applied to obtain a large-scale and multi-layer crystal from a hot-rolled multi-laminated molybdenum sheet doped and stacked alternately with different amounts of dopant. It was found that the time and/or temperature at which secondary recrystallization commence from the multi- layer sheet is strongly dependent on the amounts of dopants. Therefore the potential nucleus of the secondary grain from layers with different amounts of dopant occurred first at the layer with a small amount of dopant and then grew into the layer with a large amount of dopant after an anneal at 1800 0 C-2000 0 C. Consequently a large -scale and multi-layer molybdenum crystal can easily be obtained. 12 refs., 9 figs., 2 tabs. (Author)
South America Monsoon variability on millennial to multi-centennial time scale during the Holocene in central eastern Brazil

Science.gov (United States)

Strikis, N. M.; Cruz, F. W.; Cheng, H.; Karmann, I.; Vuille, M.; Edwards, R.; Wang, X.; Paula, M. S.; Novello, V. F.; Auler, A.

2011-12-01

A paleoprecipitation reconstruction based on high resolution and well-dated speleothem oxygen isotope records shows that the monsoon precipitation over central eastern Brazil underwent to strong variations on millennial to multi-centennial time-scales during the Holocene. This new record indicates that abrupt events of increase in monsoon precipitation are correlated to Bond events 6, 5 and 4 and also with 8.2 ky event during the early and mid-Holocene, with a mean amplitude of 1.5 % (PDB). The pacing and structure of such events are general consistent with variations in solar activity suggested by atmospheric Δ14 C records. In the late-Holocene, abrupt events of increase in monsoon precipitation peaking at 3.2, 2.7 and 2.3 ky B.P. are approximately synchronous with periods of low solar minima. In this regard, the most prominent event occurred during the late Holocene occurred at ~2.7 ky B.P. In addition, these positive anomalies of the precipitation recorded in central eastern Brazil are also in good agreement with variations in Titicaca lake level. The good correspondence between the speleothem and marine records imply that the variations in the north Atlantic sea surface temperature is the main forcing for abrupt millennial to multi-centennial precipitations variation within the region under influence of South American Monsoon.
Toward multi-scale simulation of reconnection phenomena in space plasma

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Den, M.; Horiuchi, R.; Usami, S.; Tanaka, T.; Ogawa, T.; Ohtani, H.

2013-12-01

Magnetic reconnection is considered to play an important role in space phenomena such as substorm in the Earth's magnetosphere. It is well known that magnetic reconnection is controlled by microscopic kinetic mechanism. Frozen-in condition is broken due to particle kinetic effects and collisionless reconnection is triggered when current sheet is compressed as thin as ion kinetic scales under the influence of external driving flow. On the other hand configuration of the magnetic field leading to formation of diffusion region is determined in macroscopic scale and topological change after reconnection is also expressed in macroscopic scale. Thus magnetic reconnection is typical multi-scale phenomenon and microscopic and macroscopic physics are strongly coupled. Recently Horiuchi et al. developed an effective resistivity model based on particle-in-cell (PIC) simulation results obtained in study of collisionless driven reconnection and applied to a global magnetohydrodynamics (MHD) simulation of substorm in the Earth's magnetosphere. They showed reproduction of global behavior in substrom such as dipolarization and flux rope formation by global three dimensional MHD simulation. Usami et al. developed multi-hierarchy simulation model, in which macroscopic and microscopic physics are solved self-consistently and simultaneously. Based on the domain decomposition method, this model consists of three parts: a MHD algorithm for macroscopic global dynamics, a PIC algorithm for microscopic kinetic physics, and an interface algorithm to interlock macro and micro hierarchies. They verified the interface algorithm by simulation of plasma injection flow. In their latest work, this model was applied to collisionless reconnection in an open system and magnetic reconnection was successfully found. In this paper, we describe our approach to clarify multi-scale phenomena and report the current status. Our recent study about extension of the MHD domain to global system is presented. We
Increasing Megadrought Risk at the Intersection of Decadal to Centennial Variability and Climate Change

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Overpeck, J. T.; Parsons, L. A.; Loope, G. R.; Ault, T.; Cole, J. E.; Otto-Bliesner, B. L.; Buckle, N.; Stevenson, S.; Fasullo, J.

2016-12-01

Even more than the 1930's U.S. Dust Bowl Drought, the 20th century Sahel drought stands out as the most unprecedented drought of the instrumental era, in part because it extended over multiple decades. Paleoclimatic evidence makes it clear that this Sahel drought was nonetheless not really unprecedented - droughts many decades long have occurred in sub-Saharan Africa regularly over the last several thousand years, and these constitute what is now increasingly referred to as "megadrought." Paleoclimatic evidence also makes it clear that all drought-prone semi-arid and arid regions of the globe, including southwestern North America, southeastern Australia, and the Mediterranean/Middle Eastern region likely experienced multiple such multidecadal megadroughts in recent pre-Anthropocene Earth history. In other regions of the globe, including parts of South Asia and Amazonia, short but devastating droughts of the last 50-150 years, were also eclipsed in recent Earth history by much more serious megadrought, although these megadroughts were shorter than the multidecadal droughts of Africa or SW North America. In the past, megadroughts have occurred for reasons that are increasingly well understood in terms of ocean-atmosphere dynamics that led to unusually persistent precipitation deficits. Many of these same dynamics are well simulated in state-of-the-art Earth System Models, and yet comparisons between simulated and observed paleohydroclimatic variability suggests the models generally underestimate the risk of megadrought. Paleohydroclimatic records in some cases overestimate drought persistence, but there appear to be other issues at play that need to be better understood and simulated: positive land-atmosphere feedbacks, overly energetic interannual (i.e., ENSO) modes of variability, and insufficient internal multidecadal to centennial coupled climate system variability. Taking these issues and the impact of anthropogenic climate change into account means that the
Describing temporal variability of the mean Estonian precipitation series in climate time scale

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Post, P.; Kärner, O.

2009-04-01

Applicability of the random walk type models to represent the temporal variability of various atmospheric temperature series has been successfully demonstrated recently (e.g. Kärner, 2002). Main problem in the temperature modeling is connected to the scale break in the generally self similar air temperature anomaly series (Kärner, 2005). The break separates short-range strong non-stationarity from nearly stationary longer range variability region. This is an indication of the fact that several geophysical time series show a short-range non-stationary behaviour and a stationary behaviour in longer range (Davis et al., 1996). In order to model series like that the choice of time step appears to be crucial. To characterize the long-range variability we can neglect the short-range non-stationary fluctuations, provided that we are able to model properly the long-range tendencies. The structure function (Monin and Yaglom, 1975) was used to determine an approximate segregation line between the short and the long scale in terms of modeling. The longer scale can be called climate one, because such models are applicable in scales over some decades. In order to get rid of the short-range fluctuations in daily series the variability can be examined using sufficiently long time step. In the present paper, we show that the same philosophy is useful to find a model to represent a climate-scale temporal variability of the Estonian daily mean precipitation amount series over 45 years (1961-2005). Temporal variability of the obtained daily time series is examined by means of an autoregressive and integrated moving average (ARIMA) family model of the type (0,1,1). This model is applicable for daily precipitation simulating if to select an appropriate time step that enables us to neglet the short-range non-stationary fluctuations. A considerably longer time step than one day (30 days) is used in the current paper to model the precipitation time series variability. Each ARIMA (0
A practical scale for Multi-Faceted Organizational Health Climate Assessment.

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Zweber, Zandra M; Henning, Robert A; Magley, Vicki J

2016-04-01

The current study sought to develop a practical scale to measure 3 facets of workplace health climate from the employee perspective as an important component of a healthy organization. The goal was to create a short, usable yet comprehensive scale that organizations and occupational health professionals could use to determine if workplace health interventions were needed. The proposed Multi-faceted Organizational Health Climate Assessment (MOHCA) scale assesses facets that correspond to 3 organizational levels: (a) workgroup, (b) supervisor, and (c) organization. Ten items were developed and tested on 2 distinct samples, 1 cross-organization and 1 within-organization. Exploratory and confirmatory factor analyses yielded a 9-item, hierarchical 3-factor structure. Tests confirmed MOHCA has convergent validity with related constructs, such as perceived organizational support and supervisor support, as well as discriminant validity with safety climate. Lastly, criterion-related validity was found between MOHCA and health-related outcomes. The multi-faceted nature of MOHCA provides a scale that has face validity and can be easily translated into practice, offering a means for diagnosing the shortcomings of an organization or workgroup's health climate to better plan health and well-being interventions. (c) 2016 APA, all rights reserved).
Comparative Analysis of Upper Ocean Heat Content Variability from Ensemble Operational Ocean Analyses

Science.gov (United States)

Xue, Yan; Balmaseda, Magdalena A.; Boyer, Tim; Ferry, Nicolas; Good, Simon; Ishikawa, Ichiro; Rienecker, Michele; Rosati, Tony; Yin, Yonghong; Kumar, Arun

2012-01-01

Upper ocean heat content (HC) is one of the key indicators of climate variability on many time-scales extending from seasonal to interannual to long-term climate trends. For example, HC in the tropical Pacific provides information on thermocline anomalies that is critical for the longlead forecast skill of ENSO. Since HC variability is also associated with SST variability, a better understanding and monitoring of HC variability can help us understand and forecast SST variability associated with ENSO and other modes such as Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), Tropical Atlantic Variability (TAV) and Atlantic Multidecadal Oscillation (AMO). An accurate ocean initialization of HC anomalies in coupled climate models could also contribute to skill in decadal climate prediction. Errors, and/or uncertainties, in the estimation of HC variability can be affected by many factors including uncertainties in surface forcings, ocean model biases, and deficiencies in data assimilation schemes. Changes in observing systems can also leave an imprint on the estimated variability. The availability of multiple operational ocean analyses (ORA) that are routinely produced by operational and research centers around the world provides an opportunity to assess uncertainties in HC analyses, to help identify gaps in observing systems as they impact the quality of ORAs and therefore climate model forecasts. A comparison of ORAs also gives an opportunity to identify deficiencies in data assimilation schemes, and can be used as a basis for development of real-time multi-model ensemble HC monitoring products. The OceanObs09 Conference called for an intercomparison of ORAs and use of ORAs for global ocean monitoring. As a follow up, we intercompared HC variations from ten ORAs -- two objective analyses based on in-situ data only and eight model analyses based on ocean data assimilation systems. The mean, annual cycle, interannual variability and longterm trend of HC have
3D deblending of simultaneous source data based on 3D multi-scale shaping operator

Science.gov (United States)

Zu, Shaohuan; Zhou, Hui; Mao, Weijian; Gong, Fei; Huang, Weilin

2018-04-01

We propose an iterative three-dimensional (3D) deblending scheme using 3D multi-scale shaping operator to separate 3D simultaneous source data. The proposed scheme is based on the property that signal is coherent, whereas interference is incoherent in some domains, e.g., common receiver domain and common midpoint domain. In two-dimensional (2D) blended record, the coherency difference of signal and interference is in only one spatial direction. Compared with 2D deblending, the 3D deblending can take more sparse constraints into consideration to obtain better performance, e.g., in 3D common receiver gather, the coherency difference is in two spatial directions. Furthermore, with different levels of coherency, signal and interference distribute in different scale curvelet domains. In both 2D and 3D blended records, most coherent signal locates in coarse scale curvelet domain, while most incoherent interference distributes in fine scale curvelet domain. The scale difference is larger in 3D deblending, thus, we apply the multi-scale shaping scheme to further improve the 3D deblending performance. We evaluate the performance of 3D and 2D deblending with the multi-scale and global shaping operators, respectively. One synthetic and one field data examples demonstrate the advantage of the 3D deblending with 3D multi-scale shaping operator.

Nonsolvent-assisted fabrication of multi-scaled polylactide as superhydrophobic surfaces.

Science.gov (United States)

Chang, Yafang; Liu, Xuying; Yang, Huige; Zhang, Li; Cui, Zhe; Niu, Mingjun; Liu, Hongzhi; Chen, Jinzhou

2016-03-14

The solution-processing fabrication of superhydrophobic surfaces is currently intriguing, owing to high-efficiency, low cost, and energy-consuming. Here, a facile nonsolvent-assisted process was proposed for the fabrication of the multi-scaled surface roughness in polylactide (PLA) films, thereby resulting in a significant transformation in the surface wettability from intrinsic hydrophilicity to superhydrophobicity. Moreover, it was found that the surface topographical structure of PLA films can be manipulated by varying the compositions of the PLA solutions. And the samples showed superhydrophobic surfaces as well as high melting enthalpy and crystallinity. In particular, a high contact angle of 155.8° together with a high adhesive force of 184 μN was yielded with the assistance of a multi-nonsolvent system, which contributed to the co-existence of micro-/nano-scale hierarchical structures.
The Pacific Ventilated Thermocline and its Influence on the Pacific Decadal Oscillation and Global Warming

Science.gov (United States)

Kuntz, L.; Schrag, D. P.

