The assessment of Global Precipitation Measurement estimates over the Indian subcontinent

Science.gov (United States)

Murali Krishna, U. V.; Das, Subrata Kumar; Deshpande, Sachin M.; Doiphode, S. L.; Pandithurai, G.

2017-08-01

Accurate and real-time precipitation estimation is a challenging task for current and future spaceborne measurements, which is essential to understand the global hydrological cycle. Recently, the Global Precipitation Measurement (GPM) satellites were launched as a next-generation rainfall mission for observing the global precipitation characteristics. The purpose of the GPM is to enhance the spatiotemporal resolution of global precipitation. The main objective of the present study is to assess the rainfall products from the GPM, especially the Integrated Multi-satellitE Retrievals for the GPM (IMERG) data by comparing with the ground-based observations. The multitemporal scale evaluations of rainfall involving subdaily, diurnal, monthly, and seasonal scales were performed over the Indian subcontinent. The comparison shows that the IMERG performed better than the Tropical Rainfall Measuring Mission (TRMM)-3B42, although both rainfall products underestimated the observed rainfall compared to the ground-based measurements. The analyses also reveal that the TRMM-3B42 and IMERG data sets are able to represent the large-scale monsoon rainfall spatial features but are having region-specific biases. The IMERG shows significant improvement in low rainfall estimates compared to the TRMM-3B42 for selected regions. In the spatial distribution, the IMERG shows higher rain rates compared to the TRMM-3B42, due to its enhanced spatial and temporal resolutions. Apart from this, the characteristics of raindrop size distribution (DSD) obtained from the GPM mission dual-frequency precipitation radar is assessed over the complex mountain terrain site in the Western Ghats, India, using the DSD measured by a Joss-Waldvogel disdrometer.

Large-scale connection between aerosol optical depth and summer monsoon circulation, and precipitation over northeast Asia

Science.gov (United States)

Kim, Sang-Woo; Yoon, Soon-Chang; Choi, Suk-Jin; Choi, In-Jin

2010-05-01

We investigated the large-scale connection between columnar aerosol loads and summer monsoon circulation, and also the precipitation over northeast Asia using aerosol optical depth (AOD) data obtained from the 8-year MODIS, AERONET Sun/sky radiometer, and precipitation data acquired under the Global Precipitation Climatology Project (GPCP). These high-quality data revealed the large-scale link between AOD and summer monsoon circulation, precipitation in July over northeast Asian countries, and their distinct spatial and annual variabilities. Compared to the mean AOD for the entire period of 2001-2008, the increase of almost 40-50% in the AOD value in July 2005 and July 2007 was found over the downwind regions of China (Yellow Sea, Korean peninsula, and East Sea), with negative precipitation anomalies. This can be attributable to the strong westerly confluent flows, between cyclone flows by continental thermal low centered over the northern China and anti-cyclonic flows by the western North Pacific High, which transport anthropogenic pollution aerosols emitted from east China to aforementioned downwind high AOD regions along the rim of the Pacific marine airmass. In July 2002, however, the easterly flows transported anthropogenic aerosols from east China to the southwestern part of China in July 2002. As a result, the AOD off the coast of China was dramatically reduced in spite of decreasing rainfall. From the calculation of the cross-correlation coefficient between MODIS-derived AOD anomalies and GPCP precipitation anomalies over the period 2001-2008, we found negative correlations over the areas encompassed by 105-115E and 30-35N and by 120-140E and 35-40N (Yellow Sea, Korean peninsula, and East Sea). This suggests that aerosol loads over these regions are easily influenced by the Asian monsoon flow system and associated precipitation.

Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

Science.gov (United States)

Prat, O. P.; Nelson, B. R.

2014-10-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets (bias-adjusted TMPA 3B42, near-real time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (± 6%). However, differences at the RFC are more important in particular for near-real time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near real time counterpart 3B42RT. However, large biases remained for 3B42 over the Western US for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in day-1) over the Northwest. Furthermore, the conditional analysis and the contingency analysis conducted illustrated the challenge of retrieving extreme precipitation from remote sensing estimates.

Investigating the dependence of SCM simulated precipitation and clouds on the spatial scale of large-scale forcing at SGP

Science.gov (United States)

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

2017-08-01

Large-scale forcing data, such as vertical velocity and advective tendencies, are required to drive single-column models (SCMs), cloud-resolving models, and large-eddy simulations. Previous studies suggest that some errors of these model simulations could be attributed to the lack of spatial variability in the specified domain-mean large-scale forcing. This study investigates the spatial variability of the forcing and explores its impact on SCM simulated precipitation and clouds. A gridded large-scale forcing data during the March 2000 Cloud Intensive Operational Period at the Atmospheric Radiation Measurement program's Southern Great Plains site is used for analysis and to drive the single-column version of the Community Atmospheric Model Version 5 (SCAM5). When the gridded forcing data show large spatial variability, such as during a frontal passage, SCAM5 with the domain-mean forcing is not able to capture the convective systems that are partly located in the domain or that only occupy part of the domain. This problem has been largely reduced by using the gridded forcing data, which allows running SCAM5 in each subcolumn and then averaging the results within the domain. This is because the subcolumns have a better chance to capture the timing of the frontal propagation and the small-scale systems. Other potential uses of the gridded forcing data, such as understanding and testing scale-aware parameterizations, are also discussed.

Long-Term Large-Scale Bias-Adjusted Precipitation Estimates at High Spatial and Temporal Resolution Derived from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Precipitation Reanalysis over CONUS

Science.gov (United States)

Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Seo, D. J.; Kim, B.

2014-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over Continental United States (CONUS) is nearly completed for the period covering from 2000 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network - Daily (GHCN-D) are used to adjust for those biases and to merge with the radar only product to provide a multi-sensor estimate. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. After assessing the bias and applying reduction or elimination techniques, we are investigating the kriging method and its variants such as simple kriging (SK), ordinary kriging (OK), and conditional bias-penalized Kriging (CBPK) among others. In addition we hope to generate estimates of uncertainty for the gridded estimate. In this work the methodology is presented as well as a comparison between the radar-only product and the final multi-sensor QPE product. The comparison is performed at various time scales from the sub-hourly, to annual. In addition, comparisons over the same period with a suite of lower resolution QPEs derived from ground based radar

Heating-insensitive scale increase caused by convective precipitation

Science.gov (United States)

Haerter, Jan; Moseley, Christopher; Berg, Peter

2017-04-01

The origin of intense convective extremes and their unusual temperature dependence has recently challenged traditional thermodynamic arguments, based on the Clausius-Clapeyron relation. In a sequence of studies (Lenderink and v. Mejgaard, Nat Geosc, 2008; Berg, Haerter, Moseley, Nat Geosc, 2013; and Moseley, Hohenegger, Berg, Haerter, Nat Geosc, 2016) the argument of convective-type precipitation overcoming the 7%/K increase in extremes by dynamical, rather than thermodynamic, processes has been promoted. How can the role of dynamical processes be approached for precipitating convective cloud? One-phase, non-precipitating Rayleigh-Bénard convection is a classical problem in complex systems science. When a fluid between two horizontal plates is sufficiently heated from below, convective rolls spontaneously form. In shallow, non-precipitating atmospheric convection, rolls are also known to form under specific conditions, with horizontal scales roughly proportional to the boundary layer height. Here we explore within idealized large-eddy simulations, how the scale of convection is modified, when precipitation sets in and intensifies in the course of diurnal solar heating. Before onset of precipitation, Bénard cells with relatively constant diameter form, roughly on the scale of the atmospheric boundary layer. We find that the onset of precipitation then signals an approximately linear (in time) increase in horizontal scale. This scale increase progresses at a speed which is rather insensitive to changes in surface temperature or changes in the rate at which boundary conditions change, hinting at spatial characteristics, rather than temperature, as a possible control on spatial scales of convection. When exploring the depth of spatial correlations, we find that precipitation onset causes a sudden disruption of order and a subsequent complete disintegration of organization —until precipitation eventually ceases. Returning to the initial question of convective

Contribution of large-scale circulation anomalies to changes in extreme precipitation frequency in the United States

International Nuclear Information System (INIS)

Yu, Lejiang; Zhong, Shiyuan; Pei, Lisi; Bian, Xindi; Heilman, Warren E

2016-01-01

The mean global climate has warmed as a result of the increasing emission of greenhouse gases induced by human activities. This warming is considered the main reason for the increasing number of extreme precipitation events in the US. While much attention has been given to extreme precipitation events occurring over several days, which are usually responsible for severe flooding over a large region, little is known about how extreme precipitation events that cause flash flooding and occur at sub-daily time scales have changed over time. Here we use the observed hourly precipitation from the North American Land Data Assimilation System Phase 2 forcing datasets to determine trends in the frequency of extreme precipitation events of short (1 h, 3 h, 6 h, 12 h and 24 h) duration for the period 1979–2013. The results indicate an increasing trend in the central and eastern US. Over most of the western US, especially the Southwest and the Intermountain West, the trends are generally negative. These trends can be largely explained by the interdecadal variability of the Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation (AMO), with the AMO making a greater contribution to the trends in both warm and cold seasons. (letter)

United States Temperature and Precipitation Extremes: Phenomenology, Large-Scale Organization, Physical Mechanisms and Model Representation

Science.gov (United States)

Black, R. X.

2017-12-01

We summarize results from a project focusing on regional temperature and precipitation extremes over the continental United States. Our project introduces a new framework for evaluating these extremes emphasizing their (a) large-scale organization, (b) underlying physical sources (including remote-excitation and scale-interaction) and (c) representation in climate models. Results to be reported include the synoptic-dynamic behavior, seasonality and secular variability of cold waves, dry spells and heavy rainfall events in the observational record. We also study how the characteristics of such extremes are systematically related to Northern Hemisphere planetary wave structures and thus planetary- and hemispheric-scale forcing (e.g., those associated with major El Nino events and Arctic sea ice change). The underlying physics of event onset are diagnostically quantified for different categories of events. Finally, the representation of these extremes in historical coupled climate model simulations is studied and the origins of model biases are traced using new metrics designed to assess the large-scale atmospheric forcing of local extremes.

An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

Science.gov (United States)

Chardon, Jérémy; Hingray, Benoit; Favre, Anne-Catherine

2018-01-01

Statistical downscaling models (SDMs) are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

Parameter and State Estimation of Large-Scale Complex Systems Using Python Tools

Directory of Open Access Journals (Sweden)

M. Anushka S. Perera

2015-07-01

Full Text Available This paper discusses the topics related to automating parameter, disturbance and state estimation analysis of large-scale complex nonlinear dynamic systems using free programming tools. For large-scale complex systems, before implementing any state estimator, the system should be analyzed for structural observability and the structural observability analysis can be automated using Modelica and Python. As a result of structural observability analysis, the system may be decomposed into subsystems where some of them may be observable --- with respect to parameter, disturbances, and states --- while some may not. The state estimation process is carried out for those observable subsystems and the optimum number of additional measurements are prescribed for unobservable subsystems to make them observable. In this paper, an industrial case study is considered: the copper production process at Glencore Nikkelverk, Kristiansand, Norway. The copper production process is a large-scale complex system. It is shown how to implement various state estimators, in Python, to estimate parameters and disturbances, in addition to states, based on available measurements.

Comparing NEXRAD Operational Precipitation Estimates and Raingage Observations of Intense Precipitation in the Missouri River Basin.

Science.gov (United States)

Young, C. B.

2002-05-01

Accurate observation of precipitation is critical to the study and modeling of land surface hydrologic processes. NEXRAD radar-based precipitation estimates are increasingly used in field experiments, hydrologic modeling, and water and energy budget studies due to their high spatial and temporal resolution, national coverage, and perceived accuracy. Extensive development and testing of NEXRAD precipitation algorithms have been carried out in the Southern Plains. Previous studies (Young et al. 2000, Young et al. 1999, Smith et al. 1996) indicate that NEXRAD operational products tend to underestimate precipitation at light rain rates. This study investigates the performance of NEXRAD precipitation estimates of high-intensity rainfall, focusing on flood-producing storms in the Missouri River Basin. NEXRAD estimates for these storms are compared with data from multiple raingage networks, including NWS recording and non-recording gages and ALERT raingage data for the Kansas City metropolitan area. Analyses include comparisons of gage and radar data at a wide range of temporal and spatial scales. Particular attention is paid to the October 4th, 1998, storm that produced severe flooding in Kansas City. NOTE: The phrase `NEXRAD operational products' in this abstract includes precipitation estimates generated using the Stage III and P1 algorithms. Both of these products estimate hourly accumulations on the (approximately) 4 km HRAP grid.

Climate dynamics of South America during summer: Connections between the large-scale circulation and regional precipitation

Science.gov (United States)

Lenters, Johh Derick

1997-05-01

Relationships between the large-scale circulation and regional precipitation over South America during austral summer are examined using a GCM, linear model, and observational analyses. Emphasis is placed on understanding the origin of upper-tropospheric circulation features such as the Bolivian high and its effects on South American precipitation variability, particularly on the Central Andean Altiplano. Results from the linear model indicate that the Bolivian high and 'Nordeste low' are generated in response to precipitation over the Amazon basin, Central Andes, and South Atlantic convergence zone (SACZ), with African precipitation also playing a crucial role in the formation of the low. The direct mechanical and sensible heating effects of the Andes are minimal, acting only to induce a weak lee trough in midlatitudes and a shallow monsoonal circulation over the Central Andes. In the GCM the effects of the Andes include a strengthening of the Bolivian high and northward shift of the Nordeste low, primarily through changes in the precipitation field. The position of the Bolivian high is primarily determined by Amazonian precipitation and is little affected by the removal of the Andes. Strong subsidence to the west of the high is found to be important for the maintenance of the high's warm core, while large-scale convective overshooting to the east is responsible for a layer of cold air above the high. Observations from eight summer seasons reveal a close relationship between precipitation variability in the Central Andes and the position and intensity of the Bolivian high. The physical mechanisms of this connection are explored using composite, EOF, and correlation techniques. On intraseasonal to interannual timescales, rainy episodes on the Altiplano are found to be associated with warm, moist, poleward flow along the eastern flank of the Andes, often in conjunction with extratropical disturbances and a westward displacement of the SACZ. Corresponding to this

An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

Directory of Open Access Journals (Sweden)

J. Chardon

2018-01-01

Full Text Available Statistical downscaling models (SDMs are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

The interannual precipitation variability in the southern part of Iran as linked to large-scale climate modes

Energy Technology Data Exchange (ETDEWEB)

Pourasghar, Farnaz; Jahanbakhsh, Saeed; Sari Sarraf, Behrooz [The University of Tabriz, Department of Physical Geography, Faculty of Humanities and Social Science, Tabriz (Iran, Islamic Republic of); Tozuka, Tomoki [The University of Tokyo, Department of Earth and Planetary Science, Graduate School of Science, Tokyo (Japan); Ghaemi, Hooshang [Iran Meteorological Organization, Tehran (Iran, Islamic Republic of); Yamagata, Toshio [The University of Tokyo, Department of Earth and Planetary Science, Graduate School of Science, Tokyo (Japan); Application Laboratory/JAMSTEC, Yokohama, Kanagawa (Japan)

2012-11-15

The interannual variation of precipitation in the southern part of Iran and its link with the large-scale climate modes are examined using monthly data from 183 meteorological stations during 1974-2005. The majority of precipitation occurs during the rainy season from October to May. The interannual variation in fall and early winter during the first part of the rainy season shows apparently a significant positive correlation with the Indian Ocean Dipole (IOD) and El Nino-Southern Oscillation (ENSO). However, a partial correlation analysis used to extract the respective influence of IOD and ENSO shows a significant positive correlation only with the IOD and not with ENSO. The southeasterly moisture flux anomaly over the Arabian Sea turns anti-cyclonically and transport more moisture to the southern part of Iran from the Arabian Sea, the Red Sea, and the Persian Gulf during the positive IOD. On the other hand, the moisture flux has northerly anomaly over Iran during the negative IOD, which results in reduced moisture supply from the south. During the latter part of the rainy season in late winter and spring, the interannual variation of precipitation is more strongly influenced by modes of variability over the Mediterranean Sea. The induced large-scale atmospheric circulation anomaly controls moisture supply from the Red Sea and the Persian Gulf. (orig.)