2017-12-01

Over the past century, global surface temperatures have warmed episodically despite relatively steady increases in radiative forcing. Coincident with these transitions, we identify changes in the structure of the ventilated thermocline in the Pacific as well as changes in the intensity of the equatorial undercurrent. We propose a new mechanism for the Pacific Decadal Oscillation that involves oscillations in the strength of the equatorial undercurrent and may explain multi-decadal variability of global temperatures. We suggest that the oscillation results in a greater or lesser volume of cold water reaching the eastern Pacific, which ultimately leads to a change in the heat flux out of this critical region. By varying the heat flux in the tropical Pacific in model simulations, we reproduce a stepwise pattern of warming that resembles the historical climate record without additional variability in forcing. In addition, the trajectory of the changes in thermocline structure that we now observe in the Pacific looks like it will arrive at the equator in the middle of the next decade, suggesting that the current period of reduced warming (aka "hiatus") will persist through the mid-2020s.
Diverse multi-decadal changes in streamflow within a rapidly urbanizing region

Science.gov (United States)

Diem, Jeremy E.; Hill, T. Chee; Milligan, Richard A.

2018-01-01

The impact of urbanization on streamflow depends on a variety of factors (e.g., climate, initial land cover, inter-basin transfers, water withdrawals, wastewater effluent, etc.). The purpose of this study is to examine trends in streamflow from 1986 to 2015 in a range of watersheds within the rapidly urbanizing Atlanta, GA metropolitan area. This study compares eight watersheds over three decades, while minimizing the influence of inter-annual precipitation variability. Population and land-cover data were used to analyze changes over approximately twenty years within the watersheds. Precipitation totals for the watersheds were estimated using precipitation totals at nearby weather stations. Multiple streamflow variables, such as annual streamflow, frequencies of high-flow days (HFDs), flashiness, and precipitation-adjusted streamflow, for the eight streams were calculated using daily streamflow data. Variables were tested for significant trends from 1986 to 2015 and significant differences between 1986-2000 and 2001-2015. Flashiness increased for all streams without municipal water withdrawals, and the four watersheds with the largest increase in developed land had significant increases in flashiness. Significant positive trends in precipitation-adjusted mean annual streamflow and HFDs occurred for the two watersheds (Big Creek and Suwanee Creek) that experienced the largest increases in development, and these were the only watersheds that went from majority forest land in 1986 to majority developed land in 2015. With a disproportionate increase in HFD occurrence during summer, Big Creek and Suwannee Creek also had a reduction in intra-annual variability of HFD occurrence. Watersheds that were already substantially developed at the beginning of the period and did not have wastewater discharge had declining streamflow. The most urbanized watershed (Peachtree Creek) had a significant decrease in streamflow, and a possible cause of the decrease was increasing
Industrial applications of multi-functional, multi-phase reactors

NARCIS (Netherlands)

Harmsen, G.J.; Chewter, L.A.

1999-01-01

To reveal trends in the design and operation of multi-functional, multi-phase reactors, this paper describes, in historical sequence, three industrial applications of multi-functional, multi-phase reactors developed and operated by Shell Chemicals during the last five decades. For each case, we
Multivariate Multi-Scale Permutation Entropy for Complexity Analysis of Alzheimer’s Disease EEG

Directory of Open Access Journals (Sweden)

Isabella Palamara

2012-07-01

Full Text Available An original multivariate multi-scale methodology for assessing the complexity of physiological signals is proposed. The technique is able to incorporate the simultaneous analysis of multi-channel data as a unique block within a multi-scale framework. The basic complexity measure is done by using Permutation Entropy, a methodology for time series processing based on ordinal analysis. Permutation Entropy is conceptually simple, structurally robust to noise and artifacts, computationally very fast, which is relevant for designing portable diagnostics. Since time series derived from biological systems show structures on multiple spatial-temporal scales, the proposed technique can be useful for other types of biomedical signal analysis. In this work, the possibility of distinguish among the brain states related to Alzheimer’s disease patients and Mild Cognitive Impaired subjects from normal healthy elderly is checked on a real, although quite limited, experimental database.
Multi-scale sampling to evaluate assemblage dynamics in an oceanic marine reserve.

Science.gov (United States)

Thompson, Andrew R; Watson, William; McClatchie, Sam; Weber, Edward D

2012-01-01

To resolve the capacity of Marine Protected Areas (MPA) to enhance fish productivity it is first necessary to understand how environmental conditions affect the distribution and abundance of fishes independent of potential reserve effects. Baseline fish production was examined from 2002-2004 through ichthyoplankton sampling in a large (10,878 km(2)) Southern Californian oceanic marine reserve, the Cowcod Conservation Area (CCA) that was established in 2001, and the Southern California Bight as a whole (238,000 km(2) CalCOFI sampling domain). The CCA assemblage changed through time as the importance of oceanic-pelagic species decreased between 2002 (La Niña) and 2003 (El Niño) and then increased in 2004 (El Niño), while oceanic species and rockfishes displayed the opposite pattern. By contrast, the CalCOFI assemblage was relatively stable through time. Depth, temperature, and zooplankton explained more of the variability in assemblage structure at the CalCOFI scale than they did at the CCA scale. CalCOFI sampling revealed that oceanic species impinged upon the CCA between 2002 and 2003 in association with warmer offshore waters, thus explaining the increased influence of these species in the CCA during the El Nino years. Multi-scale, spatially explicit sampling and analysis was necessary to interpret assemblage dynamics in the CCA and likely will be needed to evaluate other focal oceanic marine reserves throughout the world.
Advances in Understanding Decadal Climate Variability

Science.gov (United States)

Busalacchi, Antonio J.

1999-01-01

Recently, a joint Brazil-France-U.S. program, known as PIRATA (Pilot Research moored Array in the Tropical Atlantic), was proposed to begin the deployment of moored measurement platforms in the tropical Atlantic in order to enhance the existing observational data base and subsequent understanding of the processes by which the ocean and atmosphere couple in key regions of the tropical Atlantic Ocean. Empirical studies have suggested that there are strong relationships between tropical Atlantic upper ocean variability, SST, ocean-atmosphere coupling and regional climate variability. During the early 1980's a coordinated set of surface wind, subsurface thermal structure, and subsurface current observations were obtained as part of the U.S.-France SEQUAL-FOCAL process experiment designed to observe the seasonal response of the tropical Atlantic Ocean to surface forcing. Since that time, however, the observational data base for the tropical Atlantic Ocean has disintegrated to a few ship-tracks measuring ocean temperatures and a small collection of tide gauge stations measuring sea level. A more comprehensive set of observations, modeling and empirical studies is now in order to make progress on understanding the regional climate variability. The proposed PIRATA program will use mooring platforms similar to the tropical Pacific Ocean TAO array to measure surface fluxes of momentum and heat and the corresponding changes in the upper ocean thermal structure. It is anticipated that the oceanic data from this monitoring array will also be used in a predictive mode for initialization studies of regional coupled climate models. Of particular interest are zonal and meridional modes of ocean-atmosphere variability within the tropical Atlantic basin that have significant impacts on the regional climate of the bordering continents.
Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

Energy Technology Data Exchange (ETDEWEB)

Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States). Dept. of Oceanography; Cassano, John J. [Univ. of Colorado, Boulder, CO (United States); Gutowski, Jr., William J. [Iowa State Univ., Ames, IA (United States); Lipscomb, William H. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nijssen, Bart [Univ. of Washington, Seattle, WA (United States); Roberts, Andrew [Naval Postgraduate School, Monterey, CA (United States). Dept. of Oceanography; Robertson, William [Univ. of Texas, El Paso, TX (United States); Tulaczyk, Slawek [Univ. of California, Santa Cruz, CA (United States); Zeng, Xubin [Univ. of Arizona, Tucson, AZ (United States)

2011-05-15

The primary outcome of the project was the development of the Regional Arctic System Model (RASM) and evaluation of its individual model components, coupling among them and fully coupled model results. Overall, we have demonstrated that RASM produces realistic mean and seasonal surface climate as well as its interannual and decadal variability and trends.
Ecosystem stability in space: α, β and γ variability.

Science.gov (United States)

Wang, Shaopeng; Loreau, Michel

2014-08-01

The past two decades have seen great progress in understanding the mechanisms of ecosystem stability in local ecological systems. There is, however, an urgent need to extend existing knowledge to larger spatial scales to match the scale of management and conservation. Here, we develop a general theoretical framework to study the stability and variability of ecosystems at multiple scales. Analogously to the partitioning of biodiversity, we propose the concepts of alpha, beta and gamma variability. Gamma variability at regional (metacommunity) scale can be partitioned into local alpha variability and spatial beta variability, either multiplicatively or additively. On average, variability decreases from local to regional scales, which creates a negative variability-area relationship. Our partitioning framework suggests that mechanisms of regional ecosystem stability can be understood by investigating the influence of ecological factors on alpha and beta variability. Diversity can provide insurance effects at the various levels of variability, thus generating alpha, beta and gamma diversity-stability relationships. As a consequence, the loss of biodiversity and habitat impairs ecosystem stability at the regional scale. Overall, our framework enables a synthetic understanding of ecosystem stability at multiple scales and has practical implications for landscape management. © 2014 John Wiley & Sons Ltd/CNRS.
Mapping transient hyperventilation induced alterations with estimates of the multi-scale dynamics of BOLD signal.

Directory of Open Access Journals (Sweden)

Vesa J Kiviniemi

2009-07-01

Full Text Available Temporal blood oxygen level dependent (BOLD contrast signals in functional MRI during rest may be characterized by power spectral distribution (PSD trends of the form 1/f α. Trends with 1/f characteristics comprise fractal properties with repeating oscillation patterns in multiple time scales. Estimates of the fractal properties enable the quantification of phenomena that may otherwise be difficult to measure, such as transient, non-linear changes. In this study it was hypothesized that the fractal metrics of 1/f BOLD signal trends can map changes related to dynamic, multi-scale alterations in cerebral blood flow (CBF after a transient hyperventilation challenge. Twenty-three normal adults were imaged in a resting-state before and after hyperventilation. Different variables (1/f trend constant α, fractal dimension Df, and, Hurst exponent H characterizing the trends were measured from BOLD signals. The results show that fractal metrics of the BOLD signal follow the fractional Gaussian noise model, even during the dynamic CBF change that follows hyperventilation. The most dominant effect on the fractal metrics was detected in grey matter, in line with previous hyperventilation vaso-reactivity studies. The α was able to differentiate also blood vessels from grey matter changes. Df was most sensitive to grey matter. H correlated with default mode network areas before hyperventilation but this pattern vanished after hyperventilation due to a global increase in H. In the future, resting-state fMRI combined with fractal metrics of the BOLD signal may be used for analyzing multi-scale alterations of cerebral blood flow.
Mapping Transient Hyperventilation Induced Alterations with Estimates of the Multi-Scale Dynamics of BOLD Signal.

Science.gov (United States)

Kiviniemi, Vesa; Remes, Jukka; Starck, Tuomo; Nikkinen, Juha; Haapea, Marianne; Silven, Olli; Tervonen, Osmo

2009-01-01

Temporal blood oxygen level dependent (BOLD) contrast signals in functional MRI during rest may be characterized by power spectral distribution (PSD) trends of the form 1/f(alpha). Trends with 1/f characteristics comprise fractal properties with repeating oscillation patterns in multiple time scales. Estimates of the fractal properties enable the quantification of phenomena that may otherwise be difficult to measure, such as transient, non-linear changes. In this study it was hypothesized that the fractal metrics of 1/f BOLD signal trends can map changes related to dynamic, multi-scale alterations in cerebral blood flow (CBF) after a transient hyperventilation challenge. Twenty-three normal adults were imaged in a resting-state before and after hyperventilation. Different variables (1/f trend constant alpha, fractal dimension D(f), and, Hurst exponent H) characterizing the trends were measured from BOLD signals. The results show that fractal metrics of the BOLD signal follow the fractional Gaussian noise model, even during the dynamic CBF change that follows hyperventilation. The most dominant effect on the fractal metrics was detected in grey matter, in line with previous hyperventilation vaso-reactivity studies. The alpha was able to differentiate also blood vessels from grey matter changes. D(f) was most sensitive to grey matter. H correlated with default mode network areas before hyperventilation but this pattern vanished after hyperventilation due to a global increase in H. In the future, resting-state fMRI combined with fractal metrics of the BOLD signal may be used for analyzing multi-scale alterations of cerebral blood flow.
Impact of the initialisation on the predictability of the Southern Ocean sea ice at interannual to multi-decadal timescales

Science.gov (United States)

Zunz, Violette; Goosse, Hugues; Dubinkina, Svetlana

2015-04-01

In this study, we assess systematically the impact of different initialisation procedures on the predictability of the sea ice in the Southern Ocean. These initialisation strategies are based on three data assimilation methods: the nudging, the particle filter with sequential importance resampling and the nudging proposal particle filter. An Earth system model of intermediate complexity is used to perform hindcast simulations in a perfect model approach. The predictability of the Antarctic sea ice at interannual to multi-decadal timescales is estimated through two aspects: the spread of the hindcast ensemble, indicating the uncertainty of the ensemble, and the correlation between the ensemble mean and the pseudo-observations, used to assess the accuracy of the prediction. Our results show that at decadal timescales more sophisticated data assimilation methods as well as denser pseudo-observations used to initialise the hindcasts decrease the spread of the ensemble. However, our experiments did not clearly demonstrate that one of the initialisation methods systematically provides with a more accurate prediction of the sea ice in the Southern Ocean than the others. Overall, the predictability at interannual timescales is limited to 3 years ahead at most. At multi-decadal timescales, the trends in sea ice extent computed over the time period just after the initialisation are clearly better correlated between the hindcasts and the pseudo-observations if the initialisation takes into account the pseudo-observations. The correlation reaches values larger than 0.5 in winter. This high correlation has likely its origin in the slow evolution of the ocean ensured by its strong thermal inertia, showing the importance of the quality of the initialisation below the sea ice.
Multi-scale multi-physics computational chemistry simulation based on ultra-accelerated quantum chemical molecular dynamics method for structural materials in boiling water reactor

International Nuclear Information System (INIS)

Miyamoto, Akira; Sato, Etsuko; Sato, Ryo; Inaba, Kenji; Hatakeyama, Nozomu

2014-01-01

In collaboration with experimental experts we have reported in the present conference (Hatakeyama, N. et al., “Experiment-integrated multi-scale, multi-physics computational chemistry simulation applied to corrosion behaviour of BWR structural materials”) the results of multi-scale multi-physics computational chemistry simulations applied to the corrosion behaviour of BWR structural materials. In macro-scale, a macroscopic simulator of anode polarization curve was developed to solve the spatially one-dimensional electrochemical equations on the material surface in continuum level in order to understand the corrosion behaviour of typical BWR structural material, SUS304. The experimental anode polarization behaviours of each pure metal were reproduced by fitting all the rates of electrochemical reactions and then the anode polarization curve of SUS304 was calculated by using the same parameters and found to reproduce the experimental behaviour successfully. In meso-scale, a kinetic Monte Carlo (KMC) simulator was applied to an actual-time simulation of the morphological corrosion behaviour under the influence of an applied voltage. In micro-scale, an ultra-accelerated quantum chemical molecular dynamics (UA-QCMD) code was applied to various metallic oxide surfaces of Fe 2 O 3 , Fe 3 O 4 , Cr 2 O 3 modelled as same as water molecules and dissolved metallic ions on the surfaces, then the dissolution and segregation behaviours were successfully simulated dynamically by using UA-QCMD. In this paper we describe details of the multi-scale, multi-physics computational chemistry method especially the UA-QCMD method. This method is approximately 10,000,000 times faster than conventional first-principles molecular dynamics methods based on density-functional theory (DFT), and the accuracy was also validated for various metals and metal oxides compared with DFT results. To assure multi-scale multi-physics computational chemistry simulation based on the UA-QCMD method for
Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

Energy Technology Data Exchange (ETDEWEB)

Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States)

2016-10-17

This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate through polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.
Taking the pulse of mountains: Ecosystem responses to climatic variability

Science.gov (United States)

Fagre, Daniel B.; Peterson, David L.; Hessl, Amy E.

2003-01-01

An integrated program of ecosystem modeling and field studies in the mountains of the Pacific Northwest (U.S.A.) has quantified many of the ecological processes affected by climatic variability. Paleoecological and contemporary ecological data in forest ecosystems provided model parameterization and validation at broad spatial and temporal scales for tree growth, tree regeneration and treeline movement. For subalpine tree species, winter precipitation has a strong negative correlation with growth; this relationship is stronger at higher elevations and west-side sites (which have more precipitation). Temperature affects tree growth at some locations with respect to length of growing season (spring) and severity of drought at drier sites (summer). Furthermore, variable but predictable climate-growth relationships across elevation gradients suggest that tree species respond differently to climate at different locations, making a uniform response of these species to future climatic change unlikely. Multi-decadal variability in climate also affects ecosystem processes. Mountain hemlock growth at high-elevation sites is negatively correlated with winter snow depth and positively correlated with the winter Pacific Decadal Oscillation (PDO) index. At low elevations, the reverse is true. Glacier mass balance and fire severity are also linked to PDO. Rapid establishment of trees in subalpine ecosystems during this century is increasing forest cover and reducing meadow cover at many subalpine locations in the western U.S.A. and precipitation (snow depth) is a critical variable regulating conifer expansion. Lastly, modeling potential future ecosystem conditions suggests that increased climatic variability will result in increasing forest fire size and frequency, and reduced net primary productivity in drier, east-side forest ecosystems. As additional empirical data and modeling output become available, we will improve our ability to predict the effects of climatic change
Multi-species coral Sr/Ca-based sea-surface temperature reconstruction using Orbicella faveolata and Siderastrea siderea from the Florida Straits

Science.gov (United States)

Flannery, Jennifer A.; Richey, Julie N.; Thirumalai, Kaustubh; Poore, Richard Z.; DeLong, Kristine L.

2017-01-01

We present new, monthly-resolved Sr/Ca-based sea-surface temperature (SST) records from two species of massive coral, Orbicella faveolata and Siderastrea siderea, from the Dry Tortugas National Park, FL, USA (DTNP). We combine these new records with published data from three additional S. siderea coral colonies to generate a 278-year long multi-species stacked Sr/Ca-SST record from DTNP. The composite record of mean annual Sr/Ca-SST at DTNP shows pronounced decadal-scale variability with a range of 1 to 2°C. Notable cool intervals in the Sr/Ca-derived SST lasting about a decade centered at ~1845, ~1935, and ~1965 are associated with reduced summer Sr/Ca-SST (monthly maxima < 29°C), and imply a reduction in the spatial extent of the Atlantic Warm Pool (AWP). There is significant coherence between the composite DTNP Sr/Ca-SST record and the Atlantic Multidecadal Oscillation (AMO) index, with the AMO lagging Sr/Ca-SST at DTNP by 9 years. Low frequency variability in the Gulf Stream surface transport, which originates near DTNP, may provide a link for the lagged relationship between multidecadal variability at DTNP and the AMO.
Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.

Directory of Open Access Journals (Sweden)

Guangwei Gao

Full Text Available In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.
Collaborative Research: Quantifying the Uncertainties of Aerosol Indirect Effects and Impacts on Decadal-Scale Climate Variability in NCAR CAM5 and CESM1

Energy Technology Data Exchange (ETDEWEB)

Nenes, Athanasios [Georgia Inst. of Technology, Atlanta, GA (United States)

2017-06-23

The goal of this proposed project is to assess the climatic importance and sensitivity of aerosol indirect effect (AIE) to cloud and aerosol processes and feedbacks, which include organic aerosol hygroscopicity, cloud condensation nuclei (CCN) activation kinetics, Giant CCN, cloud-scale entrainment, ice nucleation in mixed-phase and cirrus clouds, and treatment of subgrid variability of vertical velocity. A key objective was to link aerosol, cloud microphysics and dynamics feedbacks in CAM5 with a suite of internally consistent and integrated parameterizations that provide the appropriate degrees of freedom to capture the various aspects of the aerosol indirect effect. The proposal integrated new parameterization elements into the cloud microphysics, moist turbulence and aerosol modules used by the NCAR Community Atmospheric Model version 5 (CAM5). The CAM5 model was then used to systematically quantify the uncertainties of aerosol indirect effects through a series of sensitivity tests with present-day and preindustrial aerosol emissions. New parameterization elements were developed as a result of these efforts, and new diagnostic tools & methodologies were also developed to quantify the impacts of aerosols on clouds and climate within fully coupled models. Observations were used to constrain key uncertainties in the aerosol-cloud links. Advanced sensitivity tools were developed and implements to probe the drivers of cloud microphysical variability with unprecedented temporal and spatial scale. All these results have been published in top and high impact journals (or are in the final stages of publication). This proposal has also supported a number of outstanding graduate students.
A Method of Vector Map Multi-scale Representation Considering User Interest on Subdivision Gird

Directory of Open Access Journals (Sweden)

YU Tong

2016-12-01

Full Text Available Compared with the traditional spatial data model and method, global subdivision grid show a great advantage in the organization and expression of massive spatial data. In view of this, a method of vector map multi-scale representation considering user interest on subdivision gird is proposed. First, the spatial interest field is built using a large number POI data to describe the spatial distribution of the user interest in geographic information. Second, spatial factor is classified and graded, and its representation scale range can be determined. Finally, different levels of subdivision surfaces are divided based on GeoSOT subdivision theory, and the corresponding relation of subdivision level and scale is established. According to the user interest of subdivision surfaces, the spatial feature can be expressed in different degree of detail. It can realize multi-scale representation of spatial data based on user interest. The experimental results show that this method can not only satisfy general-to-detail and important-to-secondary space cognitive demands of users, but also achieve better multi-scale representation effect.
A Framework for Parallel Numerical Simulations on Multi-Scale Geometries

KAUST Repository

Varduhn, Vasco

2012-06-01

In this paper, an approach on performing numerical multi-scale simulations on fine detailed geometries is presented. In particular, the focus lies on the generation of sufficient fine mesh representations, whereas a resolution of dozens of millions of voxels is inevitable in order to sufficiently represent the geometry. Furthermore, the propagation of boundary conditions is investigated by using simulation results on the coarser simulation scale as input boundary conditions on the next finer scale. Finally, the applicability of our approach is shown on a two-phase simulation for flooding scenarios in urban structures running from a city wide scale to a fine detailed in-door scale on feature rich building geometries. © 2012 IEEE.

Multi-infill strategy for kriging models used in variable fidelity optimization

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Chao SONG

2018-03-01

Full Text Available In this paper, a computationally efficient optimization method for aerodynamic design has been developed. The low-fidelity model and the multi-infill strategy are utilized in this approach. Low-fidelity data is employed to provide a good global trend for model prediction, and multiple sample points chosen by different infill criteria in each updating cycle are used to enhance the exploitation and exploration ability of the optimization approach. Take the advantages of low-fidelity model and the multi-infill strategy, and no initial sample for the high-fidelity model is needed. This approach is applied to an airfoil design case and a high-dimensional wing design case. It saves a large number of high-fidelity function evaluations for initial model construction. What’s more, faster reduction of an aerodynamic function is achieved, when compared to ordinary kriging using the multi-infill strategy and variable-fidelity model using single infill criterion. The results indicate that the developed approach has a promising application to efficient aerodynamic design when high-fidelity analyses are involved. Keywords: Aerodynamics, Infill criteria, Kriging models, Multi-infill, Optimization
Multi-scale carbon micro/nanofibers-based adsorbents for protein immobilization

Energy Technology Data Exchange (ETDEWEB)

Singh, Shiv; Singh, Abhinav [Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Bais, Vaibhav Sushil Singh; Prakash, Balaji [Department of Biological Science and Bioengineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Verma, Nishith, E-mail: nishith@iitk.ac.in [Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Center for Environmental Science and Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India)

2014-05-01

In the present study, different proteins, namely, bovine serum albumin (BSA), glucose oxidase (GOx) and the laboratory purified YqeH were immobilized in the phenolic resin precursor-based multi-scale web of activated carbon microfibers (ACFs) and carbon nanofibers (CNFs). These biomolecules are characteristically different from each other, having different structure, number of parent amino acid molecules and isoelectric point. CNF was grown on ACF substrate by chemical vapor deposition, using Ni nanoparticles (Nps) as the catalyst. The ultra-sonication of the CNFs was carried out in acidic medium to remove Ni Nps from the tip of the CNFs to provide additional active sites for adsorption. The prepared material was directly used as an adsorbent for proteins, without requiring any additional treatment. Several analytical techniques were used to characterize the prepared materials, including scanning electron microscopy, Fourier transform infrared spectroscopy, BET surface area, pore-size distribution, and UV–vis spectroscopy. The adsorption capacities of prepared ACFs/CNFs in this study were determined to be approximately 191, 39 and 70 mg/g for BSA, GOx and YqeH, respectively, revealing that the carbon micro-nanofibers forming synthesized multi-scale web are efficient materials for the immobilization of protein molecules. - Highlights: • Ni metal Np-dispersed carbon micro-nanofibers (ACFs/CNFs) are prepared. • ACFs/CNFs are mesoporous. • Significant adsorption of BSA, GOx and YqeH is observed on ACFs/CNFs. • Multi-scale web of ACFs/CNFs is effective for protein immobilization.
Assessment of Arctic and Antarctic sea ice predictability in CMIP5 decadal hindcasts

Directory of Open Access Journals (Sweden)

C.-Y. Yang

2016-10-01

Full Text Available This paper examines the ability of coupled global climate models to predict decadal variability of Arctic and Antarctic sea ice. We analyze decadal hindcasts/predictions of 11 Coupled Model Intercomparison Project Phase 5 (CMIP5 models. Decadal hindcasts exhibit a large multi-model spread in the simulated sea ice extent, with some models deviating significantly from the observations as the predicted ice extent quickly drifts away from the initial constraint. The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, for most models, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Sea ice extent in the North Pacific has better predictive skill than that in the North Atlantic (particularly at a lead time of 3–7 years, but there is a re-emerging predictive skill in the North Atlantic at a lead time of 6–8 years. In contrast to the Arctic, Antarctic sea ice decadal hindcasts do not show broad predictive skill at any timescales, and there is no obvious improvement linking the areal extent of significant predictive skill to lead time increase. This might be because nearly all the models predict a retreating Antarctic sea ice cover, opposite to the observations. For the Arctic, the predictive skill of the multi-model ensemble mean outperforms most models and the persistence prediction at longer timescales, which is not the case for the Antarctic. Overall, for the Arctic, initialized decadal hindcasts show improved predictive skill compared to uninitialized simulations, although this improvement is not present in the Antarctic.
R Package multiPIM: A Causal Inference Approach to Variable Importance Analysis