Nano-scaled iron-carbon precipitates in HSLC and HSLA steels

Institute of Scientific and Technical Information of China (English)

2007-01-01

This paper studies the composition, quantity and particle size distribution of nano-scaled precipitates with size less than 20 nm in high strength low carbon (HSLC) steel and their effects on mechanical properties of HSLC steel by means of mass balance calculation of nano-scaled precipitates measured by chemical phase analysis plus SAXS method, high-resolution TEM analysis and thermodynamics calculation, as well as temper rapid cooling treatment of ZJ330. It is found that there existed a large quantity of nano-scaled iron-carbon precipitates with size less than 18 nm in low carbon steel produced by CSP and they are mainly Fe-O-C and Fe-Ti-O-C precipitates formed below temperature A1. These precipitates have ob- vious precipitation strengthening effect on HSLC steel and this may be regarded as one of the main reasons why HSLC steel has higher strength. There also existed a lot of iron-carbon precipitates with size less than 36 nm in HSLA steels.

Nano-scaled iron-carbon precipitates in HSLC and HSLA steels

Institute of Scientific and Technical Information of China (English)

FU Jie; WU HuaJie; LIU YangChun; KANG YongLin

2007-01-01

This paper studies the composition, quantity and particle size distribution of nano-scaled precipitates with size less than 20 nm in high strength Iow carbon (HSLC) steel and their effects on mechanical properties of HSLC steel by means of mass balance calculation of nano-scaled precipitates measured by chemical phase analysis plus SAXS method, high-resolution TEM analysis and thermodynamics calculation, as well as temper rapid cooling treatment of ZJ330. It is found that there existed a large quantity of nano-scaled iron-carbon precipitates with size less than 18 nm in Iow carbon steel produced by CSP and they are mainly Fe-O-C and Fe-Ti-O-C precipitates formed below temperature A1. These precipitates have obvious precipitation strengthening effect on HSLC steel and this may be regarded as one of the main reasons why HSLC steel has higher strength. There also existed a lot of iron-carbon precipitates with size less than 36 nm in HSLA steels.

Efficient Topology Estimation for Large Scale Optical Mapping

CERN Document Server

Elibol, Armagan; Garcia, Rafael

2013-01-01

Large scale optical mapping methods are in great demand among scientists who study different aspects of the seabed, and have been fostered by impressive advances in the capabilities of underwater robots in gathering optical data from the seafloor. Cost and weight constraints mean that low-cost ROVs usually have a very limited number of sensors. When a low-cost robot carries out a seafloor survey using a down-looking camera, it usually follows a predefined trajectory that provides several non time-consecutive overlapping image pairs. Finding these pairs (a process known as topology estimation) is indispensable to obtaining globally consistent mosaics and accurate trajectory estimates, which are necessary for a global view of the surveyed area, especially when optical sensors are the only data source. This book contributes to the state-of-art in large area image mosaicing methods for underwater surveys using low-cost vehicles equipped with a very limited sensor suite. The main focus has been on global alignment...

Large Scale Evapotranspiration Estimates: An Important Component in Regional Water Balances to Assess Water Availability

Science.gov (United States)

Garatuza-Payan, J.; Yepez, E. A.; Watts, C.; Rodriguez, J. C.; Valdez-Torres, L. C.; Robles-Morua, A.

2013-05-01

Water security, can be defined as the reliable supply in quantity and quality of water to help sustain future populations and maintaining ecosystem health and productivity. Water security is rapidly declining in many parts of the world due to population growth, drought, climate change, salinity, pollution, land use change, over-allocation and over-utilization, among other issues. Governmental offices (such as the Comision Nacional del Agua in Mexico, CONAGUA) require and conduct studies to estimate reliable water balances at regional or continental scales in order to provide reasonable assessments of the amount of water that can be provided (from surface or ground water sources) to supply all the human needs while maintaining natural vegetation, on an operational basis and, more important, under disturbances, such as droughts. Large scale estimates of evapotranspiration (ET), a critical component of the water cycle, are needed for a better comprehension of the hydrological cycle at large scales, which, in most water balances is left as the residual. For operational purposes, such water balance estimates can not rely on ET measurements since they do not exist, should be simple and require the least ground information possible, information that is often scarce or does not exist at all. Given this limitation, the use of remotely sensed data to estimate ET could supplement the lack of ground information, particularly in remote regions In this study, a simple method, based on the Makkink equation is used to estimate ET for large areas at high spatial resolutions (1 km). The Makkink model used here is forced using three remotely sensed datasets. First, the model uses solar radiation estimates obtained from the Geostationary Operational Environmental Satellite (GOES); Second, the model uses an Enhanced Vegetation Index (EVI) obtained from the Moderate-resolution Imaging Spectroradiometer (MODIS) normalized to get an estimate for vegetation amount and land use which was

Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)

Science.gov (United States)

Adler, Robert; Gu, Guojun; Huffman, George

2012-01-01

A procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within +/- 50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation s of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (s/m, where m is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%-15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (s) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a

A test for Improvement of high resolution Quantitative Precipitation Estimation for localized heavy precipitation events

Science.gov (United States)

Lee, Jung-Hoon; Roh, Joon-Woo; Park, Jeong-Gyun

2017-04-01

Accurate estimation of precipitation is one of the most difficult and significant tasks in the area of weather diagnostic and forecasting. In the Korean Peninsula, heavy precipitations are caused by various physical mechanisms, which are affected by shortwave trough, quasi-stationary moisture convergence zone among varying air masses, and a direct/indirect effect of tropical cyclone. In addition to, various geographical and topographical elements make production of temporal and spatial distribution of precipitation is very complicated. Especially, localized heavy rainfall events in South Korea generally arise from mesoscale convective systems embedded in these synoptic scale disturbances. In weather radar data with high temporal and spatial resolution, accurate estimation of rain rate from radar reflectivity data is too difficult. Z-R relationship (Marshal and Palmer 1948) have adapted representatively. In addition to, several methods such as support vector machine (SVM), neural network, Fuzzy logic, Kriging were utilized in order to improve the accuracy of rain rate. These methods show the different quantitative precipitation estimation (QPE) and the performances of accuracy are different for heavy precipitation cases. In this study, in order to improve the accuracy of QPE for localized heavy precipitation, ensemble method for Z-R relationship and various techniques was tested. This QPE ensemble method was developed by a concept based on utilizing each advantage of precipitation calibration methods. The ensemble members were produced for a combination of different Z-R coefficient and calibration method.

Improving real-time estimation of heavy-to-extreme precipitation using rain gauge data via conditional bias-penalized optimal estimation

Science.gov (United States)

Seo, Dong-Jun; Siddique, Ridwan; Zhang, Yu; Kim, Dongsoo

2014-11-01

A new technique for gauge-only precipitation analysis for improved estimation of heavy-to-extreme precipitation is described and evaluated. The technique is based on a novel extension of classical optimal linear estimation theory in which, in addition to error variance, Type-II conditional bias (CB) is explicitly minimized. When cast in the form of well-known kriging, the methodology yields a new kriging estimator, referred to as CB-penalized kriging (CBPK). CBPK, however, tends to yield negative estimates in areas of no or light precipitation. To address this, an extension of CBPK, referred to herein as extended conditional bias penalized kriging (ECBPK), has been developed which combines the CBPK estimate with a trivial estimate of zero precipitation. To evaluate ECBPK, we carried out real-world and synthetic experiments in which ECBPK and the gauge-only precipitation analysis procedure used in the NWS's Multisensor Precipitation Estimator (MPE) were compared for estimation of point precipitation and mean areal precipitation (MAP), respectively. The results indicate that ECBPK improves hourly gauge-only estimation of heavy-to-extreme precipitation significantly. The improvement is particularly large for estimation of MAP for a range of combinations of basin size and rain gauge network density. This paper describes the technique, summarizes the results and shares ideas for future research.

A novel convective-scale regional reanalysis COSMO-REA2: Improving the representation of precipitation

Directory of Open Access Journals (Sweden)

Sabrina Wahl

2017-10-01

Full Text Available Atmospheric reanalyses are a state-of-the-art tool to generate consistent and realistic state estimates of the atmospheric system. They provide a synthesis of various heterogeneous observational systems and model simulations using a physical model together with a data assimilation scheme. Current reanalyses are mainly global, while regional reanalyses are emerging for North America, the polar region, and most recently for Europe. However, deep convection is still parameterized even in the regional reanalyses. A novel convective-scale regional reanalysis system for Central Europe (COSMO-REA2 has been developed by the Hans-Ertel Center for Weather Research – Climate Monitoring Branch. The system is based on the COSMO model and uses observational nudging for regional data assimilation. In addition to conventional observations, radar-derived rain rates are assimilated using latent heat nudging. With a horizontal grid-spacing of 2 km, the model runs without parameterization of deep moist convection. COSMO-REA2 produces horizontal wind fields that represent a realistic energy spectrum for horizontal scales above 14 km. COSMO-REA2 is currently available for seven years from 2007 to 2013.This study illustrates the improved representation of local precipitation over Germany by the convective-scale reanalysis COSMO-REA2 compared to coarser gridded European and global reanalyses. A systematic verification using rain gauge data reveals the added value of high-resolution regional atmospheric reanalyses on different time scales. On monthly to annual time scales, regional reanalyses yield better estimates of the spatial variability of precipitation patterns which can not be provided by coarser gridded global models. On hourly to daily time scales, the convective-scale reanalysis substantially improves the representation of local precipitation in two ways. On the one hand, COSMO-REA2 shows an enhanced representation of observed frequencies of local

Mediterranean hurricanes: large-scale environment and convective and precipitating areas from satellite microwave observations

Directory of Open Access Journals (Sweden)

C. Claud

2010-10-01

Full Text Available Subsynoptic scale vortices that have been likened to tropical cyclones or polar lows (medicanes are occasionally observed over the Mediterranean Sea. Generated over the sea, they are usually associated with strong winds and heavy precipitation and thus can be highly destructive in islands and costal areas. Only an accurate forecasting of such systems could mitigate these effects. However, at the moment, the predictability of these systems remains limited.

Due to the scarcity of conventional observations, use is made of NOAA/MetOp satellite observations, for which advantage can be taken of the time coverage differences between the platforms that carry it, to give a very complete temporal description of the disturbances. A combination of AMSU-B (Advanced Microwave Sounding Unit-B/MHS (Microwave Humidity Sounder observations permit to investigate precipitation associated with these systems while coincident AMSU-A (Advanced Microwave Sounding Unit-A observations give insights into the larger synoptic-scale environment in which they occur.

Three different cases (in terms of intensity, location, trajectory, duration, and periods of the year – May, September and December, respectively were investigated. Throughout these time periods, AMSU-A observations show that the persisting deep outflow of cold air over the sea together with an upper-level trough upstream constituted a favourable environment for the development of medicanes. AMSU-B/MHS based diagnostics show that convection and precipitation areas are large in the early stage of the low, but significantly reduced afterwards. Convection is maximum just after the upper-level trough, located upstream of cold mid-tropospheric air, reached its maximum intensity and acquired a cyclonic orientation.

Rain Characteristics and Large-Scale Environments of Precipitation Objects with Extreme Rain Volumes from TRMM Observations

Science.gov (United States)

Zhou, Yaping; Lau, William K M.; Liu, Chuntao

2013-01-01

This study adopts a "precipitation object" approach by using 14 years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Feature (PF) and National Centers for Environmental Prediction (NCEP) reanalysis data to study rainfall structure and environmental factors associated with extreme heavy rain events. Characteristics of instantaneous extreme volumetric PFs are examined and compared to those of intermediate and small systems. It is found that instantaneous PFs exhibit a much wider scale range compared to the daily gridded precipitation accumulation range. The top 1% of the rainiest PFs contribute over 55% of total rainfall and have 2 orders of rain volume magnitude greater than those of the median PFs. We find a threshold near the top 10% beyond which the PFs grow exponentially into larger, deeper, and colder rain systems. NCEP reanalyses show that midlevel relative humidity and total precipitable water increase steadily with increasingly larger PFs, along with a rapid increase of 500 hPa upward vertical velocity beyond the top 10%. This provides the necessary moisture convergence to amplify and sustain the extreme events. The rapid increase in vertical motion is associated with the release of convective available potential energy (CAPE) in mature systems, as is evident in the increase in CAPE of PFs up to 10% and the subsequent dropoff. The study illustrates distinct stages in the development of an extreme rainfall event including: (1) a systematic buildup in large-scale temperature and moisture, (2) a rapid change in rain structure, (3) explosive growth of the PF size, and (4) a release of CAPE before the demise of the event.

Pareto-optimal estimates that constrain mean California precipitation change

Science.gov (United States)

Langenbrunner, B.; Neelin, J. D.

2017-12-01

Global climate model (GCM) projections of greenhouse gas-induced precipitation change can exhibit notable uncertainty at the regional scale, particularly in regions where the mean change is small compared to internal variability. This is especially true for California, which is located in a transition zone between robust precipitation increases to the north and decreases to the south, and where GCMs from the Climate Model Intercomparison Project phase 5 (CMIP5) archive show no consensus on mean change (in either magnitude or sign) across the central and southern parts of the state. With the goal of constraining this uncertainty, we apply a multiobjective approach to a large set of subensembles (subsets of models from the full CMIP5 ensemble). These constraints are based on subensemble performance in three fields important to California precipitation: tropical Pacific sea surface temperatures, upper-level zonal winds in the midlatitude Pacific, and precipitation over the state. An evolutionary algorithm is used to sort through and identify the set of Pareto-optimal subensembles across these three measures in the historical climatology, and we use this information to constrain end-of-century California wet season precipitation change. This technique narrows the range of projections throughout the state and increases confidence in estimates of positive mean change. Furthermore, these methods complement and generalize emergent constraint approaches that aim to restrict uncertainty in end-of-century projections, and they have applications to even broader aspects of uncertainty quantification, including parameter sensitivity and model calibration.

Global precipitations and climate change. Proceedings

International Nuclear Information System (INIS)

Desbois, M.; Desalmand, F.

1994-01-01

The workshop reviewed the present status of knowledge concerning the past and present evolution of the distribution of precipitations at global scale, related to climate evolution at different time scales. This review was intended to assess the availability and quality of data which could help, through validation and initialization of model studies, to improve our understanding of the processes determining these precipitation changes. On another hand, the modelling specialists presented their actual use of precipitation data. Exchanges of views between the modelling and observing communities were thus made possible, leading to a set of recommendations for future studies. Sessions were then devoted to specific themes: 1) Paleoclimatology, 2) data collection, history and statistics, programmes, 3) methodologies and accuracy of large scale estimation of precipitation from conventional data, 4) estimation of precipitation from satellite data, 5) modelling studies. (orig.)

Spring soil moisture-precipitation feedback in the Southern Great Plains: How is it related to large-scale atmospheric conditions?