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Stephan J Ritter

2014-04-01

Full Text Available We describe the R package multiPIM, including statistical background, functionality and user options. The package is for variable importance analysis, and is meant primarily for analyzing data from exploratory epidemiological studies, though it could certainly be applied in other areas as well. The approach taken to variable importance comes from the causal inference field, and is different from approaches taken in other R packages. By default, multiPIM uses a double robust targeted maximum likelihood estimator (TMLE of a parameter akin to the attributable risk. Several regression methods/machine learning algorithms are available for estimating the nuisance parameters of the models, including super learner, a meta-learner which combines several different algorithms into one. We describe a simulation in which the double robust TMLE is compared to the graphical computation estimator. We also provide example analyses using two data sets which are included with the package.
Multidecadal Variability in Surface Albedo Feedback Across CMIP5 Models

Science.gov (United States)

Schneider, Adam; Flanner, Mark; Perket, Justin

2018-02-01

Previous studies quantify surface albedo feedback (SAF) in climate change, but few assess its variability on decadal time scales. Using the Coupled Model Intercomparison Project Version 5 (CMIP5) multimodel ensemble data set, we calculate time evolving SAF in multiple decades from surface albedo and temperature linear regressions. Results are meaningful when temperature change exceeds 0.5 K. Decadal-scale SAF is strongly correlated with century-scale SAF during the 21st century. Throughout the 21st century, multimodel ensemble mean SAF increases from 0.37 to 0.42 W m-2 K-1. These results suggest that models' mean decadal-scale SAFs are good estimates of their century-scale SAFs if there is at least 0.5 K temperature change. Persistent SAF into the late 21st century indicates ongoing capacity for Arctic albedo decline despite there being less sea ice. If the CMIP5 multimodel ensemble results are representative of the Earth, we cannot expect decreasing Arctic sea ice extent to suppress SAF in the 21st century.
Analytical Solutions for Multi-Time Scale Fractional Stochastic Differential Equations Driven by Fractional Brownian Motion and Their Applications

OpenAIRE

Xiao-Li Ding; Juan J. Nieto

2018-01-01

In this paper, we investigate analytical solutions of multi-time scale fractional stochastic differential equations driven by fractional Brownian motions. We firstly decompose homogeneous multi-time scale fractional stochastic differential equations driven by fractional Brownian motions into independent differential subequations, and give their analytical solutions. Then, we use the variation of constant parameters to obtain the solutions of nonhomogeneous multi-time scale fractional stochast...
Long time scale hard X-ray variability in Seyfert 1 galaxies

Science.gov (United States)

Markowitz, Alex Gary

This dissertation examines the relationship between long-term X-ray variability characteristics, black hole mass, and luminosity of Seyfert 1 Active Galactic Nuclei. High dynamic range power spectral density functions (PSDs) have been constructed for six Seyfert 1 galaxies. These PSDs show "breaks" or characteristic time scales, typically on the order of a few days. There is resemblance to PSDs of lower-mass Galactic X-ray binaries (XRBs), with the ratios of putative black hole masses and variability time scales approximately the same (106--7) between the two classes of objects. The data are consistent with a linear correlation between Seyfert PSD break time scale and black hole mass estimate; the relation extrapolates reasonably well over 6--7 orders of magnitude to XRBs. All of this strengthens the case for a physical similarity between Seyfert galaxies and XRBs. The first six years of RXTE monitoring of Seyfert 1s have been systematically analyzed to probe hard X-ray variability on multiple time scales in a total of 19 Seyfert is in an expansion of the survey of Markowitz & Edelson (2001). Correlations between variability amplitude, luminosity, and black hole mass are explored, the data support the model of PSD movement with black hole mass suggested by the PSD survey. All of the continuum variability results are consistent with relatively more massive black holes hosting larger X-ray emission regions, resulting in 'slower' observed variability. Nearly all sources in the sample exhibit stronger variability towards softer energies, consistent with softening as they brighten. Direct time-resolved spectral fitting has been performed on continuous RXTE monitoring of seven Seyfert is to study long-term spectral variability and Fe Kalpha variability characteristics. The Fe Kalpha line displays a wide range of behavior but varies less strongly than the broadband continuum. Overall, however, there is no strong evidence for correlated variability between the line and
Using decadal climate prediction to characterize and manage changing drought and flood risks in Colorado

Science.gov (United States)

Lazrus, H.; Done, J.; Morss, R. E.

2017-12-01

A new branch of climate science, known as decadal prediction, seeks to predict the time-varying trajectory of climate over the next 3-30 years and not just the longer-term trends. Decadal predictions bring climate information into the time horizon of decision makers, particularly those tasked with managing water resources and floods whose master planning is often on the timescale of decades. Information from decadal predictions may help alleviate some aspects of vulnerability by helping to inform decisions that reduce drought and flood exposure and increase adaptive capacities including preparedness, response, and recovery. This presentation will highlight an interdisciplinary project - involving atmospheric and social scientists - on the development of decadal climate information and its use in decision making. The presentation will explore the skill and utility of decadal drought and flood prediction along Colorado's Front Range, an area experiencing rapid population growth and uncertain climate variability and climate change impacts. Innovative statistical and dynamical atmospheric modeling techniques explore the extent to which Colorado precipitation can be predicted on decadal scales using remote Pacific Ocean surface temperature patterns. Concurrently, stakeholder interviews with flood managers in Colorado are being used to explore the potential utility of decadal climate information. Combining the modeling results with results from the stakeholder interviews shows that while there is still significant uncertainty surrounding precipitation on decadal time scales, relevant and well communicated decadal information has potential to be useful for drought and flood management.
Heterogeneous Multi-Robot System for Mapping Environmental Variables of Greenhouses.

Science.gov (United States)

Roldán, Juan Jesús; Garcia-Aunon, Pablo; Garzón, Mario; de León, Jorge; Del Cerro, Jaime; Barrientos, Antonio

2016-07-01

The productivity of greenhouses highly depends on the environmental conditions of crops, such as temperature and humidity. The control and monitoring might need large sensor networks, and as a consequence, mobile sensory systems might be a more suitable solution. This paper describes the application of a heterogeneous robot team to monitor environmental variables of greenhouses. The multi-robot system includes both ground and aerial vehicles, looking to provide flexibility and improve performance. The multi-robot sensory system measures the temperature, humidity, luminosity and carbon dioxide concentration in the ground and at different heights. Nevertheless, these measurements can be complemented with other ones (e.g., the concentration of various gases or images of crops) without a considerable effort. Additionally, this work addresses some relevant challenges of multi-robot sensory systems, such as the mission planning and task allocation, the guidance, navigation and control of robots in greenhouses and the coordination among ground and aerial vehicles. This work has an eminently practical approach, and therefore, the system has been extensively tested both in simulations and field experiments.
Heterogeneous Multi-Robot System for Mapping Environmental Variables of Greenhouses

Directory of Open Access Journals (Sweden)

Juan Jesús Roldán

2016-07-01

Full Text Available The productivity of greenhouses highly depends on the environmental conditions of crops, such as temperature and humidity. The control and monitoring might need large sensor networks, and as a consequence, mobile sensory systems might be a more suitable solution. This paper describes the application of a heterogeneous robot team to monitor environmental variables of greenhouses. The multi-robot system includes both ground and aerial vehicles, looking to provide flexibility and improve performance. The multi-robot sensory system measures the temperature, humidity, luminosity and carbon dioxide concentration in the ground and at different heights. Nevertheless, these measurements can be complemented with other ones (e.g., the concentration of various gases or images of crops without a considerable effort. Additionally, this work addresses some relevant challenges of multi-robot sensory systems, such as the mission planning and task allocation, the guidance, navigation and control of robots in greenhouses and the coordination among ground and aerial vehicles. This work has an eminently practical approach, and therefore, the system has been extensively tested both in simulations and field experiments.
Multi-scale modelling and numerical simulation of electronic kinetic transport

International Nuclear Information System (INIS)

Duclous, R.

2009-11-01

This research thesis which is at the interface between numerical analysis, plasma physics and applied mathematics, deals with the kinetic modelling and numerical simulations of the electron energy transport and deposition in laser-produced plasmas, having in view the processes of fuel assembly to temperature and density conditions necessary to ignite fusion reactions. After a brief review of the processes at play in the collisional kinetic theory of plasmas, with a focus on basic models and methods to implement, couple and validate them, the author focuses on the collective aspect related to the free-streaming electron transport equation in the non-relativistic limit as well as in the relativistic regime. He discusses the numerical development and analysis of the scheme for the Vlasov-Maxwell system, and the selection of a validation procedure and numerical tests. Then, he investigates more specific aspects of the collective transport: the multi-specie transport, submitted to phase-space discontinuities. Dealing with the multi-scale physics of electron transport with collision source terms, he validates the accuracy of a fast Monte Carlo multi-grid solver for the Fokker-Planck-Landau electron-electron collision operator. He reports realistic simulations for the kinetic electron transport in the frame of the shock ignition scheme, the development and validation of a reduced electron transport angular model. He finally explores the relative importance of the processes involving electron-electron collisions at high energy by means a multi-scale reduced model with relativistic Boltzmann terms
Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

Energy Technology Data Exchange (ETDEWEB)

Robertson, William [Univ. of Texas, El Paso, TX (United States)

2016-11-18

RASM is a multi-disciplinary project, which brings together researchers from six state universities, one military postgraduate school, and one DoE laboratory to address the core modeling objectives of the arctic research community articulated in the Arctic System Modeling report by Roberts et al. (2010b). This report advocates the construction of a regional downscaling tool to generate probabilistic decadal projections of Greenland ice sheet retreat, evolution of arctic sea ice cover, changes in land surface vegetation, and regional processes leading to arctic amplification. Unified coupled models such as RASM are ideal for this purpose because they simulate fine-scale physics, essential for the realistic representation of intra-annual variability, in addition to processes fundamental to long term climatic shifts (Hurrell et al. 2009). By using RASM with boundary conditions from a global model, we can generate many-member ensembles essential for understanding uncertainty in regional climate projections (Hawkins and Sutton 2009). This probabilistic approach is computationally prohibitive for high-resolution global models in the foreseeable future, and also for regional models interactively nested within global simulations. Yet it is fundamental for quantifying uncertainty in decadal forecasts to make them useful for decision makers (Doherty et al. 2009). For this reason, we have targeted development of ensemble generation techniques as a core project task (Task 4.5). Environmental impact assessment specialists need high-fidelity regional ensemble projections to improve the accuracy of their work (Challinor et al. 2009; Moss et al. 2010). This is especially true of the Arctic, where economic, social and national interests are rapidly reshaping the high north in step with regional climate change. During the next decade, considerable oil and gas discoveries are expected across many parts of the marine and terrestrial Arctic (Gautier et al. 2009), the economics of the
Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes

Science.gov (United States)

Ghosh, Subimal; Vittal, H.; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K. S.; Dhanesh, Y.; Sudheer, K. P.; Gunthe, S. S.

2016-01-01

India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins. PMID:27463092
Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes.

Directory of Open Access Journals (Sweden)

Subimal Ghosh

Full Text Available India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.
Multi-scale path planning for reduced environmental impact of aviation

Science.gov (United States)

Campbell, Scot Edward

A future air traffic management system capable of rerouting aircraft trajectories in real-time in response to transient and evolving events would result in increased aircraft efficiency, better utilization of the airspace, and decreased environmental impact. Mixed-integer linear programming (MILP) is used within a receding horizon framework to form aircraft trajectories which mitigate persistent contrail formation, avoid areas of convective weather, and seek a minimum fuel solution. Areas conducive to persistent contrail formation and areas of convective weather occur at disparate temporal and spatial scales, and thereby require the receding horizon controller to be adaptable to multi-scale events. In response, a novel adaptable receding horizon controller was developed to account for multi-scale disturbances, as well as generate trajectories using both a penalty function approach for obstacle penetration and hard obstacle avoidance constraints. A realistic aircraft fuel burn model based on aircraft data and engine performance simulations is used to form the cost function in the MILP optimization. The performance of the receding horizon algorithm is tested through simulation. A scalability analysis of the algorithm is conducted to ensure the tractability of the path planner. The adaptable receding horizon algorithm is shown to successfully negotiate multi-scale environments with performance exceeding static receding horizon solutions. The path planner is applied to realistic scenarios involving real atmospheric data. A single flight example for persistent contrail mitigation shows that fuel burn increases 1.48% when approximately 50% of persistent contrails are avoided, but 6.19% when 100% of persistent contrails are avoided. Persistent contrail mitigating trajectories are generated for multiple days of data, and the research shows that 58% of persistent contrails are avoided with a 0.48% increase in fuel consumption when averaged over a year.
A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data.

Science.gov (United States)

Mo, Qianxing; Shen, Ronglai; Guo, Cui; Vannucci, Marina; Chan, Keith S; Hilsenbeck, Susan G

2018-01-01

Identification of clinically relevant tumor subtypes and omics signatures is an important task in cancer translational research for precision medicine. Large-scale genomic profiling studies such as The Cancer Genome Atlas (TCGA) Research Network have generated vast amounts of genomic, transcriptomic, epigenomic, and proteomic data. While these studies have provided great resources for researchers to discover clinically relevant tumor subtypes and driver molecular alterations, there are few computationally efficient methods and tools for integrative clustering analysis of these multi-type omics data. Therefore, the aim of this article is to develop a fully Bayesian latent variable method (called iClusterBayes) that can jointly model omics data of continuous and discrete data types for identification of tumor subtypes and relevant omics features. Specifically, the proposed method uses a few latent variables to capture the inherent structure of multiple omics data sets to achieve joint dimension reduction. As a result, the tumor samples can be clustered in the latent variable space and relevant omics features that drive the sample clustering are identified through Bayesian variable selection. This method significantly improve on the existing integrative clustering method iClusterPlus in terms of statistical inference and computational speed. By analyzing TCGA and simulated data sets, we demonstrate the excellent performance of the proposed method in revealing clinically meaningful tumor subtypes and driver omics features. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Final Progress Report submitted via the DOE Energy Link (E-Link) in June 2009 [Collaborative Research: Decadal-to-Centennial Climate & Climate Change Studies with Enhanced Variable and Uniform Resolution GCMs Using Advanced Numerical Techniques

Energy Technology Data Exchange (ETDEWEB)

Fox-Rabinovitz, Michael S. [Univ. of Quebec (Canada); Cote, Jean [Univ. of Quebec (Canada)

2009-10-09

The joint U.S-Canadian project has been devoted to: (a) decadal climate studies using developed state-of-the-art GCMs (General Circulation Models) with enhanced variable and uniform resolution; (b) development and implementation of advanced numerical techniques; (c) research in parallel computing and associated numerical methods; (d) atmospheric chemistry experiments related to climate issues; (e) validation of regional climate modeling strategies for nested- and stretched-grid models. The variable-resolution stretched-grid (SG) GCMs produce accurate and cost-efficient regional climate simulations with mesoscale resolution. The advantage of the stretched grid approach is that it allows us to preserve the high quality of both global and regional circulations while providing consistent interactions between global and regional scales and phenomena. The major accomplishment for the project has been the successful international SGMIP-1 and SGMIP-2 (Stretched-Grid Model Intercomparison Project, phase-1 and phase-2) based on this research developments and activities. The SGMIP provides unique high-resolution regional and global multi-model ensembles beneficial for regional climate modeling and broader modeling community. The U.S SGMIP simulations have been produced using SciDAC ORNL supercomputers. The results of the successful SGMIP multi-model ensemble simulations of the U.S. climate are available at the SGMIP web site (http://essic.umd.edu/~foxrab/sgmip.html) and through the link to the WMO/WCRP/WGNE web site: http://collaboration.cmc.ec.gc.ca/science/wgne. Collaborations with other international participants M. Deque (Meteo-France) and J. McGregor (CSIRO, Australia) and their centers and groups have been beneficial for the strong joint effort, especially for the SGMIP activities. The WMO/WCRP/WGNE endorsed the SGMIP activities in 2004-2008. This project reflects a trend in the modeling and broader communities to move towards regional and sub-regional assessments and
Nonlinear dynamics of the complex multi-scale network

Science.gov (United States)

Makarov, Vladimir V.; Kirsanov, Daniil; Goremyko, Mikhail; Andreev, Andrey; Hramov, Alexander E.

2018-04-01

In this paper, we study the complex multi-scale network of nonlocally coupled oscillators for the appearance of chimera states. Chimera is a special state in which, in addition to the asynchronous cluster, there are also completely synchronous parts in the system. We show that the increase of nodes in subgroups leads to the destruction of the synchronous interaction within the common ring and to the narrowing of the chimera region.
Multi-scale dynamic modeling of atmospheric pollution in urban environment

International Nuclear Information System (INIS)

Thouron, Laetitia

2017-01-01

Urban air pollution has been identified as an important cause of health impacts, including premature deaths. In particular, ambient concentrations of gaseous pollutants such as nitrogen dioxide (NO 2 ) and particulate matter (PM10 and PM2.5) are regulated, which means that emission reduction strategies must be put in place to reduce these concentrations in places where the corresponding regulations are not respected. Besides, air pollution can contribute to the contamination of other media, for example through the contribution of atmospheric deposition to runoff contamination. The multifactorial and multi-scale aspects of urban make the pollution sources difficult to identify. Indeed, the urban environment is a heterogeneous space characterized by complex architectural structures (old buildings alongside a more modern building, residential, commercial, industrial zones, roads, etc.), non-uniform atmospheric pollutant emissions and therefore the population exposure to pollution is variable in space and time. The modeling of urban air pollution aims to understand the origin of pollutants, their spatial extent and their concentration/deposition levels. Some pollutants have long residence times and can stay several weeks in the atmosphere (PM2.5) and therefore be transported over long distances, while others are more local (NO x in the vicinity of traffic). The spatial distribution of a pollutant will therefore depend on several factors, and in particular on the surfaces encountered. Air quality depends strongly on weather, buildings (canyon-street) and emissions. The aim of this thesis is to address some of these aspects by modeling: (1) urban background pollution with a transport-chemical model (Polyphemus / POLAIR3D), which makes it possible to estimate atmospheric pollutants by type of urban surfaces (roofs, walls and roadways), (2) street-level pollution by explicitly integrating the effects of the building in a three-dimensional way with a multi-scale model of
The benefits of global scaling in multi-criteria decision analysis

Directory of Open Access Journals (Sweden)

Jamie P. Monat

2009-10-01

Full Text Available When there are multiple competing objectives in a decision-making process, Multi-Attribute Choice scoring models are excellent tools, permitting the incorporation of both subjective and objective attributes. However, their accuracy depends upon the subjective techniques used to construct the attribute scales and their concomitant weights. Conventional techniques using local scales tend to overemphasize small differences in attribute measures, which may yield erroneous conclusions. The Range Sensitivity Principle (RSP is often invoked to adjust attribute weights when local scales are used. In practice, however, decision makers often do not follow the prescriptions of the Range Sensitivity Principle and under-adjust the weights, resulting in potentially poor decisions. Examples are discussed as is a proposed solution: the use of global scales instead of local scales.

Climatic controls of the interannual to decadal variability in Saudi Arabian dust activity: Towards the development of a seasonal prediction tool

Science.gov (United States)

Yu, Y.; Notaro, M.; Liu, Z.; Alkolibi, F.; Fadda, E.; Bakhrjy, F.

2013-12-01

Atmospheric dust significantly influences the climate system, as well as human life in Saudi Arabia. Skillful seasonal prediction of dust activity with climatic variables will help prevent some negative social impacts of dust storms. Yet, the climatic regulators on Saudi Arabian dust activity remain largely unaddressed. Remote sensing and station observations show consistent seasonal cycles in Saudi Arabian dust activity, which peaks in spring and summer. The climatic controls on springtime and summertime Saudi Arabian dust activity during 1975-2010 are studied using observational and reanalysis data. Empirical Orthogonal Function (EOF) of the observed Saudi Arabian dust storm frequency shows a dominant homogeneous pattern across the country, which has distinct interannual and decadal variations, as revealed by the power spectrum. Regression and correlation analyses reveal that Saudi Arabian dust activity is largely tied to precipitation on the Arabian Peninsula in spring and northwesterly (Shamal) wind in summer. On the seasonal-interannual time scale, warm El Niño-Southern Oscillation (ENSO) phase (El Niño) in winter-to-spring inhibits spring dust activity by increasing the precipitation over the Rub'al Khali Desert, a major dust source region on the southern Arabian Peninsula; warm ENSO and warm Indian Ocean Basin Mode (IOBM) in winter-to-spring favor less summer dust activity by producing anomalously low sea-level pressure over eastern north Africa and Arabian Peninsula, which leads to the reduced Shamal wind speed. The decadal variation in dust activity is likely associated with the Atlantic Multidecadal Oscillation (AMO), which impacts Sahel rainfall and North African dust, and likely dust transport to Saudi Arabia. The Pacific Decadal Oscillation (PDO) and tropical Indian Ocean SST also have influence on the decadal variation in Saudi Arabian dust activity, by altering precipitation over the Arabian Peninsula and summer Shamal wind speed. Using eastern
Variability of the raindrop size distribution at small spatial scales

Science.gov (United States)

Berne, A.; Jaffrain, J.

2010-12-01

Because of the interactions between atmospheric turbulence and cloud microphysics, the raindrop size distribution (DSD) is strongly variable in space and time. The spatial variability of the DSD at small spatial scales (below a few km) is not well documented and not well understood, mainly because of a lack of adequate measurements at the appropriate resolutions. A network of 16 disdrometers (Parsivels) has been designed and set up over EPFL campus in Lausanne, Switzerland. This network covers a typical operational weather radar pixel of 1x1 km2. The question of the significance of the variability of the DSD at such small scales is relevant for radar remote sensing of rainfall because the DSD is often assumed to be uniform within a radar sample volume and because the Z-R relationships used to convert the measured radar reflectivity Z into rain rate R are usually derived from point measurements. Thanks to the number of disdrometers, it was possible to quantify the spatial variability of the DSD at the radar pixel scale and to show that it can be significant. In this contribution, we show that the variability of the total drop concentration, of the median volume diameter and of the rain rate are significant, taking into account the sampling uncertainty associated with disdrometer measurements. The influence of this variability on the Z-R relationship can be non-negligible. Finally, the spatial structure of the DSD is quantified using a geostatistical tool, the variogram, and indicates high spatial correlation within a radar pixel.
A novel fruit shape classification method based on multi-scale analysis

Science.gov (United States)

Gui, Jiangsheng; Ying, Yibin; Rao, Xiuqin

2005-11-01

Shape is one of the major concerns and which is still a difficult problem in automated inspection and sorting of fruits. In this research, we proposed the multi-scale energy distribution (MSED) for object shape description, the relationship between objects shape and its boundary energy distribution at multi-scale was explored for shape extraction. MSED offers not only the mainly energy which represent primary shape information at the lower scales, but also subordinate energy which represent local shape information at higher differential scales. Thus, it provides a natural tool for multi resolution representation and can be used as a feature for shape classification. We addressed the three main processing steps in the MSED-based shape classification. They are namely, 1) image preprocessing and citrus shape extraction, 2) shape resample and shape feature normalization, 3) energy decomposition by wavelet and classification by BP neural network. Hereinto, shape resample is resample 256 boundary pixel from a curve which is approximated original boundary by using cubic spline in order to get uniform raw data. A probability function was defined and an effective method to select a start point was given through maximal expectation, which overcame the inconvenience of traditional methods in order to have a property of rotation invariants. The experiment result is relatively well normal citrus and serious abnormality, with a classification rate superior to 91.2%. The global correct classification rate is 89.77%, and our method is more effective than traditional method. The global result can meet the request of fruit grading.
Multi-scale window specification over streaming trajectories

Directory of Open Access Journals (Sweden)

Kostas Patroumpas

2013-12-01

Full Text Available Enormous amounts of positional information are collected by monitoring applications in domains such as fleet management, cargo transport, wildlife protection, etc. With the advent of modern location-based services, processing such data mostly focuses on providing real-time response to a variety of user requests in continuous and scalable fashion. An important class of such queries concerns evolving trajectories that continuously trace the streaming locations of moving objects, like GPS-equipped vehicles, commodities with RFID's, people with smartphones etc. In this work, we propose an advanced windowing operator that enables online, incremental examination of recent motion paths at multiple resolutions for numerous point entities. When applied against incoming positions, this window can abstract trajectories at coarser representations towards the past, while retaining progressively finer features closer to the present. We explain the semantics of such multi-scale sliding windows through parameterized functions that reflect the sequential nature of trajectories and can effectively capture their spatiotemporal properties. Such window specification goes beyond its usual role for non-blocking processing of multiple concurrent queries. Actually, it can offer concrete subsequences from each trajectory, thus preserving continuity in time and contiguity in space along the respective segments. Further, we suggest language extensions in order to express characteristic spatiotemporal queries using windows. Finally, we discuss algorithms for nested maintenance of multi-scale windows and evaluate their efficiency against streaming positional data, offering empirical evidence of their benefits to online trajectory processing.
Sensitivity of Water Scarcity Events to ENSO-Driven Climate Variability at the Global Scale

Science.gov (United States)

Veldkamp, T. I. E.; Eisner, S.; Wada, Y.; Aerts, J. C. J. H.; Ward, P. J.

2015-01-01

Globally, freshwater shortage is one of the most dangerous risks for society. Changing hydro-climatic and socioeconomic conditions have aggravated water scarcity over the past decades. A wide range of studies show that water scarcity will intensify in the future, as a result of both increased consumptive water use and, in some regions, climate change. Although it is well-known that El Niño- Southern Oscillation (ENSO) affects patterns of precipitation and drought at global and regional scales, little attention has yet been paid to the impacts of climate variability on water scarcity conditions, despite its importance for adaptation planning. Therefore, we present the first global-scale sensitivity assessment of water scarcity to ENSO, the most dominant signal of climate variability. We show that over the time period 1961-2010, both water availability and water scarcity conditions are significantly correlated with ENSO-driven climate variability over a large proportion of the global land area (> 28.1 %); an area inhabited by more than 31.4% of the global population. We also found, however, that climate variability alone is often not enough to trigger the actual incidence of water scarcity events. The sensitivity of a region to water scarcity events, expressed in terms of land area or population exposed, is determined by both hydro-climatic and socioeconomic conditions. Currently, the population actually impacted by water scarcity events consists of 39.6% (CTA: consumption-to-availability ratio) and 41.1% (WCI: water crowding index) of the global population, whilst only 11.4% (CTA) and 15.9% (WCI) of the global population is at the same time living in areas sensitive to ENSO-driven climate variability. These results are contrasted, however, by differences in growth rates found under changing socioeconomic conditions, which are relatively high in regions exposed to water scarcity events. Given the correlations found between ENSO and water availability and scarcity
Pyrodiversity promotes avian diversity over the decade following forest fire.