KAUST Repository

Su, Hua

2014-02-22

The Southern Great Plains (SGP) has been shown as a region of significant soil moisture-precipitation (S-P) coupling. However, how strong evapotranspiration (ET) can affect regional precipitation remains largely unclear, impeding a full grasp of the S-P feedback in that area. The current study seeks to unravel, in a spring month (April), the potential role played by large-scale atmospheric conditions in shaping S (ET)-P feedback. Our regional climate modeling experiments demonstrate that the presence of anomalous low (high) pressure and cyclonic (anticyclonic) flows at the upper/middle troposphere over the relevant areas is associated with strongest (minimum) positive S-P feedback in the SGP. Their impacts are interpreted in terms of large-scale atmospheric dynamical disturbance, including the intensity and location of synoptic eddies. Further analyses of the vertical velocity fields corroborate these interpretations. In addition, the relationship between lower tropospheric moisture conditions (including winds) and feedback composites is evaluated. Key Points The S-P feedback strength in SGP in April varies inter-annually The atmospheric dynamic features affect significantly the feedback strength composite moisture conditions are related to atmospheric circulation structure ©2014. American Geophysical Union. All Rights Reserved.

Spring soil moisture-precipitation feedback in the Southern Great Plains: How is it related to large-scale atmospheric conditions?

KAUST Repository

Su, Hua; Yang, Zong-Liang; Dickinson, Robert E.; Wei, Jiangfeng

2014-01-01

The Southern Great Plains (SGP) has been shown as a region of significant soil moisture-precipitation (S-P) coupling. However, how strong evapotranspiration (ET) can affect regional precipitation remains largely unclear, impeding a full grasp of the S-P feedback in that area. The current study seeks to unravel, in a spring month (April), the potential role played by large-scale atmospheric conditions in shaping S (ET)-P feedback. Our regional climate modeling experiments demonstrate that the presence of anomalous low (high) pressure and cyclonic (anticyclonic) flows at the upper/middle troposphere over the relevant areas is associated with strongest (minimum) positive S-P feedback in the SGP. Their impacts are interpreted in terms of large-scale atmospheric dynamical disturbance, including the intensity and location of synoptic eddies. Further analyses of the vertical velocity fields corroborate these interpretations. In addition, the relationship between lower tropospheric moisture conditions (including winds) and feedback composites is evaluated. Key Points The S-P feedback strength in SGP in April varies inter-annually The atmospheric dynamic features affect significantly the feedback strength composite moisture conditions are related to atmospheric circulation structure ©2014. American Geophysical Union. All Rights Reserved.

Spatial Downscaling of TRMM Precipitation Using Geostatistics and Fine Scale Environmental Variables

Directory of Open Access Journals (Sweden)

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.

Reconstructions of spring/summer precipitation for the Eastern Mediterranean from tree-ring widths and its connection to large-scale atmospheric circulation

Energy Technology Data Exchange (ETDEWEB)

Touchan, Ramzi; Funkhouser, Gary; Hughes, Malcolm K. [The University of Arizona, Laboratory of Tree-Ring Research, Tucson, AZ (United States); Xoplaki, Elena; Luterbacher, Juerg [University of Bern, Institute of Geography and NCCR Climate, Bern (Switzerland); Erkan, Nesat [Southwest Anatolia Forest Research Institute (SAFRI), Antalya (Turkey); Akkemik, Uenal [University of Istanbul, Faculty of Forestry, Department of Forest Botany, Bahcekoey-Istanbul (Turkey); Stephan, Jean [Ministry of Agriculture, Forestry Department, Beirut (Lebanon)

2005-07-01

This study represents the first large-scale systematic dendroclimatic sampling focused on developing chronologies from different species in the eastern Mediterranean region. Six reconstructions were developed from chronologies ranging in length from 115 years to 600 years. The first reconstruction (1885-2000) was derived from principal components (PCs) of 36 combined chronologies. The remaining five, 1800-2000, 1700-2000, 1600-2000, 1500-2000 and 1400-2000 were developed from PCs of 32, 18, 14, 9, and 7 chronologies, respectively. Calibration and verification statistics for the period 1931-2000 show good levels of skill for all reconstructions. The longest period of consecutive dry years, defined as those with less than 90% of the mean of the observed May-August precipitation, was 5 years (1591-1595) and occurred only once during the last 600 years. The longest reconstructed wet period was 5 years (1601-1605 and 1751-1755). No long term trends were found in May-August precipitation during the last few centuries. Regression maps are used to identify the influence of large-scale atmospheric circulation on regional precipitation. In general, tree-ring indices are influenced by May-August precipitation, which is driven by anomalous below (above) normal pressure at all atmospheric levels and by convection (subsidence) and small pressure gradients at sea level. These atmospheric conditions also control the anomaly surface air temperature distribution which indicates below (above) normal values in the southern regions and warmer (cooler) conditions north of around 40 N. A compositing technique is used to extract information on large-scale climate signals from extreme wet and dry summers for the second half of the twentieth century and an independent reconstruction over the last 237 years. Similar main modes of atmospheric patterns and surface air temperature distribution related to extreme dry and wet summers were identified both for the most recent 50 years and the last

The effect of scale in daily precipitation hazard assessment

Directory of Open Access Journals (Sweden)

J. J. Egozcue

2006-01-01

Full Text Available Daily precipitation is recorded as the total amount of water collected by a rain-gauge in 24 h. Events are modelled as a Poisson process and the 24 h precipitation by a Generalised Pareto Distribution (GPD of excesses. Hazard assessment is complete when estimates of the Poisson rate and the distribution parameters, together with a measure of their uncertainty, are obtained. The shape parameter of the GPD determines the support of the variable: Weibull domain of attraction (DA corresponds to finite support variables as should be for natural phenomena. However, Fréchet DA has been reported for daily precipitation, which implies an infinite support and a heavy-tailed distribution. Bayesian techniques are used to estimate the parameters. The approach is illustrated with precipitation data from the Eastern coast of the Iberian Peninsula affected by severe convective precipitation. The estimated GPD is mainly in the Fréchet DA, something incompatible with the common sense assumption of that precipitation is a bounded phenomenon. The bounded character of precipitation is then taken as a priori hypothesis. Consistency of this hypothesis with the data is checked in two cases: using the raw-data (in mm and using log-transformed data. As expected, a Bayesian model checking clearly rejects the model in the raw-data case. However, log-transformed data seem to be consistent with the model. This fact may be due to the adequacy of the log-scale to represent positive measurements for which differences are better relative than absolute.

Scale-up of precipitation processes

OpenAIRE

Zauner, R.

1999-01-01

This thesis concerns the scale-up of precipitation processes aimed at predicting product particle characteristics. Although precipitation is widely used in the chemical and pharmaceutical industry, successful scale-up is difficult due to the absence of a validated methodology. It is found that none of the conventional scale-up criteria reported in the literature (equal power input per unit mass, equal tip speed, equal stirring rate) is capable of predicting the experimentally o...

Connecting Satellite-Based Precipitation Estimates to Users

Science.gov (United States)

Huffman, George J.; Bolvin, David T.; Nelkin, Eric

2018-01-01

Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

Large Scale Influences on Summertime Extreme Precipitation in the Northeastern United States

Science.gov (United States)

Collow, Allison B. Marquardt; Bosilovich, Michael G.; Koster, Randal Dean

2016-01-01

Observations indicate that over the last few decades there has been a statistically significant increase in precipitation in the northeastern United States and that this can be attributed to an increase in precipitation associated with extreme precipitation events. Here a state-of-the-art atmospheric reanalysis is used to examine such events in detail. Daily extreme precipitation events defined at the 75th and 95th percentile from gridded gauge observations are identified for a selected region within the Northeast. Atmospheric variables from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), are then composited during these events to illustrate the time evolution of associated synoptic structures, with a focus on vertically integrated water vapor fluxes, sea level pressure, and 500-hectopascal heights. Anomalies of these fields move into the region from the northwest, with stronger anomalies present in the 95th percentile case. Although previous studies show tropical cyclones are responsible for the most intense extreme precipitation events, only 10 percent of the events in this study are caused by tropical cyclones. On the other hand, extreme events resulting from cutoff low pressure systems have increased. The time period of the study was divided in half to determine how the mean composite has changed over time. An arc of lower sea level pressure along the East Coast and a change in the vertical profile of equivalent potential temperature suggest a possible increase in the frequency or intensity of synoptic-scale baroclinic disturbances.

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

Science.gov (United States)

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.

Cardinality Estimation Algorithm in Large-Scale Anonymous Wireless Sensor Networks

KAUST Repository

Douik, Ahmed

2017-08-30

Consider a large-scale anonymous wireless sensor network with unknown cardinality. In such graphs, each node has no information about the network topology and only possesses a unique identifier. This paper introduces a novel distributed algorithm for cardinality estimation and topology discovery, i.e., estimating the number of node and structure of the graph, by querying a small number of nodes and performing statistical inference methods. While the cardinality estimation allows the design of more efficient coding schemes for the network, the topology discovery provides a reliable way for routing packets. The proposed algorithm is shown to produce a cardinality estimate proportional to the best linear unbiased estimator for dense graphs and specific running times. Simulation results attest the theoretical results and reveal that, for a reasonable running time, querying a small group of nodes is sufficient to perform an estimation of 95% of the whole network. Applications of this work include estimating the number of Internet of Things (IoT) sensor devices, online social users, active protein cells, etc.

Distributed weighted least-squares estimation with fast convergence for large-scale systems☆

Science.gov (United States)

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods. PMID:25641976

Distributed weighted least-squares estimation with fast convergence for large-scale systems.

Science.gov (United States)

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods.

Incorporating Satellite Precipitation Estimates into a Radar-Gauge Multi-Sensor Precipitation Estimation Algorithm

Directory of Open Access Journals (Sweden)

Yuxiang He

2018-01-01

Full Text Available This paper presents a new and enhanced fusion module for the Multi-Sensor Precipitation Estimator (MPE that would objectively blend real-time satellite quantitative precipitation estimates (SQPE with radar and gauge estimates. This module consists of a preprocessor that mitigates systematic bias in SQPE, and a two-way blending routine that statistically fuses adjusted SQPE with radar estimates. The preprocessor not only corrects systematic bias in SQPE, but also improves the spatial distribution of precipitation based on SQPE and makes it closely resemble that of radar-based observations. It uses a more sophisticated radar-satellite merging technique to blend preprocessed datasets, and provides a better overall QPE product. The performance of the new satellite-radar-gauge blending module is assessed using independent rain gauge data over a five-year period between 2003–2007, and the assessment evaluates the accuracy of newly developed satellite-radar-gauge (SRG blended products versus that of radar-gauge products (which represents MPE algorithm currently used in the NWS (National Weather Service operations over two regions: (I Inside radar effective coverage and (II immediately outside radar coverage. The outcomes of the evaluation indicate (a ingest of SQPE over areas within effective radar coverage improve the quality of QPE by mitigating the errors in radar estimates in region I; and (b blending of radar, gauge, and satellite estimates over region II leads to reduction of errors relative to bias-corrected SQPE. In addition, the new module alleviates the discontinuities along the boundaries of radar effective coverage otherwise seen when SQPE is used directly to fill the areas outside of effective radar coverage.

Pareto-Optimal Estimates of California Precipitation Change

Science.gov (United States)

Langenbrunner, Baird; Neelin, J. David

2017-12-01

In seeking constraints on global climate model projections under global warming, one commonly finds that different subsets of models perform well under different objective functions, and these trade-offs are difficult to weigh. Here a multiobjective approach is applied to a large set of subensembles generated from the Climate Model Intercomparison Project phase 5 ensemble. We use observations and reanalyses to constrain tropical Pacific sea surface temperatures, upper level zonal winds in the midlatitude Pacific, and California precipitation. An evolutionary algorithm identifies the set of Pareto-optimal subensembles across these three measures, and these subensembles are used to constrain end-of-century California wet season precipitation change. This methodology narrows the range of projections throughout California, increasing confidence in estimates of positive mean precipitation change. Finally, we show how this technique complements and generalizes emergent constraint approaches for restricting uncertainty in end-of-century projections within multimodel ensembles using multiple criteria for observational constraints.

Estimating large carnivore populations at global scale based on spatial predictions of density and distribution – Application to the jaguar (Panthera onca)

Science.gov (United States)

Robinson, Hugh S.; Abarca, Maria; Zeller, Katherine A.; Velasquez, Grisel; Paemelaere, Evi A. D.; Goldberg, Joshua F.; Payan, Esteban; Hoogesteijn, Rafael; Boede, Ernesto O.; Schmidt, Krzysztof; Lampo, Margarita; Viloria, Ángel L.; Carreño, Rafael; Robinson, Nathaniel; Lukacs, Paul M.; Nowak, J. Joshua; Salom-Pérez, Roberto; Castañeda, Franklin; Boron, Valeria; Quigley, Howard

2018-01-01

Broad scale population estimates of declining species are desired for conservation efforts. However, for many secretive species including large carnivores, such estimates are often difficult. Based on published density estimates obtained through camera trapping, presence/absence data, and globally available predictive variables derived from satellite imagery, we modelled density and occurrence of a large carnivore, the jaguar, across the species’ entire range. We then combined these models in a hierarchical framework to estimate the total population. Our models indicate that potential jaguar density is best predicted by measures of primary productivity, with the highest densities in the most productive tropical habitats and a clear declining gradient with distance from the equator. Jaguar distribution, in contrast, is determined by the combined effects of human impacts and environmental factors: probability of jaguar occurrence increased with forest cover, mean temperature, and annual precipitation and declined with increases in human foot print index and human density. Probability of occurrence was also significantly higher for protected areas than outside of them. We estimated the world’s jaguar population at 173,000 (95% CI: 138,000–208,000) individuals, mostly concentrated in the Amazon Basin; elsewhere, populations tend to be small and fragmented. The high number of jaguars results from the large total area still occupied (almost 9 million km2) and low human densities (conservation actions. PMID:29579129

Influences of large-scale convection and moisture source on monthly precipitation isotope ratios observed in Thailand, Southeast Asia

Science.gov (United States)

Wei, Zhongwang; Lee, Xuhui; Liu, Zhongfang; Seeboonruang, Uma; Koike, Masahiro; Yoshimura, Kei

2018-04-01

Many paleoclimatic records in Southeast Asia rely on rainfall isotope ratios as proxies for past hydroclimatic variability. However, the physical processes controlling modern rainfall isotopic behaviors in the region is poorly constrained. Here, we combined isotopic measurements at six sites across Thailand with an isotope-incorporated atmospheric circulation model (IsoGSM) and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to investigate the factors that govern the variability of precipitation isotope ratios in this region. Results show that rainfall isotope ratios are both correlated with local rainfall amount and regional outgoing longwave radiation, suggesting that rainfall isotope ratios in this region are controlled not only by local rain amount (amount effect) but also by large-scale convection. As a transition zone between the Indian monsoon and the western North Pacific monsoon, the spatial difference of observed precipitation isotope among different sites are associated with moisture source. These results highlight the importance of regional processes in determining rainfall isotope ratios in the tropics and provide constraints on the interpretation of paleo-precipitation isotope records in the context of regional climate dynamics.

Evaluating 20th Century precipitation characteristics between multi-scale atmospheric models with different land-atmosphere coupling

Science.gov (United States)

Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.

2016-12-01

Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.