Science.gov (United States)

Tingley, Morgan W; Ruiz-Gutiérrez, Viviana; Wilkerson, Robert L; Howell, Christine A; Siegel, Rodney B

2016-10-12

An emerging hypothesis in fire ecology is that pyrodiversity increases species diversity. We test whether pyrodiversity-defined as the standard deviation of fire severity-increases avian biodiversity at two spatial scales, and whether and how this relationship may change in the decade following fire. We use a dynamic Bayesian community model applied to a multi-year dataset of bird surveys at 1106 points sampled across 97 fires in montane California. Our results provide strong support for a positive relationship between pyrodiversity and bird diversity. This relationship interacts with time since fire, with pyrodiversity having a greater effect on biodiversity at 10 years post-fire than at 1 year post-fire. Immediately after fires, patches of differing burn severities hold similar bird communities, but over the ensuing decade, bird assemblages within patches of contrasting severities differentiate. When evaluated at the scale of individual fires, fires with a greater heterogeneity of burn severities hold substantially more species. High spatial heterogeneity in severity, sometimes called 'mixed-severity fire', is a natural part of wildfire regimes in western North America, but may be jeopardized by climate change and a legacy of fire suppression. Forest management that encourages mixed-severity fire may be critical for sustaining biodiversity across fire-prone landscapes. © 2016 The Author(s).
Multi-GNSS PPP-RTK: From Large- to Small-Scale Networks

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Nandakumaran Nadarajah

2018-04-01

Full Text Available Precise point positioning (PPP and its integer ambiguity resolution-enabled variant, PPP-RTK (real-time kinematic, can benefit enormously from the integration of multiple global navigation satellite systems (GNSS. In such a multi-GNSS landscape, the positioning convergence time is expected to be reduced considerably as compared to the one obtained by a single-GNSS setup. It is therefore the goal of the present contribution to provide numerical insights into the role taken by the multi-GNSS integration in delivering fast and high-precision positioning solutions (sub-decimeter and centimeter levels using PPP-RTK. To that end, we employ the Curtin PPP-RTK platform and process data-sets of GPS, BeiDou Navigation Satellite System (BDS and Galileo in stand-alone and combined forms. The data-sets are collected by various receiver types, ranging from high-end multi-frequency geodetic receivers to low-cost single-frequency mass-market receivers. The corresponding stations form a large-scale (Australia-wide network as well as a small-scale network with inter-station distances less than 30 km. In case of the Australia-wide GPS-only ambiguity-float setup, 90% of the horizontal positioning errors (kinematic mode are shown to become less than five centimeters after 103 min. The stated required time is reduced to 66 min for the corresponding GPS + BDS + Galieo setup. The time is further reduced to 15 min by applying single-receiver ambiguity resolution. The outcomes are supported by the positioning results of the small-scale network.
Geomagnetic field and length-of-day fluctuations at decadal and subdecadal time scales. A plea for looking beyond the atmosphere for partners in Earth's rotation

Science.gov (United States)

Demetrescu, C.; Dobrica, V.; Stefan, C.

2017-12-01

A rich scientific literature is linking length-of-day (LOD) fluctuations to geomagnetic field and flow oscillations in the fluid outer core. We demostrate that the temporal evolution of the geomagnetic field shows the existence of several oscillations at decadal, inter-decadal, and sub-centennial time scales that superimpose on a so-called inter-centennial constituent. We show that while the subcentennial oscillations of the geomagnetic field, produced by torsional oscillations in the core, could be linked to oscillations of LOD at a similar time scale, the oscillations at decadal and sub-decadal time scales, of external origin, can be found in LOD too. We discuss these issues from the perspective of long time-span main field models (gufm1 - Jackson et al., 2000; COV-OBS - Gillet et al., 2013) that are used to retrieve time series of geomagnetic elements in a 2.5x2.5° network. The decadal and sub-decadal constituents of the time series of annual values in LOD and geomagnetic field were separated in the cyclic component of a Hodrick-Prescott filtering applied to data, and shown to highly correlate to variations of external sources such as the magnetospheric ring current.
Multi-Scale Dissemination of Time Series Data

DEFF Research Database (Denmark)

Guo, Qingsong; Zhou, Yongluan; Su, Li

2013-01-01

In this paper, we consider the problem of continuous dissemination of time series data, such as sensor measurements, to a large number of subscribers. These subscribers fall into multiple subscription levels, where each subscription level is specified by the bandwidth constraint of a subscriber......, which is an abstract indicator for both the physical limits and the amount of data that the subscriber would like to handle. To handle this problem, we propose a system framework for multi-scale time series data dissemination that employs a typical tree-based dissemination network and existing time...
Multi-scale sampling to evaluate assemblage dynamics in an oceanic marine reserve.

Directory of Open Access Journals (Sweden)

Andrew R Thompson

Full Text Available To resolve the capacity of Marine Protected Areas (MPA to enhance fish productivity it is first necessary to understand how environmental conditions affect the distribution and abundance of fishes independent of potential reserve effects. Baseline fish production was examined from 2002-2004 through ichthyoplankton sampling in a large (10,878 km(2 Southern Californian oceanic marine reserve, the Cowcod Conservation Area (CCA that was established in 2001, and the Southern California Bight as a whole (238,000 km(2 CalCOFI sampling domain. The CCA assemblage changed through time as the importance of oceanic-pelagic species decreased between 2002 (La Niña and 2003 (El Niño and then increased in 2004 (El Niño, while oceanic species and rockfishes displayed the opposite pattern. By contrast, the CalCOFI assemblage was relatively stable through time. Depth, temperature, and zooplankton explained more of the variability in assemblage structure at the CalCOFI scale than they did at the CCA scale. CalCOFI sampling revealed that oceanic species impinged upon the CCA between 2002 and 2003 in association with warmer offshore waters, thus explaining the increased influence of these species in the CCA during the El Nino years. Multi-scale, spatially explicit sampling and analysis was necessary to interpret assemblage dynamics in the CCA and likely will be needed to evaluate other focal oceanic marine reserves throughout the world.
Impacts of Climate Variability on Latin American Small-scale Fisheries

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Omar Defeo

2013-12-01

Full Text Available Small-scale fisheries (SSFs are social-ecological systems that play a critical role in terms of food security and poverty alleviation in Latin America. These fisheries are increasingly threatened by anthropogenic and climatic drivers acting at multiple scales. We review the effects of climate variability on Latin American SSFs, and discuss the combined effects of two additional human drivers: globalization of markets and governance. We show drastic long-term and large-scale effects of climate variability, e.g., sea surface temperature anomalies, wind intensity, sea level, and climatic indices, on SSFs. These variables, acting in concert with economic drivers, have exacerbated stock depletion rates in Latin American SSFs. The impact of these drivers varied according to the life cycle and latitudinal distribution of the target species, the characteristics of the oceanographic systems, and the inherent features of the social systems. Our review highlights the urgent need to improve management and governance systems to promote resilience as a way to cope with the increasing uncertainty about the impacts of climate and globalization of markets on Latin American SSFs.
Spatial Downscaling of TRMM Precipitation Using Geostatistics and Fine Scale Environmental Variables

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No-Wook Park

2013-01-01

Full Text Available A geostatistical downscaling scheme is presented and can generate fine scale precipitation information from coarse scale Tropical Rainfall Measuring Mission (TRMM data by incorporating auxiliary fine scale environmental variables. Within the geostatistical framework, the TRMM precipitation data are first decomposed into trend and residual components. Quantitative relationships between coarse scale TRMM data and environmental variables are then estimated via regression analysis and used to derive trend components at a fine scale. Next, the residual components, which are the differences between the trend components and the original TRMM data, are then downscaled at a target fine scale via area-to-point kriging. The trend and residual components are finally added to generate fine scale precipitation estimates. Stochastic simulation is also applied to the residual components in order to generate multiple alternative realizations and to compute uncertainty measures. From an experiment using a digital elevation model (DEM and normalized difference vegetation index (NDVI, the geostatistical downscaling scheme generated the downscaling results that reflected detailed characteristics with better predictive performance, when compared with downscaling without the environmental variables. Multiple realizations and uncertainty measures from simulation also provided useful information for interpretations and further environmental modeling.
The Cea multi-scale and multi-physics simulation project for nuclear applications

International Nuclear Information System (INIS)

Ledermann, P.; Chauliac, C.; Thomas, J.B.

2005-01-01

Full text of publication follows. Today numerical modelling is everywhere recognized as an essential tool of capitalization, integration and share of knowledge. For this reason, it becomes the central tool of research. Until now, the Cea developed a set of scientific software allowing to model, in each situation, the operation of whole or part of a nuclear installation and these codes are largely used in nuclear industry. However, for the future, it is essential to aim for a better accuracy, a better control of uncertainties and better performance in computing times. The objective is to obtain validated models allowing accurate predictive calculations for actual complex nuclear problems such as fuel behaviour in accidental situation. This demands to master a large and interactive set of phenomena ranging from nuclear reaction to heat transfer. To this end, Cea, with industrial partners (EDF, Framatome-ANP, ANDRA) has designed an integrated platform of calculation, devoted to the study of nuclear systems, and intended at the same time for industries and scientists. The development of this platform is under way with the start in 2005 of the integrated project NURESIM, with 18 European partners. Improvement is coming not only through a multi-scale description of all phenomena but also through an innovative design approach requiring deep functional analysis which is upstream from the development of the simulation platform itself. In addition, the studies of future nuclear systems are increasingly multidisciplinary (simultaneous modelling of core physics, thermal-hydraulics and fuel behaviour). These multi-physics and multi-scale aspects make mandatory to pay very careful attention to software architecture issues. A global platform is thus developed integrating dedicated specialized platforms: DESCARTES for core physics, NEPTUNE for thermal-hydraulics, PLEIADES for fuel behaviour, SINERGY for materials behaviour under irradiation, ALLIANCES for the performance
Spatial and Temporal Variability in Biogenic Gas Accumulation and Release in The Greater Everglades at Multiple Scales of Measurement

Science.gov (United States)

McClellan, M. D.; Cornett, C.; Schaffer, L.; Comas, X.

2017-12-01

Wetlands play a critical role in the carbon (C) cycle by producing and releasing significant amounts of greenhouse biogenic gasses (CO2, CH4) into the atmosphere. Wetlands in tropical and subtropical climates (such as the Florida Everglades) have become of great interest in the past two decades as they account for more than 20% of the global peatland C stock and are located in climates that favor year-round C emissions. Despite the increase in research involving C emission from these types of wetlands, the spatial and temporal variability involving C production, accumulation and release is still highly uncertain, and is the focus of this research at multiple scales of measurement (i.e. lab, field and landscape). Spatial variability in biogenic gas content, build up and release, at both the lab and field scales, was estimated using a series of ground penetrating radar (GPR) surveys constrained with gas traps fitted with time-lapse cameras. Variability in gas content was estimated at the sub-meter scale (lab scale) within two extracted monoliths from different wetland ecosystems at the Disney wilderness Preserve (DWP) and the Blue Cypress Preserve (BCP) using high frequency GPR (1.2 GHz) transects across the monoliths. At the field scale (> 10m) changes in biogenic gas content were estimated using 160 MHz GPR surveys collected within 4 different emergent wetlands at the DWP. Additionally, biogenic gas content from the extracted monoliths was used to developed a landscape comparison of C accumulation and emissions for each different wetland ecosystem. Changes in gas content over time were estimated at the lab scale at high temporal resolution (i.e. sub-hourly) in monoliths from the BCP and Water Conservation Area 1-A. An autonomous rail system was constructed to estimate biogenic gas content variability within the wetland soil matrix using a series of continuous, uninterrupted 1.2 GHz GPR transects along the samples. Measurements were again constrained with an array
Multi scales based sparse matrix spectral clustering image segmentation

Science.gov (United States)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.
Improving plot- and regional-scale crop models for simulating impacts of climate variability and extremes

Science.gov (United States)

Tao, F.; Rötter, R.

2013-12-01

Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for
Sea Level Trend and Variability in the Straits of Singapore and Malacca

Science.gov (United States)

Luu, Q.; Tkalich, P.

2013-12-01

The Straits of Singapore and Malacca (SSM) connect the Andaman Sea located northeast of the Indian Ocean to the South China Sea, the largest marginal sea situated in the tropical Pacific Ocean. Consequently, sea level in the SSM is assumed to be governed by various regional phenomena associated with the adjacent parts of Indian and Pacific Oceans. At annual scale sea level variability is dominant by the Asian monsoon. Interannual sea level signals are modulated by the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). In the long term, regional sea level is driven by the global climate change. However, relative impacts of these multi-scale phenomena on regional sea level in the SSM are yet to be quantified. In present study, publicly available tide gauge records and satellite altimetry data are used to derive long-term sea level trend and variability in SSM. We used the data from research-quality stations, including four located in the Singapore Strait (Tanjong Pagar, Raffles Lighthouse, Sultan Shoal and Sembawang) and seven situated in the Malacca Strait (Kelang, Keling, Kukup, Langkawji, Lumut, Penang and Ko Taphao Noi), each one having 25-39 year data up to the year 2011. Harmonic analysis is performed to filter out astronomic tides from the tide gauge records when necessary; and missing data are reconstructed using identified relationships between sea level and the governing phenomena. The obtained sea level anomalies (SLAs) and reconstructed mean sea level are then validated against satellite altimetry data from AVISO. At multi-decadal scale, annual measured sea level in the SSM is varying with global mean sea level, rising for the period 1984-2009 at the rate 1.8-2.3 mm/year in the Singapore Strait and 1.1-2.8 mm/year in the Malacca Strait. Interannual regional sea level drops are associated with El Niño events, while the rises are correlated with La Niña episodes; both variations are in the range of ×5 cm with correlation coefficient
MULTI-SCALE SEGMENTATION OF HIGH RESOLUTION REMOTE SENSING IMAGES BY INTEGRATING MULTIPLE FEATURES

Directory of Open Access Journals (Sweden)

Y. Di

2017-05-01

Full Text Available Most of multi-scale segmentation algorithms are not aiming at high resolution remote sensing images and have difficulty to communicate and use layers’ information. In view of them, we proposes a method of multi-scale segmentation of high resolution remote sensing images by integrating multiple features. First, Canny operator is used to extract edge information, and then band weighted distance function is built to obtain the edge weight. According to the criterion, the initial segmentation objects of color images can be gained by Kruskal minimum spanning tree algorithm. Finally segmentation images are got by the adaptive rule of Mumford–Shah region merging combination with spectral and texture information. The proposed method is evaluated precisely using analog images and ZY-3 satellite images through quantitative and qualitative analysis. The experimental results show that the multi-scale segmentation of high resolution remote sensing images by integrating multiple features outperformed the software eCognition fractal network evolution algorithm (highest-resolution network evolution that FNEA on the accuracy and slightly inferior to FNEA on the efficiency.
Prediction of Coal Face Gas Concentration by Multi-Scale Selective Ensemble Hybrid Modeling

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WU Xiang

2014-06-01

Full Text Available A selective ensemble hybrid modeling prediction method based on wavelet transformation is proposed to improve the fitting and generalization capability of the existing prediction models of the coal face gas concentration, which has a strong stochastic volatility. Mallat algorithm was employed for the multi-scale decomposition and single-scale reconstruction of the gas concentration time series. Then, it predicted every subsequence by sparsely weighted multi unstable ELM(extreme learning machine predictor within method SERELM(sparse ensemble regressors of ELM. At last, it superimposed the predicted values of these models to obtain the predicted values of the original sequence. The proposed method takes advantage of characteristics of multi scale analysis of wavelet transformation, accuracy and fast characteristics of ELM prediction and the generalization ability of L1 regularized selective ensemble learning method. The results show that the forecast accuracy has large increase by using the proposed method. The average relative error is 0.65%, the maximum relative error is 4.16% and the probability of relative error less than 1% reaches 0.785.
Multi-scale modeling of inter-granular fracture in UO2

Energy Technology Data Exchange (ETDEWEB)

Chakraborty, Pritam [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhang, Yongfeng [Idaho National Lab. (INL), Idaho Falls, ID (United States); Tonks, Michael R. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Biner, S. Bulent [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-03-01

A hierarchical multi-scale approach is pursued in this work to investigate the influence of porosity, pore and grain size on the intergranular brittle fracture in UO2. In this approach, molecular dynamics simulations are performed to obtain the fracture properties for different grain boundary types. A phase-field model is then utilized to perform intergranular fracture simulations of representative microstructures with different porosities, pore and grain sizes. In these simulations the grain boundary fracture properties obtained from molecular dynamics simulations are used. The responses from the phase-field fracture simulations are then fitted with a stress-based brittle fracture model usable at the engineering scale. This approach encapsulates three different length and time scales, and allows the development of microstructurally informed engineering scale model from properties evaluated at the atomistic scale.

Beyond harvests in the commons: multi-scale governance and turbulence in indigenous/community conserved areas in Oaxaca, Mexico

Directory of Open Access Journals (Sweden)

David Barton Bray

2012-08-01

Full Text Available Some important elements of common property theory include a focus on individual communities or user groups, local level adjudication of conflicts, local autonomy in rule making, physical harvests, and low levels of articulation with markets. We present a case study of multi-scale collective action around indigenous/community conserved areas (ICCAs in Oaxaca, Mexico that suggests a modification of these components of common property theory. A multi-community ICCA in Oaxaca demonstrates the importance of inter-community collective action as key link in multi-scale governance, that conflicts are often negotiated in multiple arenas, that rules emerge at multiple scales, and that management for conservation and environmental services implies no physical harvests. Realizing economic gains from ICCAs for strict conservation may require something very different than traditional natural resource management. It requires intense engagement with extensive networks of government and civil society actors and new forms of community and inter-community collection action, or multi-scale governance. Multi-scale governance is built on trust and social capital at multiple scales and also constitutes collective action at multiple scales. However, processes of multi-scale governance are also necessarily “turbulent” with actors frequently having conflicting values and goals to be negotiated. We present an analytic history of the process of emergence of community and inter-community collective action around strict conservation and examples of internal and external turbulence. We argue that this case study and other literature requires an extensions of the constitutive elements of common property theory.
Decadal variability and metastability in the Southern Hemisphere

Science.gov (United States)

O'Kane, Terence; Risbey, James; Franzke, Christian; Horenko, Illia; Monselesan, Didier

2014-05-01

An examination of systematic changes in the metastability of the southern hemisphere 500hPa circulation is performed using both cluster analysis techniques and split flow blocking indices. The cluster methodology is a purely data-driven approach for parametrisation whereby a multi-scale approximation to non-stationary dynamical processes is achieved through optimal sequences of locally stationary fast Vector Auto-Regressive Factor (VARX) processes and some slow (or persistent) hidden process switching between them. Comparison is made with blocking indices commonly used in weather forecasting and climate analysis to identify dynamically relevant metastable regimes in the 500hPa circulation in both reanalysis and AMIP model data sets. Our analysis characterises the metastable regime in both reanalysis and model data sets prior to 1978 as positive and negative phases of a hemispheric mid-latitude blocking state with the Southern Annular Mode (SAM) associated with a transition state. Post 1978, SAM emerges as a true metastable state replacing the negative phase of the hemispheric blocking pattern. The hidden state frequency of occurrences exhibits strong trends. The blocking pattern dominates in the early 1980s then gradually decreases. There is a corresponding increase in the SAM frequency of occurrence. This trend is largely evident in the reanalysis summer and spring but was not evident in the AMIP data set. Non-stationary cluster analysis was then further used to identify the Southern Oceans response to the systematic changes in the mid-latitude atmospheric circulation and identify dynamical regimes associated with subsurface thermocline anomalies which were found to teleconnect the Pacific and Atlantic regions of the Antarctic Circumpolar Current (ACC).
The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence

Energy Technology Data Exchange (ETDEWEB)

Staebler, G. M.; Candy, J. [General Atomics, San Diego, California 92186 (United States); Howard, N. T. [Oak Ridge Institute for Science Education (ORISE), Oak Ridge, Tennessee 37831 (United States); Holland, C. [University of California San Diego, San Diego, California 92093 (United States)

2016-06-15

The 2D spectrum of the saturated electric potential from gyrokinetic turbulence simulations that include both ion and electron scales (multi-scale) in axisymmetric tokamak geometry is analyzed. The paradigm that the turbulence is saturated when the zonal (axisymmetic) ExB flow shearing rate competes with linear growth is shown to not apply to the electron scale turbulence. Instead, it is the mixing rate by the zonal ExB velocity spectrum with the turbulent distribution function that competes with linear growth. A model of this mechanism is shown to be able to capture the suppression of electron-scale turbulence by ion-scale turbulence and the threshold for the increase in electron scale turbulence when the ion-scale turbulence is reduced. The model computes the strength of the zonal flow velocity and the saturated potential spectrum from the linear growth rate spectrum. The model for the saturated electric potential spectrum is applied to a quasilinear transport model and shown to accurately reproduce the electron and ion energy fluxes of the non-linear gyrokinetic multi-scale simulations. The zonal flow mixing saturation model is also shown to reproduce the non-linear upshift in the critical temperature gradient caused by zonal flows in ion-scale gyrokinetic simulations.
The decadal-scale variation of the South Asian summer monsoon onset and its connection with the PDO

Science.gov (United States)

Watanabe, T.; Yamazaki, K.

2013-12-01

The summer Asian monsoon shows the abrupt increase of precipitation on the onset phase. It is an interesting and important problem when the summer monsoon onset occurs because natural resources, such as water and renewable energy agricultural product, are influenced by the variation of the summer Asian monsoon. Some researchers suggested the advance of the Asian summer monsoon onset in recent decades. We investigated the variation of the Asian monsoon onset using the long-term onset data over Kerala, a state in the southwest region of India, for 1948-2011. We discuss three main questions: 1) how is the variation of the monsoon onset date in the long-term period, 2) how the variation of the onset date is related to variations of atmospheric circulation and SST, and 3) what is the mechanism of such variation. Our main method is composite analysis using monthly-mean data. Though the onset date over Kerala shows the trend toward the early onset in recent three decades, such a trend is not observed in the whole period. It is noteworthy that the onset over Kerala shows the interannual variation on a multi-decadal scale. As regards the early onset years of Kerala, the summer monsoon onset is early over the following regions: the region from the southern Arabian Sea to southwestern India, the region from the southern Bay of Bengal to the Indochina Peninsula and the western North Pacific Ocean. On the other hand, the onset is late over southern China, Taiwan and the northern Philippine Sea. In early onset years of Kerala, the sea surface temperature over the northern Pacific Ocean is very similar to the negative PDO. The stationary wave train related with the negative PDO reaches into the Central Asia region, generates warm anomaly there and hence intensifies the land-sea thermal contrast there, which promotes the summer monsoon onset over South and Southeast Asia. Though the correlation between the onset over Kerala and the PDO is weak before 1976, it becomes high after
Subgrid-scale stresses and scalar fluxes constructed by the multi-scale turnover Lagrangian map

Science.gov (United States)

AL-Bairmani, Sukaina; Li, Yi; Rosales, Carlos; Xie, Zheng-tong

2017-04-01

The multi-scale turnover Lagrangian map (MTLM) [C. Rosales and C. Meneveau, "Anomalous scaling and intermittency in three-dimensional synthetic turbulence," Phys. Rev. E 78, 016313 (2008)] uses nested multi-scale Lagrangian advection of fluid particles to distort a Gaussian velocity field and, as a result, generate non-Gaussian synthetic velocity fields. Passive scalar fields can be generated with the procedure when the fluid particles carry a scalar property [C. Rosales, "Synthetic three-dimensional turbulent passive scalar fields via the minimal Lagrangian map," Phys. Fluids 23, 075106 (2011)]. The synthetic fields have been shown to possess highly realistic statistics characterizing small scale intermittency, geometrical structures, and vortex dynamics. In this paper, we present a study of the synthetic fields using the filtering approach. This approach, which has not been pursued so far, provides insights on the potential applications of the synthetic fields in large eddy simulations and subgrid-scale (SGS) modelling. The MTLM method is first generalized to model scalar fields produced by an imposed linear mean profile. We then calculate the subgrid-scale stress, SGS scalar flux, SGS scalar variance, as well as related quantities from the synthetic fields. Comparison with direct numerical simulations (DNSs) shows that the synthetic fields reproduce the probability distributions of the SGS energy and scalar dissipation rather well. Related geometrical statistics also display close agreement with DNS results. The synthetic fields slightly under-estimate the mean SGS energy dissipation and slightly over-predict the mean SGS scalar variance dissipation. In general, the synthetic fields tend to slightly under-estimate the probability of large fluctuations for most quantities we have examined. Small scale anisotropy in the scalar field originated from the imposed mean gradient is captured. The sensitivity of the synthetic fields on the input spectra is assessed by
Based on a multi-agent system for multi-scale simulation and application of household's LUCC: a case study for Mengcha village, Mizhi county, Shaanxi province.