Hydrometeorological variability on a large french catchment and its relation to large-scale circulation across temporal scales

Science.gov (United States)

Massei, Nicolas; Dieppois, Bastien; Fritier, Nicolas; Laignel, Benoit; Debret, Maxime; Lavers, David; Hannah, David

2015-04-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating large-scale/local-scale correlation, enmpirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the large-scale/local-scale links were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach which integrated discrete wavelet multiresolution analysis for reconstructing local hydrometeorological processes (predictand : precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector) on a monthly time-step. This approach

Surface Runoff Estimation Using SMOS Observations, Rain-gauge Measurements and Satellite Precipitation Estimations. Comparison with Model Predictions

Science.gov (United States)

Garcia Leal, Julio A.; Lopez-Baeza, Ernesto; Khodayar, Samiro; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Kuligowski, Robert; Herrera, Eddy

Surface runoff is defined as the amount of water that originates from precipitation, does not infiltrates due to soil saturation and therefore circulates over the surface. A good estimation of runoff is useful for the design of draining systems, structures for flood control and soil utilisation. For runoff estimation there exist different methods such as (i) rational method, (ii) isochrone method, (iii) triangular hydrograph, (iv) non-dimensional SCS hydrograph, (v) Temez hydrograph, (vi) kinematic wave model, represented by the dynamics and kinematics equations for a uniforme precipitation regime, and (vii) SCS-CN (Soil Conservation Service Curve Number) model. This work presents a way of estimating precipitation runoff through the SCS-CN model, using SMOS (Soil Moisture and Ocean Salinity) mission soil moisture observations and rain-gauge measurements, as well as satellite precipitation estimations. The area of application is the Jucar River Basin Authority area where one of the objectives is to develop the SCS-CN model in a spatial way. The results were compared to simulations performed with the 7-km COSMO-CLM (COnsortium for Small-scale MOdelling, COSMO model in CLimate Mode) model. The use of SMOS soil moisture as input to the COSMO-CLM model will certainly improve model simulations.

Improving Satellite Quantitative Precipitation Estimation Using GOES-Retrieved Cloud Optical Depth

Energy Technology Data Exchange (ETDEWEB)

Stenz, Ronald; Dong, Xiquan; Xi, Baike; Feng, Zhe; Kuligowski, Robert J.

2016-02-01

To address significant gaps in ground-based radar coverage and rain gauge networks in the U.S., geostationary satellite quantitative precipitation estimates (QPEs) such as the Self-Calibrating Multivariate Precipitation Retrievals (SCaMPR) can be used to fill in both the spatial and temporal gaps of ground-based measurements. Additionally, with the launch of GOES-R, the temporal resolution of satellite QPEs may be comparable to that of Weather Service Radar-1988 Doppler (WSR-88D) volume scans as GOES images will be available every five minutes. However, while satellite QPEs have strengths in spatial coverage and temporal resolution, they face limitations particularly during convective events. Deep Convective Systems (DCSs) have large cloud shields with similar brightness temperatures (BTs) over nearly the entire system, but widely varying precipitation rates beneath these clouds. Geostationary satellite QPEs relying on the indirect relationship between BTs and precipitation rates often suffer from large errors because anvil regions (little/no precipitation) cannot be distinguished from rain-cores (heavy precipitation) using only BTs. However, a combination of BTs and optical depth (τ) has been found to reduce overestimates of precipitation in anvil regions (Stenz et al. 2014). A new rain mask algorithm incorporating both τ and BTs has been developed, and its application to the existing SCaMPR algorithm was evaluated. The performance of the modified SCaMPR was evaluated using traditional skill scores and a more detailed analysis of performance in individual DCS components by utilizing the Feng et al. (2012) classification algorithm. SCaMPR estimates with the new rain mask applied benefited from significantly reduced overestimates of precipitation in anvil regions and overall improvements in skill scores.

Disinformative data in large-scale hydrological modelling

Directory of Open Access Journals (Sweden)

A. Kauffeldt

2013-07-01

Full Text Available Large-scale hydrological modelling has become an important tool for the study of global and regional water resources, climate impacts, and water-resources management. However, modelling efforts over large spatial domains are fraught with problems of data scarcity, uncertainties and inconsistencies between model forcing and evaluation data. Model-independent methods to screen and analyse data for such problems are needed. This study aimed at identifying data inconsistencies in global datasets using a pre-modelling analysis, inconsistencies that can be disinformative for subsequent modelling. The consistency between (i basin areas for different hydrographic datasets, and (ii between climate data (precipitation and potential evaporation and discharge data, was examined in terms of how well basin areas were represented in the flow networks and the possibility of water-balance closure. It was found that (i most basins could be well represented in both gridded basin delineations and polygon-based ones, but some basins exhibited large area discrepancies between flow-network datasets and archived basin areas, (ii basins exhibiting too-high runoff coefficients were abundant in areas where precipitation data were likely affected by snow undercatch, and (iii the occurrence of basins exhibiting losses exceeding the potential-evaporation limit was strongly dependent on the potential-evaporation data, both in terms of numbers and geographical distribution. Some inconsistencies may be resolved by considering sub-grid variability in climate data, surface-dependent potential-evaporation estimates, etc., but further studies are needed to determine the reasons for the inconsistencies found. Our results emphasise the need for pre-modelling data analysis to identify dataset inconsistencies as an important first step in any large-scale study. Applying data-screening methods before modelling should also increase our chances to draw robust conclusions from subsequent

Dynamic state estimation techniques for large-scale electric power systems

International Nuclear Information System (INIS)

Rousseaux, P.; Pavella, M.

1991-01-01

This paper presents the use of dynamic type state estimators for energy management in electric power systems. Various dynamic type estimators have been developed, but have never been implemented. This is primarily because of dimensionality problems posed by the conjunction of an extended Kalman filter with a large scale power system. This paper precisely focuses on how to circumvent the high dimensionality, especially prohibitive in the filtering step, by using a decomposition-aggregation hierarchical scheme; to appropriately model the power system dynamics, the authors introduce new state variables in the prediction step and rely on a load forecasting method. The combination of these two techniques succeeds in solving the overall dynamic state estimation problem not only in a tractable and realistic way, but also in compliance with real-time computational requirements. Further improvements are also suggested, bound to the specifics of the high voltage electric transmission systems

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.

Radar-Derived Quantitative Precipitation Estimation Based on Precipitation Classification

Directory of Open Access Journals (Sweden)

Lili Yang

2016-01-01

Full Text Available A method for improving radar-derived quantitative precipitation estimation is proposed. Tropical vertical profiles of reflectivity (VPRs are first determined from multiple VPRs. Upon identifying a tropical VPR, the event can be further classified as either tropical-stratiform or tropical-convective rainfall by a fuzzy logic (FL algorithm. Based on the precipitation-type fields, the reflectivity values are converted into rainfall rate using a Z-R relationship. In order to evaluate the performance of this rainfall classification scheme, three experiments were conducted using three months of data and two study cases. In Experiment I, the Weather Surveillance Radar-1988 Doppler (WSR-88D default Z-R relationship was applied. In Experiment II, the precipitation regime was separated into convective and stratiform rainfall using the FL algorithm, and corresponding Z-R relationships were used. In Experiment III, the precipitation regime was separated into convective, stratiform, and tropical rainfall, and the corresponding Z-R relationships were applied. The results show that the rainfall rates obtained from all three experiments match closely with the gauge observations, although Experiment II could solve the underestimation, when compared to Experiment I. Experiment III significantly reduced this underestimation and generated the most accurate radar estimates of rain rate among the three experiments.

Improving multisensor estimation of heavy-to-extreme precipitation via conditional bias-penalized optimal estimation

Science.gov (United States)

Kim, Beomgeun; Seo, Dong-Jun; Noh, Seong Jin; Prat, Olivier P.; Nelson, Brian R.

2018-01-01

A new technique for merging radar precipitation estimates and rain gauge data is developed and evaluated to improve multisensor quantitative precipitation estimation (QPE), in particular, of heavy-to-extreme precipitation. Unlike the conventional cokriging methods which are susceptible to conditional bias (CB), the proposed technique, referred to herein as conditional bias-penalized cokriging (CBPCK), explicitly minimizes Type-II CB for improved quantitative estimation of heavy-to-extreme precipitation. CBPCK is a bivariate version of extended conditional bias-penalized kriging (ECBPK) developed for gauge-only analysis. To evaluate CBPCK, cross validation and visual examination are carried out using multi-year hourly radar and gauge data in the North Central Texas region in which CBPCK is compared with the variant of the ordinary cokriging (OCK) algorithm used operationally in the National Weather Service Multisensor Precipitation Estimator. The results show that CBPCK significantly reduces Type-II CB for estimation of heavy-to-extreme precipitation, and that the margin of improvement over OCK is larger in areas of higher fractional coverage (FC) of precipitation. When FC > 0.9 and hourly gauge precipitation is > 60 mm, the reduction in root mean squared error (RMSE) by CBPCK over radar-only (RO) is about 12 mm while the reduction in RMSE by OCK over RO is about 7 mm. CBPCK may be used in real-time analysis or in reanalysis of multisensor precipitation for which accurate estimation of heavy-to-extreme precipitation is of particular importance.

Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

Science.gov (United States)

Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

2011-01-01

The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

Cerebral methodology based computing to estimate real phenomena from large-scale nuclear simulation

International Nuclear Information System (INIS)

Suzuki, Yoshio

2011-01-01

Our final goal is to estimate real phenomena from large-scale nuclear simulations by using computing processes. Large-scale simulations mean that they include scale variety and physical complexity so that corresponding experiments and/or theories do not exist. In nuclear field, it is indispensable to estimate real phenomena from simulations in order to improve the safety and security of nuclear power plants. Here, the analysis of uncertainty included in simulations is needed to reveal sensitivity of uncertainty due to randomness, to reduce the uncertainty due to lack of knowledge and to lead a degree of certainty by verification and validation (V and V) and uncertainty quantification (UQ) processes. To realize this, we propose 'Cerebral Methodology based Computing (CMC)' as computing processes with deductive and inductive approaches by referring human reasoning processes. Our idea is to execute deductive and inductive simulations contrasted with deductive and inductive approaches. We have established its prototype system and applied it to a thermal displacement analysis of a nuclear power plant. The result shows that our idea is effective to reduce the uncertainty and to get the degree of certainty. (author)

Fast Component Pursuit for Large-Scale Inverse Covariance Estimation.

Science.gov (United States)

Han, Lei; Zhang, Yu; Zhang, Tong

2016-08-01

The maximum likelihood estimation (MLE) for the Gaussian graphical model, which is also known as the inverse covariance estimation problem, has gained increasing interest recently. Most existing works assume that inverse covariance estimators contain sparse structure and then construct models with the ℓ 1 regularization. In this paper, different from existing works, we study the inverse covariance estimation problem from another perspective by efficiently modeling the low-rank structure in the inverse covariance, which is assumed to be a combination of a low-rank part and a diagonal matrix. One motivation for this assumption is that the low-rank structure is common in many applications including the climate and financial analysis, and another one is that such assumption can reduce the computational complexity when computing its inverse. Specifically, we propose an efficient COmponent Pursuit (COP) method to obtain the low-rank part, where each component can be sparse. For optimization, the COP method greedily learns a rank-one component in each iteration by maximizing the log-likelihood. Moreover, the COP algorithm enjoys several appealing properties including the existence of an efficient solution in each iteration and the theoretical guarantee on the convergence of this greedy approach. Experiments on large-scale synthetic and real-world datasets including thousands of millions variables show that the COP method is faster than the state-of-the-art techniques for the inverse covariance estimation problem when achieving comparable log-likelihood on test data.

Temporal and spatial scaling impacts on extreme precipitation

Science.gov (United States)

Eggert, B.; Berg, P.; Haerter, J. O.; Jacob, D.; Moseley, C.

2015-01-01

Both in the current climate and in the light of climate change, understanding of the causes and risk of precipitation extremes is essential for protection of human life and adequate design of infrastructure. Precipitation extreme events depend qualitatively on the temporal and spatial scales at which they are measured, in part due to the distinct types of rain formation processes that dominate extremes at different scales. To capture these differences, we first filter large datasets of high-resolution radar measurements over Germany (5 min temporally and 1 km spatially) using synoptic cloud observations, to distinguish convective and stratiform rain events. In a second step, for each precipitation type, the observed data are aggregated over a sequence of time intervals and spatial areas. The resulting matrix allows a detailed investigation of the resolutions at which convective or stratiform events are expected to contribute most to the extremes. We analyze where the statistics of the two types differ and discuss at which resolutions transitions occur between dominance of either of the two precipitation types. We characterize the scales at which the convective or stratiform events will dominate the statistics. For both types, we further develop a mapping between pairs of spatially and temporally aggregated statistics. The resulting curve is relevant when deciding on data resolutions where statistical information in space and time is balanced. Our study may hence also serve as a practical guide for modelers, and for planning the space-time layout of measurement campaigns. We also describe a mapping between different pairs of resolutions, possibly relevant when working with mismatched model and observational resolutions, such as in statistical bias correction.

Estimating basin scale evapotranspiration (ET) by water balance and remote sensing methods

Science.gov (United States)

Senay, G.B.; Leake, S.; Nagler, P.L.; Artan, G.; Dickinson, J.; Cordova, J.T.; Glenn, E.P.

2011-01-01

Evapotranspiration (ET) is an important hydrological process that can be studied and estimated at multiple spatial scales ranging from a leaf to a river basin. We present a review of methods in estimating basin scale ET and its applications in understanding basin water balance dynamics. The review focuses on two aspects of ET: (i) how the basin scale water balance approach is used to estimate ET; and (ii) how ‘direct’ measurement and modelling approaches are used to estimate basin scale ET. Obviously, the basin water balance-based ET requires the availability of good precipitation and discharge data to calculate ET as a residual on longer time scales (annual) where net storage changes are assumed to be negligible. ET estimated from such a basin water balance principle is generally used for validating the performance of ET models. On the other hand, many of the direct estimation methods involve the use of remotely sensed data to estimate spatially explicit ET and use basin-wide averaging to estimate basin scale ET. The direct methods can be grouped into soil moisture balance modelling, satellite-based vegetation index methods, and methods based on satellite land surface temperature measurements that convert potential ET into actual ET using a proportionality relationship. The review also includes the use of complementary ET estimation principles for large area applications. The review identifies the need to compare and evaluate the different ET approaches using standard data sets in basins covering different hydro-climatic regions of the world.

Cosmological Parameter Estimation with Large Scale Structure Observations

CERN Document Server

Di Dio, Enea; Durrer, Ruth; Lesgourgues, Julien

2014-01-01

We estimate the sensitivity of future galaxy surveys to cosmological parameters, using the redshift dependent angular power spectra of galaxy number counts, $C_\\ell(z_1,z_2)$, calculated with all relativistic corrections at first order in perturbation theory. We pay special attention to the redshift dependence of the non-linearity scale and present Fisher matrix forecasts for Euclid-like and DES-like galaxy surveys. We compare the standard $P(k)$ analysis with the new $C_\\ell(z_1,z_2)$ method. We show that for surveys with photometric redshifts the new analysis performs significantly better than the $P(k)$ analysis. For spectroscopic redshifts, however, the large number of redshift bins which would be needed to fully profit from the redshift information, is severely limited by shot noise. We also identify surveys which can measure the lensing contribution and we study the monopole, $C_0(z_1,z_2)$.

Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy.

Science.gov (United States)

Penas, David R; González, Patricia; Egea, Jose A; Doallo, Ramón; Banga, Julio R

2017-01-21

The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times. Here we present a novel parallel method, self-adaptive cooperative enhanced scatter search (saCeSS), to accelerate the solution of this class of problems. The method is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies. The performance and robustness of saCeSS is illustrated by solving a set of challenging parameter estimation problems, including medium and large-scale kinetic models of the bacterium E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The results consistently show that saCeSS is a robust and efficient method, allowing very significant reduction of computation times with respect to several previous state of the art methods (from days to minutes, in several cases) even when only a small number of processors is used. The new parallel cooperative method presented here allows the solution of medium and large scale parameter estimation problems in reasonable computation times and with small hardware requirements. Further, the method includes self-tuning mechanisms which facilitate its use by non-experts. We believe that this new method can play a key role in the development of large-scale and even whole-cell dynamic models.

Scaling of Precipitation Extremes Modelled by Generalized Pareto Distribution

Science.gov (United States)

Rajulapati, C. R.; Mujumdar, P. P.

2017-12-01

Precipitation extremes are often modelled with data from annual maximum series or peaks over threshold series. The Generalized Pareto Distribution (GPD) is commonly used to fit the peaks over threshold series. Scaling of precipitation extremes from larger time scales to smaller time scales when the extremes are modelled with the GPD is burdened with difficulties arising from varying thresholds for different durations. In this study, the scale invariance theory is used to develop a disaggregation model for precipitation extremes exceeding specified thresholds. A scaling relationship is developed for a range of thresholds obtained from a set of quantiles of non-zero precipitation of different durations. The GPD parameters and exceedance rate parameters are modelled by the Bayesian approach and the uncertainty in scaling exponent is quantified. A quantile based modification in the scaling relationship is proposed for obtaining the varying thresholds and exceedance rate parameters for shorter durations. The disaggregation model is applied to precipitation datasets of Berlin City, Germany and Bangalore City, India. From both the applications, it is observed that the uncertainty in the scaling exponent has a considerable effect on uncertainty in scaled parameters and return levels of shorter durations.

Combinations of large-scale circulation anomalies conducive to precipitation extremes in the Czech Republic

Czech Academy of Sciences Publication Activity Database

Kašpar, Marek; Müller, Miloslav

2014-01-01

Roč. 138, March 2014 (2014), s. 205-212 ISSN 0169-8095 R&D Projects: GA ČR(CZ) GAP209/11/1990 Institutional support: RVO:68378289 Keywords : precipitation extreme * synoptic-scale cause * re-analysis * circulation anomaly Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 2.844, year: 2014 http://www.sciencedirect.com/science/article/pii/S0169809513003372

Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR upon TRMM Precipitation Radar (PR in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

Directory of Open Access Journals (Sweden)

Jinyu Gao

2017-11-01

Full Text Available Spaceborne precipitation radars are powerful tools used to acquire adequate and high-quality precipitation estimates with high spatial resolution for a variety of applications in hydrological research. The Global Precipitation Measurement (GPM mission, which deployed the first spaceborne Ka- and Ku-dual frequency radar (DPR, was launched in February 2014 as the upgraded successor of the Tropical Rainfall Measuring Mission (TRMM. This study matches the swath data of TRMM PR and GPM DPR Level 2 products during their overlapping periods at the global scale to investigate their similarities and DPR’s improvements concerning precipitation amount estimation and type classification of GPM DPR over TRMM PR. Results show that PR and DPR agree very well with each other in the global distribution of precipitation, while DPR improves the detectability of precipitation events significantly, particularly for light precipitation. The occurrences of total precipitation and the light precipitation (rain rates < 1 mm/h detected by GPM DPR are ~1.7 and ~2.53 times more than that of PR. With regard to type classification, the dual-frequency (Ka/Ku and single frequency (Ku methods performed similarly. In both inner (the central 25 beams and outer swaths (1–12 beams and 38–49 beams of DPR, the results are consistent. GPM DPR improves precipitation type classification remarkably, reducing the misclassification of clouds and noise signals as precipitation type “other” from 10.14% of TRMM PR to 0.5%. Generally, GPM DPR exhibits the same type division for around 82.89% (71.02% of stratiform (convective precipitation events recognized by TRMM PR. With regard to the freezing level height and bright band (BB height, both radars correspond with each other very well, contributing to the consistency in stratiform precipitation classification. Both heights show clear latitudinal dependence. Results in this study shall contribute to future development of spaceborne

Large-scale derived flood frequency analysis based on continuous simulation

Science.gov (United States)

Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several

Improving precipitation estimates over the western United States using GOES-R precipitation data

Science.gov (United States)

Karbalaee, N.; Kirstetter, P. E.; Gourley, J. J.

2017-12-01

Satellite remote sensing data with fine spatial and temporal resolution are widely used for precipitation estimation for different applications such as hydrological modeling, storm prediction, and flash flood monitoring. The Geostationary Operational Environmental Satellites-R series (GOES-R) is the next generation of environmental satellites that provides hydrologic, atmospheric, and climatic information every 30 seconds over the western hemisphere. The high-resolution and low-latency of GOES-R observations is essential for the monitoring and prediction of floods, specifically in the Western United States where the vantage point of space can complement the degraded weather radar coverage of the NEXRAD network. The GOES-R rainfall rate algorithm will yield deterministic quantitative precipitation estimates (QPE). Accounting for inherent uncertainties will further advance the GOES-R QPEs since with quantifiable error bars, the rainfall estimates can be more readily fused with ground radar products. On the ground, the high-resolution NEXRAD-based precipitation estimation from the Multi-Radar/Multi-Sensor (MRMS) system, which is now operational in the National Weather Service (NWS), is challenged due to a lack of suitable coverage of operational weather radars over complex terrain. Distribution of QPE uncertainties associated with the GOES-R deterministic retrievals are derived and analyzed using MRMS over regions with good radar coverage. They will be merged with MRMS-based probabilistic QPEs developed to advance multisensor QPE integration. This research aims at improving precipitation estimation over the CONUS by combining the observations from GOES-R and MRMS to provide consistent, accurate and fine resolution precipitation rates with uncertainties over the CONUS.

The impact of reflectivity correction and conversion methods to improve precipitation estimation by weather radar for an extreme low-land Mesoscale Convective System

Science.gov (United States)

Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

2014-05-01

, stratiform and undefined). These are then used to obtain coherent parameter sets for the radar reflectivity-rainfall rate (Z-R) and radar reflectivity-attenuation (Z-k) relationship, specifically applicable for this event. By applying a single parameter set to correct for both sources of errors, the quality of the rainfall product improves further, leading to >80% of the observed accumulations. However, by differentiating between precipitation type no better results are obtained as when using the operational relationships. This leads to the question: how representative are local disdrometer observations to correct large scale weather radar measurements? In order to tackle this question a Monte Carlo approach was used to generate >10000 sets of the normalized dropsize distribution parameters and to assess their impact on the estimated precipitation amounts. Results show that a large number of parameter sets result in improved precipitation estimated by the weather radar closely resembling observations. However, these optimal sets vary considerably as compared to those obtained from the local disdrometer measurements.

Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

Science.gov (United States)

Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William

2016-01-01

Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

LARGE-SCALE MAGNETIC HELICITY FLUXES ESTIMATED FROM MDI MAGNETIC SYNOPTIC CHARTS OVER THE SOLAR CYCLE 23

Energy Technology Data Exchange (ETDEWEB)

Yang Shangbin; Zhang Hongqi, E-mail: yangshb@nao.cas.cn [Key Laboratory of Solar Activity, National Astronomical Observatories, Chinese Academy of Sciences, 100012 Beijing (China)

2012-10-10

To investigate the characteristics of large-scale and long-term evolution of magnetic helicity with solar cycles, we use the method of Local Correlation Tracking to estimate the magnetic helicity evolution over solar cycle 23 from 1996 to 2009 using 795 MDI magnetic synoptic charts. The main results are as follows: the hemispheric helicity rule still holds in general, i.e., the large-scale negative (positive) magnetic helicity dominates the northern (southern) hemisphere. However, the large-scale magnetic helicity fluxes show the same sign in both hemispheres around 2001 and 2005. The global, large-scale magnetic helicity flux over the solar disk changes from a negative value at the beginning of solar cycle 23 to a positive value at the end of the cycle, while the net accumulated magnetic helicity is negative in the period between 1996 and 2009.

LARGE-SCALE MAGNETIC HELICITY FLUXES ESTIMATED FROM MDI MAGNETIC SYNOPTIC CHARTS OVER THE SOLAR CYCLE 23

International Nuclear Information System (INIS)

Yang Shangbin; Zhang Hongqi

2012-01-01

To investigate the characteristics of large-scale and long-term evolution of magnetic helicity with solar cycles, we use the method of Local Correlation Tracking to estimate the magnetic helicity evolution over solar cycle 23 from 1996 to 2009 using 795 MDI magnetic synoptic charts. The main results are as follows: the hemispheric helicity rule still holds in general, i.e., the large-scale negative (positive) magnetic helicity dominates the northern (southern) hemisphere. However, the large-scale magnetic helicity fluxes show the same sign in both hemispheres around 2001 and 2005. The global, large-scale magnetic helicity flux over the solar disk changes from a negative value at the beginning of solar cycle 23 to a positive value at the end of the cycle, while the net accumulated magnetic helicity is negative in the period between 1996 and 2009.

Plasma parameter estimations for the Large Helical Device based on the gyro-reduced Bohm scaling

International Nuclear Information System (INIS)

Okamoto, Masao; Nakajima, Noriyoshi; Sugama, Hideo.

1991-10-01

A model of gyro-reduced Bohm scaling law is incorporated into a one-dimensional transport code to predict plasma parameters for the Large Helical Device (LHD). The transport code calculations reproduce well the LHD empirical scaling law and basic parameters and profiles of the LHD plasma are calculated. The amounts of toroidal currents (bootstrap current and beam-driven current) are also estimated. (author)

The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset

Science.gov (United States)

Huffman, George J.; Adler, Robert F.; Arkin, Philip; Chang, Alfred; Ferraro, Ralph; Gruber, Arnold; Janowiak, John; McNab, Alan; Rudolf, Bruno; Schneider, Udo

1997-01-01

The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit -satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5 deg x 2.5 deg latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.

Antecedent precipitation index determined from CST estimates of rainfall

Science.gov (United States)

Martin, David W.

1992-01-01

This paper deals with an experimental calculation of a satellite-based antecedent precipitation index (API). The index is also derived from daily rain images produced from infrared images using an improved version of GSFC's Convective/Stratiform Technique (CST). API is a measure of soil moisture, and is based on the notion that the amount of moisture in the soil at a given time is related to precipitation at earlier times. Four different CST programs as well as the Geostationary Operational Enviroment Satellite (GOES) Precipitation Index developed by Arkin in 1979 are compared to experimental results, for the Mississippi Valley during the month of July. Rain images are shown for the best CST code and the ARK program. Comparisons are made as to the accuracy and detail of the results for the two codes. This project demonstrates the feasibility of running the CST on a synoptic scale. The Mississippi Valley case is well suited for testing the feasibility of monitoring soil moisture by means of CST. Preliminary comparisons of CST and ARK indicate significant differences in estimates of rain amount and distribution.

Opportunities and challenges for evaluating precipitation estimates during GPM mission

Energy Technology Data Exchange (ETDEWEB)

Amitai, E. [George Mason Univ. and NASA Goddard Space Flight Center, Greenbelt, MD (United States); NASA Goddard Space Flight Center, Greenbelt, MD (United States); Llort, X.; Sempere-Torres, D. [GRAHI/Univ. Politecnica de Catalunya, Barcelona (Spain)

2006-10-15

Data assimilation in conjunction with numerical weather prediction and a variety of hydrologic applications now depend on satellite observations of precipitation. However, providing values of precipitation is not sufficient unless they are accompanied by the associated uncertainty estimates. The main approach of quantifying satellite precipitation uncertainties generally requires establishment of reliable uncertainty estimates for the ground validation rainfall products. This paper discusses several of the relevant validation concepts evolving from the tropical rainfall measuring mission (TRMM) era to the global precipitation measurement mission (GPM) era in the context of determining and reducing uncertainties of ground and space-based radar rainfall estimates. From comparisons of probability distribution functions of rain rates derived from TRMM precipitation radar and co-located ground based radar data - using the new NASA TRMM radar rainfall products (version 6) - this paper provides (1) a brief review of the importance of comparing pdfs of rain rate for statistical and physical verification of space-borne radar estimates of precipitation; (2) a brief review of how well the ground validation estimates compare to the TRMM radar retrieved estimates; and (3) discussion on opportunities and challenges to determine and reduce the uncertainties in space-based and ground-based radar estimates of rain rate distributions. (orig.)

Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

Directory of Open Access Journals (Sweden)

Basile Pauthier

2016-01-01

Full Text Available A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1 PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2 both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3 PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE. This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

Global warming precipitation accumulation increases above the current-climate cutoff scale.

Science.gov (United States)

Neelin, J David; Sahany, Sandeep; Stechmann, Samuel N; Bernstein, Diana N

2017-02-07

Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff.

Global warming precipitation accumulation increases above the current-climate cutoff scale

Science.gov (United States)

Sahany, Sandeep; Stechmann, Samuel N.; Bernstein, Diana N.

2017-01-01

Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff. PMID:28115693

Precipitation Estimation Using L-Band and C-Band Soil Moisture Retrievals

Science.gov (United States)

Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

2016-01-01

An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to approximately100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.

A BAYESIAN ESTIMATE OF THE CMB–LARGE-SCALE STRUCTURE CROSS-CORRELATION

Energy Technology Data Exchange (ETDEWEB)

Moura-Santos, E. [Instituto de Física, Universidade de São Paulo, Rua do Matão trav. R 187, 05508-090, São Paulo—SP (Brazil); Carvalho, F. C. [Departamento de Física, Universidade do Estado do Rio Grande do Norte, 59610-210, Mossoró-RN (Brazil); Penna-Lima, M. [APC, AstroParticule et Cosmologie, Université Paris Diderot, CNRS/IN2P3, CEA/Irfu, Observatoire de Paris, Sorbonne Paris Cité, 10, rue Alice Domon et Léonie Duquet, F-75205 Paris Cedex 13 (France); Novaes, C. P.; Wuensche, C. A., E-mail: emoura@if.usp.br, E-mail: fabiocabral@uern.br, E-mail: pennal@apc.in2p3.fr, E-mail: cawuenschel@das.inpe.br, E-mail: camilanovaes@on.br [Observatório Nacional, Rua General José Cristino 77, São Cristóvão, 20921-400, Rio de Janeiro, RJ (Brazil)

2016-08-01

Evidences for late-time acceleration of the universe are provided by multiple probes, such as Type Ia supernovae, the cosmic microwave background (CMB), and large-scale structure (LSS). In this work, we focus on the integrated Sachs–Wolfe (ISW) effect, i.e., secondary CMB fluctuations generated by evolving gravitational potentials due to the transition between, e.g., the matter and dark energy (DE) dominated phases. Therefore, assuming a flat universe, DE properties can be inferred from ISW detections. We present a Bayesian approach to compute the CMB–LSS cross-correlation signal. The method is based on the estimate of the likelihood for measuring a combined set consisting of a CMB temperature and galaxy contrast maps, provided that we have some information on the statistical properties of the fluctuations affecting these maps. The likelihood is estimated by a sampling algorithm, therefore avoiding the computationally demanding techniques of direct evaluation in either pixel or harmonic space. As local tracers of the matter distribution at large scales, we used the Two Micron All Sky Survey galaxy catalog and, for the CMB temperature fluctuations, the ninth-year data release of the Wilkinson Microwave Anisotropy Probe ( WMAP 9). The results show a dominance of cosmic variance over the weak recovered signal, due mainly to the shallowness of the catalog used, with systematics associated with the sampling algorithm playing a secondary role as sources of uncertainty. When combined with other complementary probes, the method presented in this paper is expected to be a useful tool to late-time acceleration studies in cosmology.