Science.gov (United States)

Chen, Hai; Liang, Xiaoying; Li, Rui

2013-01-01

Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the
Biology meets Physics: Reductionism and Multi-scale Modeling of Morphogenesis

DEFF Research Database (Denmark)

Green, Sara; Batterman, Robert

2017-01-01

A common reductionist assumption is that macro-scale behaviors can be described "bottom-up" if only sufficient details about lower-scale processes are available. The view that an "ideal" or "fundamental" physics would be sufficient to explain all macro-scale phenomena has been met with criticism ...... modeling in developmental biology. In such contexts, the relation between models at different scales and from different disciplines is neither reductive nor completely autonomous, but interdependent....... from philosophers of biology. Specifically, scholars have pointed to the impossibility of deducing biological explanations from physical ones, and to the irreducible nature of distinctively biological processes such as gene regulation and evolution. This paper takes a step back in asking whether bottom......-up modeling is feasible even when modeling simple physical systems across scales. By comparing examples of multi-scale modeling in physics and biology, we argue that the “tyranny of scales” problem present a challenge to reductive explanations in both physics and biology. The problem refers to the scale...
Model under-representation of decadal Pacific trade wind trends and its link to tropical Atlantic bias

Science.gov (United States)

Kajtar, Jules B.; Santoso, Agus; McGregor, Shayne; England, Matthew H.; Baillie, Zak

2018-02-01

The strengthening of the Pacific trade winds in recent decades has been unmatched in the observational record stretching back to the early twentieth century. This wind strengthening has been connected with numerous climate-related phenomena, including accelerated sea-level rise in the western Pacific, alterations to Indo-Pacific ocean currents, increased ocean heat uptake, and a slow-down in the rate of global-mean surface warming. Here we show that models in the Coupled Model Intercomparison Project phase 5 underestimate the observed range of decadal trends in the Pacific trade winds, despite capturing the range in decadal sea surface temperature (SST) variability. Analysis of observational data suggests that tropical Atlantic SST contributes considerably to the Pacific trade wind trends, whereas the Atlantic feedback in coupled models is muted. Atmosphere-only simulations forced by observed SST are capable of recovering the time-variation and the magnitude of the trade wind trends. Hence, we explore whether it is the biases in the mean or in the anomalous SST patterns that are responsible for the under-representation in fully coupled models. Over interannual time-scales, we find that model biases in the patterns of Atlantic SST anomalies are the strongest source of error in the precipitation and atmospheric circulation response. In contrast, on decadal time-scales, the magnitude of the model biases in Atlantic mean SST are directly linked with the trade wind variability response.
Generating relations of multi-variable Tricomi functions of two indices using Lie algebra representation

Directory of Open Access Journals (Sweden)

Nader Ali Makboul Hassan

2014-01-01

Full Text Available This paper is an attempt to stress the usefulness of the multi-variable special functions. In this paper, we derive certain generating relations involving 2-indices 5-variables 5-parameters Tricomi functions (2I5V5PTF by using a Lie-algebraic method. Further, we derive certain new and known generating relations involving other forms of Tricomi and Bessel functions as applications.
HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

Science.gov (United States)

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.
Influence of plant productivity over variability of soil respiration: a multi-scale approach

Science.gov (United States)

Curiel Yuste, J.

2009-04-01

To investigate the role of plant photosynthetic activity on the variations in soil respiration (SR), SR data obtained from manual sampling and automatic soil respiration chambers placed on eddy flux towers sites were used. Plant photosynthetic activity was represented as Gross Primary Production (GPP), calculated from the half hourly continuous measurements of Net Ecosystem Exchange (NEE). The role of plant photosynthetic activity over the variation in SR was investigated at different time-scales: data averaged hourly, daily and weekly were used to study the photosynthetic effect on SR dial variations (Hourly data), 15 days variations (Daily averages), monthly variations (daily and weekly averages) and seasonal variations (weekly data). Our results confirm the important role of plant photosynthetic activity on the variations of SR at each of the mentioned time-scales. The effect of photosynthetic activity on SR was high on hourly time-scale (dial variations of SR). At half of the studied ecosystems GPP was the best single predictor of dial variations of SR. However at most of the studied sites the combination of soil temperature and GPP was the best predictor of dial variations in SR. The effect of aboveground productivity over dial variations of SR lagged on the range of 5 to 15 hours, depending on the ecosystem. At daily to monthly time scale variations of SR were in general better explained with the combination of temperature and moisture variations. However, ‘jumps' in average weekly SR during the growing season yielded anomaly high values of Q10, in some cases above 1000, which probably reflects synoptic changes in photosynthates translocation from plant activity. Finally, although seasonal changes of SR were in general very well explained by temperature and soil moisture, seasonality of SR was better correlated to seasonality of GPP than to seasonality of soil temperature and/or soil moisture. Therefore the magnitude of the seasonal variation in SR was in
Analytical Solutions for Multi-Time Scale Fractional Stochastic Differential Equations Driven by Fractional Brownian Motion and Their Applications

Directory of Open Access Journals (Sweden)

Xiao-Li Ding

2018-01-01

Full Text Available In this paper, we investigate analytical solutions of multi-time scale fractional stochastic differential equations driven by fractional Brownian motions. We firstly decompose homogeneous multi-time scale fractional stochastic differential equations driven by fractional Brownian motions into independent differential subequations, and give their analytical solutions. Then, we use the variation of constant parameters to obtain the solutions of nonhomogeneous multi-time scale fractional stochastic differential equations driven by fractional Brownian motions. Finally, we give three examples to demonstrate the applicability of our obtained results.
Multi-scale Dynamical Processes in Space and Astrophysical Plasmas

CERN Document Server

Vörös, Zoltán; IAFA 2011 - International Astrophysics Forum 2011 : Frontiers in Space Environment Research

2012-01-01

Magnetized plasmas in the universe exhibit complex dynamical behavior over a huge range of scales. The fundamental mechanisms of energy transport, redistribution and conversion occur at multiple scales. The driving mechanisms often include energy accumulation, free-energy-excited relaxation processes, dissipation and self-organization. The plasma processes associated with energy conversion, transport and self-organization, such as magnetic reconnection, instabilities, linear and nonlinear waves, wave-particle interactions, dynamo processes, turbulence, heating, diffusion and convection represent fundamental physical effects. They demonstrate similar dynamical behavior in near-Earth space, on the Sun, in the heliosphere and in astrophysical environments. 'Multi-scale Dynamical Processes in Space and Astrophysical Plasmas' presents the proceedings of the International Astrophysics Forum Alpbach 2011. The contributions discuss the latest advances in the exploration of dynamical behavior in space plasmas environm...
Comparison of environmental forcings affecting suspended sediments variability in two macrotidal, highly-turbid estuaries

Science.gov (United States)

Jalón-Rojas, Isabel; Schmidt, Sabine; Sottolichio, Aldo

2017-11-01

The relative contribution of environmental forcing frequencies on turbidity variability is, for the first time, quantified at seasonal and multiannual time scales in tidal estuarine systems. With a decade of high-frequency, multi-site turbidity monitoring, the two nearby, macrotidal and highly-turbid Gironde and Loire estuaries (west France) are excellent natural laboratories for this purpose. Singular Spectrum Analyses, combined with Lomb-Scargle periodograms and Wavelet Transforms, were applied to the continuous multiannual turbidity time series. Frequencies of the main environmental factors affecting turbidity were identified: hydrological regime (high versus low river discharges), river flow variability, tidal range, tidal cycles, and turbulence. Their relative influences show similar patterns in both estuaries and depend on the estuarine region (lower or upper estuary) and the time scale (multiannual or seasonal). On the multiannual time scale, the relative contribution of tidal frequencies (tidal cycles and range) to turbidity variability decreases up-estuary from 68% to 47%, while the influence of river flow frequencies increases from 3% to 42%. On the seasonal time scale, the relative influence of forcings frequencies remains almost constant in the lower estuary, dominated by tidal frequencies (60% and 30% for tidal cycles and tidal range, respectively); in the upper reaches, it is variable depending on hydrological regime, even if tidal frequencies are responsible for up 50% of turbidity variance. These quantifications show the potential of combined spectral analyses to compare the behavior of suspended sediment in tidal estuaries throughout the world and to evaluate long-term changes in environmental forcings, especially in a context of global change. The relevance of this approach to compare nearby and overseas systems and to support management strategies is discussed (e.g., selection of effective operation frequencies/regions, prediction of the most
Fast Decentralized Averaging via Multi-scale Gossip

Science.gov (United States)

Tsianos, Konstantinos I.; Rabbat, Michael G.

We are interested in the problem of computing the average consensus in a distributed fashion on random geometric graphs. We describe a new algorithm called Multi-scale Gossip which employs a hierarchical decomposition of the graph to partition the computation into tractable sub-problems. Using only pairwise messages of fixed size that travel at most O(n^{1/3}) hops, our algorithm is robust and has communication cost of O(n loglogn logɛ - 1) transmissions, which is order-optimal up to the logarithmic factor in n. Simulated experiments verify the good expected performance on graphs of many thousands of nodes.
Antipersistent dynamics in short time scale variability of self-potential signals

Directory of Open Access Journals (Sweden)

M. Ragosta

2000-06-01

Full Text Available Time scale properties of self-potential signals are investigated through the analysis of the second order structure function (variogram, a powerful tool to investigate the spatial and temporal variability of observational data. In this work we analyse two sequences of self-potential values measured by means of a geophysical monitoring array located in a seismically active area of Southern Italy. The range of scales investigated goes from a few minutes to several days. It is shown that signal fluctuations are characterised by two time scale ranges in which self-potential variability appears to follow slightly different dynamical behaviours. Results point to the presence of fractal, non stationary features expressing a long term correlation with scaling coefficients which are the clue of stabilising mechanisms. In the scale ranges in which the series show scale invariant behaviour, self-potentials evolve like fractional Brownian motions with anticorrelated increments typical of processes regulated by negative feedback mechanisms (antipersistence. On scales below about 6 h the strength of such an antipersistence appears to be slightly greater than that observed on larger time scales where the fluctuations are less efficiently stabilised.
High-Temperature Tolerance in Multi-Scale Cermet Solar-Selective Absorbing Coatings Prepared by Laser Cladding.

Science.gov (United States)

Pang, Xuming; Wei, Qian; Zhou, Jianxin; Ma, Huiyang

2018-06-19

In order to achieve cermet-based solar absorber coatings with long-term thermal stability at high temperatures, a novel single-layer, multi-scale TiC-Ni/Mo cermet coating was first prepared using laser cladding technology in atmosphere. The results show that the optical properties of the cermet coatings using laser cladding were much better than the preplaced coating. In addition, the thermal stability of the optical properties for the laser cladding coating were excellent after annealing at 650 °C for 200 h. The solar absorptance and thermal emittance of multi-scale cermet coating were 85% and 4.7% at 650 °C. The results show that multi-scale cermet materials are more suitable for solar-selective absorbing coating. In addition, laser cladding is a new technology that can be used for the preparation of spectrally-selective coatings.
High-Temperature Tolerance in Multi-Scale Cermet Solar-Selective Absorbing Coatings Prepared by Laser Cladding

Directory of Open Access Journals (Sweden)

Xuming Pang

2018-06-01

Full Text Available In order to achieve cermet-based solar absorber coatings with long-term thermal stability at high temperatures, a novel single-layer, multi-scale TiC-Ni/Mo cermet coating was first prepared using laser cladding technology in atmosphere. The results show that the optical properties of the cermet coatings using laser cladding were much better than the preplaced coating. In addition, the thermal stability of the optical properties for the laser cladding coating were excellent after annealing at 650 °C for 200 h. The solar absorptance and thermal emittance of multi-scale cermet coating were 85% and 4.7% at 650 °C. The results show that multi-scale cermet materials are more suitable for solar-selective absorbing coating. In addition, laser cladding is a new technology that can be used for the preparation of spectrally-selective coatings.
Multi-scale interactions affecting transport, storage, and processing of solutes and sediments in stream corridors (Invited)

Science.gov (United States)

Harvey, J. W.; Packman, A. I.

2010-12-01

where hyporheic fluxes cannot be accurately estimated without considering multi-scale effects. Our modeling captures the dominance of small-scale features such as bedforms that drive the majority of hyporheic flow, but it also captures how hyporheic flow is substantially modified by relatively small changes in streamflow or groundwater flow. The additional field measurements add sensitivity and power to whole stream tracer additions by improving resolution of the relative importance of storage at different scales (e.g. bar-scale versus bedform-scale). This information is critical in identifying hot spots where important biogeochemical reactions occur. In summary, interpreting multi-scale interactions in streams requires models that are physically based and that incorporate non-linear process dynamics. Such models can take advantage of increasingly comprehensive field data to integrate transport processes across spatially variable flow and geomorphic conditions. The most useful field and modeling approaches will be those that are simple enough to be easily implemented by users from various disciplines but comprehensive enough to produce meaningful predictions for a wide range of flow and geomorphic scenarios. This capability is needed to support improved strategies for protecting stream ecological health in the face of accelerating land use and climate change.
Millennial- to century-scale variability in Gulf of Mexico Holocene climate records

Science.gov (United States)

Poore, R.Z.; Dowsett, H.J.; Verardo, S.; Quinn, T.M.

2003-01-01

Proxy records from two piston cores in the Gulf of Mexico (GOM) provide a detailed (50-100 year resolution) record of climate variability over the last 14,000 years. Long-term (millennial-scale) trends and changes are related to the transition from glacial to interglacial conditions and movement of the average position of the Intertropical Convergence Zone (ITCZ) related to orbital forcing. The ??18O of the surface-dwelling planktic foraminifer Globigerinoides ruber show negative excursions between 14 and 10.2 ka (radiocarbon years) that reflect influx of meltwater into the western GOM during melting of the Laurentide Ice Sheet. The relative abundance of the planktic foraminifer Globigerinoides sacculifer is related to transport of Caribbean water into the GOM. Maximum transport of Caribbean surface waters and moisture into the GOM associated with a northward migration of the average position of the ITCZ occurs between about 6.5 and 4.5 ka. In addition, abundance variations of G. sacculifer show century-scale variability throughout most of the Holocene. The GOM record is consistent with records from other areas, suggesting that century-scale variability is a pervasive feature of Holocene climate. The frequency of several cycles in the climate records is similar to cycles identified in proxy records of solar variability, indicating that at least some of the century-scale climate variability during the Holocene is due to external (solar) forcing.

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