Stochastically Estimating Modular Criticality in Large-Scale Logic Circuits Using Sparsity Regularization and Compressive Sensing

Directory of Open Access Journals (Sweden)

Mohammed Alawad

2015-03-01

Full Text Available This paper considers the problem of how to efficiently measure a large and complex information field with optimally few observations. Specifically, we investigate how to stochastically estimate modular criticality values in a large-scale digital circuit with a very limited number of measurements in order to minimize the total measurement efforts and time. We prove that, through sparsity-promoting transform domain regularization and by strategically integrating compressive sensing with Bayesian learning, more than 98% of the overall measurement accuracy can be achieved with fewer than 10% of measurements as required in a conventional approach that uses exhaustive measurements. Furthermore, we illustrate that the obtained criticality results can be utilized to selectively fortify large-scale digital circuits for operation with narrow voltage headrooms and in the presence of soft-errors rising at near threshold voltage levels, without excessive hardware overheads. Our numerical simulation results have shown that, by optimally allocating only 10% circuit redundancy, for some large-scale benchmark circuits, we can achieve more than a three-times reduction in its overall error probability, whereas if randomly distributing such 10% hardware resource, less than 2% improvements in the target circuit’s overall robustness will be observed. Finally, we conjecture that our proposed approach can be readily applied to estimate other essential properties of digital circuits that are critical to designing and analyzing them, such as the observability measure in reliability analysis and the path delay estimation in stochastic timing analysis. The only key requirement of our proposed methodology is that these global information fields exhibit a certain degree of smoothness, which is universally true for almost any physical phenomenon.

Orographic precipitation at global and regional scales: Observational uncertainty and evaluation of 25-km global model simulations

Science.gov (United States)

Schiemann, Reinhard; Roberts, Charles J.; Bush, Stephanie; Demory, Marie-Estelle; Strachan, Jane; Vidale, Pier Luigi; Mizielinski, Matthew S.; Roberts, Malcolm J.

2015-04-01

Precipitation over land exhibits a high degree of variability due to the complex interaction of the precipitation generating atmospheric processes with coastlines, the heterogeneous land surface, and orography. Global general circulation models (GCMs) have traditionally had very limited ability to capture this variability on the mesoscale (here ~50-500 km) due to their low resolution. This has changed with recent investments in resolution and ensembles of multidecadal climate simulations of atmospheric GCMs (AGCMs) with ~25 km grid spacing are becoming increasingly available. Here, we evaluate the mesoscale precipitation distribution in one such set of simulations obtained in the UPSCALE (UK on PrACE - weather-resolving Simulations of Climate for globAL Environmental risk) modelling campaign with the HadGEM-GA3 AGCM. Increased model resolution also poses new challenges to the observational datasets used to evaluate models. Global gridded data products such as those provided by the Global Precipitation Climatology Project (GPCP) are invaluable for assessing large-scale features of the precipitation distribution but may not sufficiently resolve mesoscale structures. In the absence of independent estimates, the intercomparison of different observational datasets may be the only way to get some insight into the uncertainties associated with these observations. Here, we focus on mid-latitude continental regions where observations based on higher-density gauge networks are available in addition to the global data sets: Europe/the Alps, South and East Asia, and the continental US. The ability of GCMs to represent mesoscale variability is of interest in its own right, as climate information on this scale is required by impact studies. An additional motivation for the research proposed here arises from continuing efforts to quantify the components of the global radiation budget and water cycle. Recent estimates based on radiation measurements suggest that the global mean

A spatial approach to the modelling and estimation of areal precipitation

Energy Technology Data Exchange (ETDEWEB)

Skaugen, T

1996-12-31

In hydroelectric power technology it is important that the mean precipitation that falls in an area can be calculated. This doctoral thesis studies how the morphology of rainfall, described by the spatial statistical parameters, can be used to improve interpolation and estimation procedures. It attempts to formulate a theory which includes the relations between the size of the catchment and the size of the precipitation events in the modelling of areal precipitation. The problem of estimating and modelling areal precipitation can be formulated as the problem of estimating an inhomogeneously distributed flux of a certain spatial extent being measured at points in a randomly placed domain. The information contained in the different morphology of precipitation types is used to improve estimation procedures of areal precipitation, by interpolation (kriging) or by constructing areal reduction factors. A new approach to precipitation modelling is introduced where the analysis of the spatial coverage of precipitation at different intensities plays a key role in the formulation of a stochastic model for extreme areal precipitation and in deriving the probability density function of areal precipitation. 127 refs., 30 figs., 13 tabs.

Variability in warm-season atmospheric circulation and precipitation patterns over subtropical South America: relationships between the South Atlantic convergence zone and large-scale organized convection over the La Plata basin

Science.gov (United States)

Mattingly, Kyle S.; Mote, Thomas L.

2017-01-01

Warm-season precipitation variability over subtropical South America is characterized by an inverse relationship between the South Atlantic convergence zone (SACZ) and precipitation over the central and western La Plata basin of southeastern South America. This study extends the analysis of this "South American Seesaw" precipitation dipole to relationships between the SACZ and large, long-lived mesoscale convective systems (LLCSs) over the La Plata basin. By classifying SACZ events into distinct continental and oceanic categories and building a logistic regression model that relates LLCS activity across the region to continental and oceanic SACZ precipitation, a detailed account of spatial variability in the out-of-phase coupling between the SACZ and large-scale organized convection over the La Plata basin is provided. Enhanced precipitation in the continental SACZ is found to result in increased LLCS activity over northern, northeastern, and western sections of the La Plata basin, in association with poleward atmospheric moisture flux from the Amazon basin toward these regions, and a decrease in the probability of LLCS occurrence over the southeastern La Plata basin. Increased oceanic SACZ precipitation, however, was strongly related to reduced atmospheric moisture and decreased probability of LLCS occurrence over nearly the entire La Plata basin. These results suggest that continental SACZ activity and large-scale organized convection over the northern and eastern sections of the La Plata basin are closely tied to atmospheric moisture transport from the Amazon basin, while the warm coastal Brazil Current may also play an important role as an evaporative moisture source for LLCSs over the central and western La Plata basin.

Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

Science.gov (United States)

Cheung, Kar-Ming; Jennings, Esther H.; Sergui, John S.

2013-01-01

A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of

Merging Radar Quantitative Precipitation Estimates (QPEs) from the High-resolution NEXRAD Reanalysis over CONUS with Rain-gauge Observations

Science.gov (United States)

Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Nickl, E.; Seo, D. J.; Kim, B.; Zhang, J.; Qi, Y.

2015-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over the Continental United States (CONUS) is completed for the period covering from 2002 to 2011. While this constitutes a unique opportunity to study precipitation processes at higher resolution than conventionally possible (1-km, 5-min), the long-term radar-only product needs to be merged with in-situ information in order to be suitable for hydrological, meteorological and climatological applications. The radar-gauge merging is performed by using rain gauge information at daily (Global Historical Climatology Network-Daily: GHCN-D), hourly (Hydrometeorological Automated Data System: HADS), and 5-min (Automated Surface Observing Systems: ASOS; Climate Reference Network: CRN) resolution. The challenges related to incorporating differing resolution and quality networks to generate long-term large-scale gridded estimates of precipitation are enormous. In that perspective, we are implementing techniques for merging the rain gauge datasets and the radar-only estimates such as Inverse Distance Weighting (IDW), Simple Kriging (SK), Ordinary Kriging (OK), and Conditional Bias-Penalized Kriging (CBPK). An evaluation of the different radar-gauge merging techniques is presented and we provide an estimate of uncertainty for the gridded estimates. In addition, comparisons with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) are provided in order to give a detailed picture of the improvements and remaining challenges.

Interannual variation of annual precipitation and urban effect on precipitation in the Beijing region

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

The large scale character of the interannual variation of precipitation and the urban effect on local annual precipitation anomaly are investigated in this paper based on the 1960-2000 annual precipitation observations at 20 stations in the Beijing region. The results show that: the annual precipitation in the Beijing region possesses the large scale variation character with the linear trend of - 1.197/10 yr, which corresponds to a total reduction of 27.82 mm in annual precipitation in the 41 years; the local annual precipitation anomalies (percent of the normal 1960-2000) show a positive center near the urban area, i.e. urban precipitation island (UPI), whose intensity increases with the linear trend of 0. 6621%/10 yr, opposite to the interannual trend of large scale precipitation over the Beijing region; changes in the UPI are also associated with the intensity of synoptic processes of precipitation, and when the synoptic processes are strong (wet years), the intensity of UPI strengthens, while the synoptic processes are weak (dry years), and the UPI disappears in the Beijing region.

Large-scale precipitation tracking and the MJO over the Maritime Continent and Indo-Pacific warm pool

Science.gov (United States)

Kerns, Brandon W.; Chen, Shuyi S.

2016-08-01

A large-scale precipitation tracking (LPT) method is developed to track convection and precipitation associated with the Madden-Julian oscillation (MJO) using the Tropical Rainfall Measurement Mission 3B42 rainfall data from October to March 1998-2015. LPT uses spatially smoothed 3 day rainfall accumulation to identify and track precipitation features in time with a minimum size of 300,000 km2 and time continuity at least 10 days. While not all LPT systems (LPTs) are attributable to the MJO, among the 199 LPTs, there were 42 with a mean eastward propagation of at least 2 m s-1, which are considered to be MJO convective initiation events. These LPTs capture the diversity of the MJO convection, which is not well depicted by the Real-time Multivariate MJO (RMM) index or the outgoing longwave radiation MJO index. During the 17 years, there were 17 instances out of 45 with a MJO signature in the RMM without eastward propagating LPTs. Among the 42 eastward propagating LPTs, 24 propagated across the Maritime Continent (MC), which confirms the MC barrier effect. Among the cases that crossed the MC from the Indian Ocean to the western Pacific (MC crossing), 18 (75%) had a significant MJO signature in the RMM index. In contrast, only six (33%) of the non-MC-crossing cases occurred with a RMM MJO signal. There is a significant seasonal and interannual variability with MC-crossing LPTs occurring in December more commonly than other months. More MC-crossing events were observed during La Niña than El Niño, which is consistent with the observations of stronger and more frequent MJO events identified by RMM during La Niña years.

The Signature of Southern Hemisphere Atmospheric Circulation Patterns in Antarctic Precipitation.

Science.gov (United States)

Marshall, Gareth J; Thompson, David W J; van den Broeke, Michiel R

2017-11-28

We provide the first comprehensive analysis of the relationships between large-scale patterns of Southern Hemisphere climate variability and the detailed structure of Antarctic precipitation. We examine linkages between the high spatial resolution precipitation from a regional atmospheric model and four patterns of large-scale Southern Hemisphere climate variability: the southern baroclinic annular mode, the southern annular mode, and the two Pacific-South American teleconnection patterns. Variations in all four patterns influence the spatial configuration of precipitation over Antarctica, consistent with their signatures in high-latitude meridional moisture fluxes. They impact not only the mean but also the incidence of extreme precipitation events. Current coupled-climate models are able to reproduce all four patterns of atmospheric variability but struggle to correctly replicate their regional impacts on Antarctic climate. Thus, linking these patterns directly to Antarctic precipitation variability may allow a better estimate of future changes in precipitation than using model output alone.

An operational weather radar-based Quantitative Precipitation Estimation and its application in catchment water resources modeling

DEFF Research Database (Denmark)

He, Xin; Vejen, Flemming; Stisen, Simon

2011-01-01

of precipitation compared with rain-gauge-based methods, thus providing the basis for better water resources assessments. The radar QPE algorithm called ARNE is a distance-dependent areal estimation method that merges radar data with ground surface observations. The method was applied to the Skjern River catchment...... in western Denmark where alternative precipitation estimates were also used as input to an integrated hydrologic model. The hydrologic responses from the model were analyzed by comparing radar- and ground-based precipitation input scenarios. Results showed that radar QPE products are able to generate...... reliable simulations of stream flow and water balance. The potential of using radar-based precipitation was found to be especially high at a smaller scale, where the impact of spatial resolution was evident from the stream discharge results. Also, groundwater recharge was shown to be sensitive...

Estimating Tropical Cyclone Precipitation from Station Observations

Institute of Scientific and Technical Information of China (English)

REN Fumin; WANG Yongmei; WANG Xiaoling; LI Weijing

2007-01-01

In this paper, an objective technique for estimating the tropical cyclone (TC) precipitation from station observations is proposed. Based on a comparison between the Original Objective Method (OOM) and the Expert Subjective Method (ESM), the Objective Synoptic Analysis Technique (OSAT) for partitioning TC precipitation was developed by analyzing the western North Pacific (WNP) TC historical track and the daily precipitation datasets. Being an objective way of the ESM, OSAT overcomes the main problems in OOM,by changing two fixed parameters in OOM, the thresholds for the distance of the absolute TC precipitation (D0) and the TC size (D1), into variable parameters.Case verification for OSAT was also carried out by applying CMORPH (Climate Prediction Center MORPHing technique) daily precipitation measurements, which is NOAA's combined satellite precipitation measurement system. This indicates that OSAT is capable of distinguishing simultaneous TC precipitation rain-belts from those associated with different TCs or with middle-latitude weather systems.

Large Scale Water Vapor Sources Relative to the October 2000 Piedmont Flood

Science.gov (United States)

Turato, Barbara; Reale, Oreste; Siccardi, Franco

2003-01-01

Very intense mesoscale or synoptic-scale rainfall events can occasionally be observed in the Mediterranean region without any deep cyclone developing over the areas affected by precipitation. In these perplexing cases the synoptic situation can superficially look similar to cases in which very little precipitation occurs. These situations could possibly baffle the operational weather forecasters. In this article, the major precipitation event that affected Piedmont (Italy) between 13 and 16 October 2000 is investigated. This is one of the cases in which no intense cyclone was observed within the Mediterranean region at any time, only a moderate system was present, and yet exceptional rainfall and flooding occurred. The emphasis of this study is on the moisture origin and transport. Moisture and energy balances are computed on different space- and time-scales, revealing that precipitation exceeds evaporation over an area inclusive of Piedmont and the northwestern Mediterranean region, on a time-scale encompassing the event and about two weeks preceding it. This is suggestive of an important moisture contribution originating from outside the region. A synoptic and dynamic analysis is then performed to outline the potential mechanisms that could have contributed to the large-scale moisture transport. The central part of the work uses a quasi-isentropic water-vapor back trajectory technique. The moisture sources obtained by this technique are compared with the results of the balances and with the synoptic situation, to unveil possible dynamic mechanisms and physical processes involved. It is found that moisture sources on a variety of atmospheric scales contribute to this event. First, an important contribution is caused by the extratropical remnants of former tropical storm Leslie. The large-scale environment related to this system allows a significant amount of moisture to be carried towards Europe. This happens on a time- scale of about 5-15 days preceding the

Interpolation of Missing Precipitation Data Using Kernel Estimations for Hydrologic Modeling

Directory of Open Access Journals (Sweden)

Hyojin Lee

2015-01-01

Full Text Available Precipitation is the main factor that drives hydrologic modeling; therefore, missing precipitation data can cause malfunctions in hydrologic modeling. Although interpolation of missing precipitation data is recognized as an important research topic, only a few methods follow a regression approach. In this study, daily precipitation data were interpolated using five different kernel functions, namely, Epanechnikov, Quartic, Triweight, Tricube, and Cosine, to estimate missing precipitation data. This study also presents an assessment that compares estimation of missing precipitation data through Kth nearest neighborhood (KNN regression to the five different kernel estimations and their performance in simulating streamflow using the Soil Water Assessment Tool (SWAT hydrologic model. The results show that the kernel approaches provide higher quality interpolation of precipitation data compared with the KNN regression approach, in terms of both statistical data assessment and hydrologic modeling performance.

Assessment of Evolving TRMM-Based Real-Time Precipitation Estimation Methods and Their Impacts on Hydrologic Prediction in a High-Latitude Basin

Science.gov (United States)

Yong, Bin; Hong, Yang; Ren, Li-Liang; Gourley, Jonathan; Huffman, George J.; Chen, Xi; Wang, Wen; Khan, Sadiq I.

2013-01-01

The real-time availability of satellite-derived precipitation estimates provides hydrologists an opportunity to improve current hydrologic prediction capability for medium to large river basins. Due to the availability of new satellite data and upgrades to the precipitation algorithms, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time estimates (TMPA-RT) have been undergoing several important revisions over the past ten years. In this study, the changes of the relative accuracy and hydrologic potential of TMPA-RT estimates over its three major evolving periods were evaluated and inter-compared at daily, monthly and seasonal scales in the high-latitude Laohahe basin in China. Assessment results show that the performance of TMPA-RT in terms of precipitation estimation and streamflow simulation was significantly improved after 3 February 2005. Overestimation during winter months was noteworthy and consistent, which is suggested to be a consequence from interference of snow cover to the passive microwave retrievals. Rainfall estimated by the new version 6 of TMPA-RT starting from 1 October 2008 to present has higher correlations with independent gauge observations and tends to perform better in detecting rain compared to the prior periods, although it suffers larger mean error and relative bias. After a simple bias correction, this latest dataset of TMPA-RT exhibited the best capability in capturing hydrologic response among the three tested periods. In summary, this study demonstrated that there is an increasing potential in the use of TMPA-RT in hydrologic streamflow simulations over its three algorithm upgrade periods, but still with significant challenges during the winter snowing events.

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.

Assessing groundwater storage changes using remote sensing-based evapotranspiration and precipitation at a large semiarid basin scale

NARCIS (Netherlands)

Gokmen, M.; Vekerdy, Z.; Lubczynski, M.; Timmermans, J.; Batelaan, Okke; Verhoef, W.

2013-01-01

A method is presented that uses remote sensing (RS)-based evapotranspiration (ET) and precipitation estimates with improved accuracies under semiarid conditions to quantify a spatially distributed water balance, for analyzing groundwater storage changes due to supplementary water uses. The method is

Penalized Estimation in Large-Scale Generalized Linear Array Models

DEFF Research Database (Denmark)

Lund, Adam; Vincent, Martin; Hansen, Niels Richard

2017-01-01

Large-scale generalized linear array models (GLAMs) can be challenging to fit. Computation and storage of its tensor product design matrix can be impossible due to time and memory constraints, and previously considered design matrix free algorithms do not scale well with the dimension...

Errors and parameter estimation in precipitation-runoff modeling: 1. Theory

Science.gov (United States)

Troutman, Brent M.

1985-01-01

Errors in complex conceptual precipitation-runoff models may be analyzed by placing them into a statistical framework. This amounts to treating the errors as random variables and defining the probabilistic structure of the errors. By using such a framework, a large array of techniques, many of which have been presented in the statistical literature, becomes available to the modeler for quantifying and analyzing the various sources of error. A number of these techniques are reviewed in this paper, with special attention to the peculiarities of hydrologic models. Known methodologies for parameter estimation (calibration) are particularly applicable for obtaining physically meaningful estimates and for explaining how bias in runoff prediction caused by model error and input error may contribute to bias in parameter estimation.

Case Study: Commercialization of sweet sorghum juice clarification for large-scale syrup manufacture

Science.gov (United States)

The precipitation and burning of insoluble granules of starch from sweet sorghum juice on heating coils prevented the large scale manufacture of syrup at a new industrial plant in Missouri, USA. To remove insoluble starch granules, a series of small and large-scale experiments were conducted at the...

Large-scale fluid motion in the earth's outer core estimated from non-dipole magnetic field data

International Nuclear Information System (INIS)

Matsushima, Masaki; Honkura, Yoshimori

1989-01-01

Fluid motions in the Earth's outer core can be estimated from magnetic field data at the Earth's surface based on some assumptions. The basic standpoint here is that the non-dipole magnetic field is generated by the interaction between a strong toroidal magnetic field, created by differential rotation, and the convective motion in the outer core. Large-scale convective motions are studied to express them in terms of the poloidal velocity field expanded into a series of spherical harmonics. The radial distribution of differential rotation is estimated from the balance between the effective couple due to angular momentum transfer and the electromagnetic couple. Then the radial dependence of the toroidal magnetic field is derived from the interaction between the differential rotation thus estimated and the dipole magnetic field within the outer core. Magnetic field data are applied to a secular variation model which takes into account the fluctuations of the standing and drifting parts of the non-zonal magnetic field. The velocity field in the outer core is estimated for two cases. It is revealed that the pattern of convective motions is generally characterized by large-scale motions in the quasi-steady case. In the non-steady case, the magnitude of the velocity field is much larger, indicating a more dynamic feature. (N.K.)

Large-scale lysimeter site St. Arnold, Germany: analysis of 40 years of precipitation, leachate and evapotranspiration

Directory of Open Access Journals (Sweden)

N. Harsch

2009-03-01

Full Text Available This study deals with a lysimetrical-meteorological data series collected on the large-scale lysimeter site "St. Arnold", Germany, from November 1965 to April 2007. The particular relevance of this data rests both upon its perdurability and upon the fact that the site is comprised of a grassland basin, an oak/beech and a pine basin.

Apart from analyzing long term trends of the meteorological measurements, the primary objective of this study is to investigate the water balance in grassland and forested basins, in particular comparing the precipitation term to leachate quantities and potential and actual evapotranspiration. The latter are based upon the Penman and the Penman-Monteith approaches, respectively.

The main results of this survey are that, on a long-term average, the grassland basin turns more than half (53% of its annually incoming precipitation into leachate and only 36% into water vapour, while the deciduous forest exhibits a ratio of 37% for leachate and 56% for evapotranspiration, and the evergreen coniferous forest shows the highest evaporation rate (65% and the lowest leachate rate (26%.

Concerning these water balances, considerable differences both between basins and between seasons stand out. While summer periods exhibit high evapotranspiration rates for the forests and moderate ones for the grassland, winter periods are characterised by considerable leachate quantities for grassland and the deciduous forest and moderate ones for the coniferous forest. Following the analysis of the climatic development in St. Arnold, trends towards a milder and more humid regional climate were detected.

Estimating GHG emission mitigation supply curves of large-scale biomass use on a country level

International Nuclear Information System (INIS)

Dornburg, Veronika; Dam, Jinke van; Faaij, Andre

2007-01-01

This study evaluates the possible influences of a large-scale introduction of biomass material and energy systems and their market volumes on land, material and energy market prices and their feedback to greenhouse gas (GHG) emission mitigation costs. GHG emission mitigation supply curves for large-scale biomass use were compiled using a methodology that combines a bottom-up analysis of biomass applications, biomass cost supply curves and market prices of land, biomaterials and bioenergy carriers. These market prices depend on the scale of biomass use and the market volume of materials and energy carriers and were estimated using own-price elasticities of demand. The methodology was demonstrated for a case study of Poland in the year 2015 applying different scenarios on economic development and trade in Europe. For the key technologies considered, i.e. medium density fibreboard, poly lactic acid, electricity and methanol production, GHG emission mitigation costs increase strongly with the scale of biomass production. Large-scale introduction of biomass use decreases the GHG emission reduction potential at costs below 50 Euro /Mg CO 2eq with about 13-70% depending on the scenario. Biomaterial production accounts for only a small part of this GHG emission reduction potential due to relatively small material markets and the subsequent strong decrease of biomaterial market prices at large scale of production. GHG emission mitigation costs depend strongly on biomass supply curves, own-price elasticity of land and market volumes of bioenergy carriers. The analysis shows that these influences should be taken into account for developing biomass implementations strategies

Using damage data to estimate the risk from summer convective precipitation extremes

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Schroeer, Katharina; Tye, Mari

2017-04-01

This study explores the potential added value from including loss and damage data to understand the risks from high-intensity short-duration convective precipitation events. Projected increases in these events are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows, and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to this, not only are extreme events rare, but such small-scale events are likely to be underreported where they do not coincide with the observation network. Reports of private loss and damage on a local administrative unit scale (LAU 2 level) are used to explore the relationship between observed rainfall events and damages reportedly related to hydro-meteorological processes. With 480 Austrian municipalities located within our south-eastern Alpine study region, the damage data are available on a much smaller scale than the available rainfall data. Precipitation is recorded daily at 185 gauges and 52% of these stations additionally deliver sub-hourly rainfall information. To obtain physically plausible information, damage and rainfall data are grouped and analyzed on a catchment scale. The data indicate that rainfall intensities are higher on days that coincide with a damage claim than on days for which no damage was reported. However, approximately one third of the damages related to hydro-meteorological hazards were claimed on days for which no rainfall was recorded at any gauge in the respective catchment. Our goal is to assess whether these events indicate potential extreme events missing in the observations. Damage always is a consequence of an asset being exposed and susceptible to a hazardous process, and naturally, many factors influence whether an extreme rainfall event causes damage. We set up a statistical

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

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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

Radar-derived quantitative precipitation estimation in complex terrain over the eastern Tibetan Plateau

Science.gov (United States)

Gou, Yabin; Ma, Yingzhao; Chen, Haonan; Wen, Yixin

2018-05-01

Quantitative precipitation estimation (QPE) is one of the important applications of weather radars. However, in complex terrain such as Tibetan Plateau, it is a challenging task to obtain an optimal Z-R relation due to the complex spatial and temporal variability in precipitation microphysics. This paper develops two radar QPE schemes respectively based on Reflectivity Threshold (RT) and Storm Cell Identification and Tracking (SCIT) algorithms using observations from 11 Doppler weather radars and 3264 rain gauges over the Eastern Tibetan Plateau (ETP). These two QPE methodologies are evaluated extensively using four precipitation events that are characterized by different meteorological features. Precipitation characteristics of independent storm cells associated with these four events, as well as the storm-scale differences, are investigated using short-term vertical profile of reflectivity (VPR) clusters. Evaluation results show that the SCIT-based rainfall approach performs better than the simple RT-based method for all precipitation events in terms of score comparison using validation gauge measurements as references. It is also found that the SCIT-based approach can effectively mitigate the local error of radar QPE and represent the precipitation spatiotemporal variability better than the RT-based scheme.

Quantifying streamflow change caused by forest disturbance at a large spatial scale: A single watershed study

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Wei, Xiaohua; Zhang, Mingfang

2010-12-01

Climatic variability and forest disturbance are commonly recognized as two major drivers influencing streamflow change in large-scale forested watersheds. The greatest challenge in evaluating quantitative hydrological effects of forest disturbance is the removal of climatic effect on hydrology. In this paper, a method was designed to quantify respective contributions of large-scale forest disturbance and climatic variability on streamflow using the Willow River watershed (2860 km2) located in the central part of British Columbia, Canada. Long-term (>50 years) data on hydrology, climate, and timber harvesting history represented by equivalent clear-cutting area (ECA) were available to discern climatic and forestry influences on streamflow by three steps. First, effective precipitation, an integrated climatic index, was generated by subtracting evapotranspiration from precipitation. Second, modified double mass curves were developed by plotting accumulated annual streamflow against annual effective precipitation, which presented a much clearer picture of the cumulative effects of forest disturbance on streamflow following removal of climatic influence. The average annual streamflow changes that were attributed to forest disturbances and climatic variability were then estimated to be +58.7 and -72.4 mm, respectively. The positive (increasing) and negative (decreasing) values in streamflow change indicated opposite change directions, which suggest an offsetting effect between forest disturbance and climatic variability in the study watershed. Finally, a multivariate Autoregressive Integrated Moving Average (ARIMA) model was generated to establish quantitative relationships between accumulated annual streamflow deviation attributed to forest disturbances and annual ECA. The model was then used to project streamflow change under various timber harvesting scenarios. The methodology can be effectively applied to any large-scale single watershed where long-term data (>50

Development of Deep Learning Based Data Fusion Approach for Accurate Rainfall Estimation Using Ground Radar and Satellite Precipitation Products

Science.gov (United States)

Chen, H.; Chandra, C. V.; Tan, H.; Cifelli, R.; Xie, P.

2016-12-01

Rainfall estimation based on onboard satellite measurements has been an important topic in satellite meteorology for decades. A number of precipitation products at multiple time and space scales have been developed based upon satellite observations. For example, NOAA Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space based rainfall estimates. The CMORPH products are essentially derived based on geostationary satellite IR brightness temperature information and retrievals from passive microwave measurements (Joyce et al. 2004). Although the space-based precipitation products provide an excellent tool for regional and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, its accuracy is limited due to the sampling limitations, particularly for extreme events such as very light and/or heavy rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization technique and further enhanced by urban scale radar networks. Therefore, ground radars are often critical for providing local scale rainfall estimation and a "heads-up" for operational forecasters to issue watches and warnings as well as validation of various space measurements and products. The CASA DFW QPE system, which is based on dual-polarization X-band CASA radars and a local S-band WSR-88DP radar, has demonstrated its excellent performance during several years of operation in a variety of precipitation regimes. The real-time CASA DFW QPE products are used extensively for localized hydrometeorological applications such as urban flash flood forecasting. In this paper, a neural network based data fusion mechanism is introduced to improve the satellite-based CMORPH precipitation product by taking into account the ground radar measurements. A deep learning system is

Augmenting Satellite Precipitation Estimation with Lightning Information

Energy Technology Data Exchange (ETDEWEB)

Mahrooghy, Majid [Mississippi State University (MSU); Anantharaj, Valentine G [ORNL; Younan, Nicolas H. [Mississippi State University (MSU); Petersen, Walter A. [NASA Marshall Space Flight Center, Huntsville, AL; Hsu, Kuo-Lin [University of California, Irvine; Behrangi, Ali [Jet Propulsion Laboratory, Pasadena, CA; Aanstoos, James [Mississippi State University (MSU)

2013-01-01

We have used lightning information to augment the Precipitation Estimation from Remotely Sensed Imagery using an Artificial Neural Network - Cloud Classification System (PERSIANN-CCS). Co-located lightning data are used to segregate cloud patches, segmented from GOES-12 infrared data, into either electrified (EL) or non-electrified (NEL) patches. A set of features is extracted separately for the EL and NEL cloud patches. The features for the EL cloud patches include new features based on the lightning information. The cloud patches are classified and clustered using self-organizing maps (SOM). Then brightness temperature and rain rate (T-R) relationships are derived for the different clusters. Rain rates are estimated for the cloud patches based on their representative T-R relationship. The Equitable Threat Score (ETS) for daily precipitation estimates is improved by almost 12% for the winter season. In the summer, no significant improvements in ETS are noted.

Changes and Attribution of Extreme Precipitation in Climate Models: Subdaily and Daily Scales

Science.gov (United States)

Zhang, W.; Villarini, G.; Scoccimarro, E.; Vecchi, G. A.

2017-12-01

Extreme precipitation events are responsible for numerous hazards, including flooding, soil erosion, and landslides. Because of their significant socio-economic impacts, the attribution and projection of these events is of crucial importance to improve our response, mitigation and adaptation strategies. Here we present results from our ongoing work.In terms of attribution, we use idealized experiments [pre-industrial control experiment (PI) and 1% per year increase (1%CO2) in atmospheric CO2] from ten general circulation models produced under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and the fraction of attributable risk to examine the CO2 effects on extreme precipitation at the sub-daily and daily scales. We find that the increased CO2 concentration substantially increases the odds of the occurrence of sub-daily precipitation extremes compared to the daily scale in most areas of the world, with the exception of some regions in the sub-tropics, likely in relation to the subsidence of the Hadley Cell. These results point to the large role that atmospheric CO2 plays in extreme precipitation under an idealized framework. Furthermore, we investigate the changes in extreme precipitation events with the Community Earth System Model (CESM) climate experiments using the scenarios consistent with the 1.5°C and 2°C temperature targets. We find that the frequency of annual extreme precipitation at a global scale increases in both 1.5°C and 2°C scenarios until around 2070, after which the magnitudes of the trend become much weaker or even negative. Overall, the frequency of global annual extreme precipitation is similar between 1.5°C and 2°C for the period 2006-2035, and the changes in extreme precipitation in individual seasons are consistent with those for the entire year. The frequency of extreme precipitation in the 2°C experiments is higher than for the 1.5°C experiment after the late 2030s, particularly for the period 2071-2100.

Enhancement of regional wet deposition estimates based on modeled precipitation inputs

Science.gov (United States)

James A. Lynch; Jeffery W. Grimm; Edward S. Corbett

1996-01-01

Application of a variety of two-dimensional interpolation algorithms to precipitation chemistry data gathered at scattered monitoring sites for the purpose of estimating precipitation- born ionic inputs for specific points or regions have failed to produce accurate estimates. The accuracy of these estimates is particularly poor in areas of high topographic relief....

Assessment of satellite-based precipitation estimates over Paraguay

Science.gov (United States)

Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

2018-04-01

Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

Atmospheric water vapor transport: Estimation of continental precipitation recycling and parameterization of a simple climate model. M.S. Thesis

Science.gov (United States)

Brubaker, Kaye L.; Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

The advective transport of atmospheric water vapor and its role in global hydrology and the water balance of continental regions are discussed and explored. The data set consists of ten years of global wind and humidity observations interpolated onto a regular grid by objective analysis. Atmospheric water vapor fluxes across the boundaries of selected continental regions are displayed graphically. The water vapor flux data are used to investigate the sources of continental precipitation. The total amount of water that precipitates on large continental regions is supplied by two mechanisms: (1) advection from surrounding areas external to the region; and (2) evaporation and transpiration from the land surface recycling of precipitation over the continental area. The degree to which regional precipitation is supplied by recycled moisture is a potentially significant climate feedback mechanism and land surface-atmosphere interaction, which may contribute to the persistence and intensification of droughts. A simplified model of the atmospheric moisture over continents and simultaneous estimates of regional precipitation are employed to estimate, for several large continental regions, the fraction of precipitation that is locally derived. In a separate, but related, study estimates of ocean to land water vapor transport are used to parameterize an existing simple climate model, containing both land and ocean surfaces, that is intended to mimic the dynamics of continental climates.

Recent Progress on the Second Generation CMORPH: LEO-IR Based Precipitation Estimates and Cloud Motion Vector

Science.gov (United States)

Xie, Pingping; Joyce, Robert; Wu, Shaorong

2015-04-01

As reported at the EGU General Assembly of 2014, a prototype system was developed for the second generation CMORPH to produce global analyses of 30-min precipitation on a 0.05olat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. Key to the success of the 2nd generation CMORPH, among a couple of other elements, are the development of a LEO-IR based precipitation estimation to fill in the polar gaps and objectively analyzed cloud motion vectors to capture the cloud movements of various spatial scales over the entire globe. In this presentation, we report our recent work on the refinement for these two important algorithm components. The prototype algorithm for the LEO IR precipitation estimation is refined to achieve improved quantitative accuracy and consistency with PMW retrievals. AVHRR IR TBB data from all LEO satellites are first remapped to a 0.05olat/lon grid over the entire globe and in a 30-min interval. Temporally and spatially co-located data pairs of the LEO TBB and inter-calibrated combined satellite PMW retrievals (MWCOMB) are then collected to construct tables. Precipitation at a grid box is derived from the TBB through matching the PDF tables for the TBB and the MWCOMB. This procedure is implemented for different season, latitude band and underlying surface types to account for the variations in the cloud - precipitation relationship. At the meantime, a sub-system is developed to construct analyzed fields of

Two methods for estimating limits to large-scale wind power generation.

Science.gov (United States)

Miller, Lee M; Brunsell, Nathaniel A; Mechem, David B; Gans, Fabian; Monaghan, Andrew J; Vautard, Robert; Keith, David W; Kleidon, Axel

2015-09-08

Wind turbines remove kinetic energy from the atmospheric flow, which reduces wind speeds and limits generation rates of large wind farms. These interactions can be approximated using a vertical kinetic energy (VKE) flux method, which predicts that the maximum power generation potential is 26% of the instantaneous downward transport of kinetic energy using the preturbine climatology. We compare the energy flux method to the Weather Research and Forecasting (WRF) regional atmospheric model equipped with a wind turbine parameterization over a 10(5) km2 region in the central United States. The WRF simulations yield a maximum generation of 1.1 We⋅m(-2), whereas the VKE method predicts the time series while underestimating the maximum generation rate by about 50%. Because VKE derives the generation limit from the preturbine climatology, potential changes in the vertical kinetic energy flux from the free atmosphere are not considered. Such changes are important at night when WRF estimates are about twice the VKE value because wind turbines interact with the decoupled nocturnal low-level jet in this region. Daytime estimates agree better to 20% because the wind turbines induce comparatively small changes to the downward kinetic energy flux. This combination of downward transport limits and wind speed reductions explains why large-scale wind power generation in windy regions is limited to about 1 We⋅m(-2), with VKE capturing this combination in a comparatively simple way.

Large-scale fluctuations in the diffusive decomposition of solid solutions

International Nuclear Information System (INIS)

Karpov, V.G.; Grimsditch, M.

1995-01-01

The concept of an instability in the classic Ostwald ripening theory with respect to compositional fluctuations is suggested. We show that small statistical fluctuations in the precipitate phase lead to gigantic Coulomb-like fluctuations in the solute concentration which in turn affect the ripening. As a result large-scale fluctuations in both the precipitate and solute concentrations appear. These fluctuations are characterized by amplitudes of the order of the average values of the corresponding quantities and by a space scale L∼(na) -1/2 which is considerably greater than both the average nuclear radius and internuclear distance. The Lifshitz-Slyozov theory of ripening is shown to remain locally applicable, over length scales much less than L. The implications of these findings for elastic light scattering in solid solutions that have undergone Ostwald ripening are considered

Large-scale fluctuations in the diffusive decomposition of solid solutions

Science.gov (United States)

Karpov, V. G.; Grimsditch, M.

1995-04-01

The concept of an instability in the classic Ostwald ripening theory with respect to compositional fluctuations is suggested. We show that small statistical fluctuations in the precipitate phase lead to gigantic Coulomb-like fluctuations in the solute concentration which in turn affect the ripening. As a result large-scale fluctuations in both the precipitate and solute concentrations appear. These fluctuations are characterized by amplitudes of the order of the average values of the corresponding quantities and by a space scale L~(na)-1/2 which is considerably greater than both the average nuclear radius and internuclear distance. The Lifshitz-Slyozov theory of ripening is shown to remain locally applicable, over length scales much less than L. The implications of these findings for elastic light scattering in solid solutions that have undergone Ostwald ripening are considered.

Meteorological impact assessment of possible large scale irrigation in Southwest Saudi Arabia

NARCIS (Netherlands)

Maat, ter H.W.; Hutjes, R.W.A.; Ohba, R.; Ueda, H.; Bisselink, B.; Bauer, T.

2006-01-01

On continental to regional scales feedbacks between landuse and landcover change and climate have been widely documented over the past 10¿15 years. In the present study we explore the possibility that also vegetation changes over much smaller areas may affect local precipitation regimes. Large scale

Large scale debris-flow hazard assessment: a geotechnical approach and GIS modelling

Directory of Open Access Journals (Sweden)

G. Delmonaco

2003-01-01

Full Text Available A deterministic distributed model has been developed for large-scale debris-flow hazard analysis in the basin of River Vezza (Tuscany Region – Italy. This area (51.6 km 2 was affected by over 250 landslides. These were classified as debris/earth flow mainly involving the metamorphic geological formations outcropping in the area, triggered by the pluviometric event of 19 June 1996. In the last decades landslide hazard and risk analysis have been favoured by the development of GIS techniques permitting the generalisation, synthesis and modelling of stability conditions on a large scale investigation (>1:10 000. In this work, the main results derived by the application of a geotechnical model coupled with a hydrological model for the assessment of debris flows hazard analysis, are reported. This analysis has been developed starting by the following steps: landslide inventory map derived by aerial photo interpretation, direct field survey, generation of a database and digital maps, elaboration of a DTM and derived themes (i.e. slope angle map, definition of a superficial soil thickness map, geotechnical soil characterisation through implementation of a backanalysis on test slopes, laboratory test analysis, inference of the influence of precipitation, for distinct return times, on ponding time and pore pressure generation, implementation of a slope stability model (infinite slope model and generalisation of the safety factor for estimated rainfall events with different return times. Such an approach has allowed the identification of potential source areas of debris flow triggering. This is used to detected precipitation events with estimated return time of 10, 50, 75 and 100 years. The model shows a dramatic decrease of safety conditions for the simulation when is related to a 75 years return time rainfall event. It corresponds to an estimated cumulated daily intensity of 280–330 mm. This value can be considered the hydrological triggering

Spatio-temporal precipitation climatology over complex terrain using a censored additive regression model.

Science.gov (United States)

Stauffer, Reto; Mayr, Georg J; Messner, Jakob W; Umlauf, Nikolaus; Zeileis, Achim

2017-06-15

Flexible spatio-temporal models are widely used to create reliable and accurate estimates for precipitation climatologies. Most models are based on square root transformed monthly or annual means, where a normal distribution seems to be appropriate. This assumption becomes invalid on a daily time scale as the observations involve large fractions of zero observations and are limited to non-negative values. We develop a novel spatio-temporal model to estimate the full climatological distribution of precipitation on a daily time scale over complex terrain using a left-censored normal distribution. The results demonstrate that the new method is able to account for the non-normal distribution and the large fraction of zero observations. The new climatology provides the full climatological distribution on a very high spatial and temporal resolution, and is competitive with, or even outperforms existing methods, even for arbitrary locations.

Evaluating the MSG satellite Multi-Sensor Precipitation Estimate for extreme rainfall monitoring over northern Tunisia

Directory of Open Access Journals (Sweden)

Saoussen Dhib

2017-06-01

Full Text Available Knowledge and evaluation of extreme precipitation is important for water resources and flood risk management, soil and land degradation, and other environmental issues. Due to the high potential threat to local infrastructure, such as buildings, roads and power supplies, heavy precipitation can have an important social and economic impact on society. At present, satellite derived precipitation estimates are becoming more readily available. This paper aims to investigate the potential use of the Meteosat Second Generation (MSG Multi-Sensor Precipitation Estimate (MPE for extreme rainfall assessment in Tunisia. The MSGMPE data combine microwave rain rate estimations with SEVIRI thermal infrared channel data, using an EUMETSAT production chain in near real time mode. The MPE data can therefore be used in a now-casting mode, and are potentially useful for extreme weather early warning and monitoring. Daily precipitation observed across an in situ gauge network in the north of Tunisia were used during the period 2007–2009 for validation of the MPE extreme event data. As a first test of the MSGMPE product's performance, very light to moderate rainfall classes, occurring between January and October 2007, were evaluated. Extreme rainfall events were then selected, using a threshold criterion for large rainfall depth (>50 mm/day occurring at least at one ground station. Spatial interpolation methods were applied to generate rainfall maps for the drier summer season (from May to October and the wet winter season (from November to April. Interpolated gauge rainfall maps were then compared to MSGMPE data available from the EUMETSAT UMARF archive or from the GEONETCast direct dissemination system. The summation of the MPE data at 5 and/or 15 min time intervals over a 24 h period, provided a basis for comparison. The MSGMPE product was not very effective in the detection of very light and light rain events. Better results were obtained for the slightly

Estimating mountain basin-mean precipitation from streamflow using Bayesian inference

Science.gov (United States)

Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Lundquist, Jessica D.

2015-10-01

Estimating basin-mean precipitation in complex terrain is difficult due to uncertainty in the topographical representativeness of precipitation gauges relative to the basin. To address this issue, we use Bayesian methodology coupled with a multimodel framework to infer basin-mean precipitation from streamflow observations, and we apply this approach to snow-dominated basins in the Sierra Nevada of California. Using streamflow observations, forcing data from lower-elevation stations, the Bayesian Total Error Analysis (BATEA) methodology and the Framework for Understanding Structural Errors (FUSE), we infer basin-mean precipitation, and compare it to basin-mean precipitation estimated using topographically informed interpolation from gauges (PRISM, the Parameter-elevation Regression on Independent Slopes Model). The BATEA-inferred spatial patterns of precipitation show agreement with PRISM in terms of the rank of basins from wet to dry but differ in absolute values. In some of the basins, these differences may reflect biases in PRISM, because some implied PRISM runoff ratios may be inconsistent with the regional climate. We also infer annual time series of basin precipitation using a two-step calibration approach. Assessment of the precision and robustness of the BATEA approach suggests that uncertainty in the BATEA-inferred precipitation is primarily related to uncertainties in hydrologic model structure. Despite these limitations, time series of inferred annual precipitation under different model and parameter assumptions are strongly correlated with one another, suggesting that this approach is capable of resolving year-to-year variability in basin-mean precipitation.

Scaling and clustering effects of extreme precipitation distributions

Science.gov (United States)

Zhang, Qiang; Zhou, Yu; Singh, Vijay P.; Li, Jianfeng

2012-08-01

SummaryOne of the impacts of climate change and human activities on the hydrological cycle is the change in the precipitation structure. Closely related to the precipitation structure are two characteristics: the volume (m) of wet periods (WPs) and the time interval between WPs or waiting time (t). Using daily precipitation data for a period of 1960-2005 from 590 rain gauge stations in China, these two characteristics are analyzed, involving scaling and clustering of precipitation episodes. Our findings indicate that m and t follow similar probability distribution curves, implying that precipitation processes are controlled by similar underlying thermo-dynamics. Analysis of conditional probability distributions shows a significant dependence of m and t on their previous values of similar volumes, and the dependence tends to be stronger when m is larger or t is longer. It indicates that a higher probability can be expected when high-intensity precipitation is followed by precipitation episodes with similar precipitation intensity and longer waiting time between WPs is followed by the waiting time of similar duration. This result indicates the clustering of extreme precipitation episodes and severe droughts or floods are apt to occur in groups.

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).

Application of physical scaling towards downscaling climate model precipitation data

Science.gov (United States)

Gaur, Abhishek; Simonovic, Slobodan P.

2018-04-01

Physical scaling (SP) method downscales climate model data to local or regional scales taking into consideration physical characteristics of the area under analysis. In this study, multiple SP method based models are tested for their effectiveness towards downscaling North American regional reanalysis (NARR) daily precipitation data. Model performance is compared with two state-of-the-art downscaling methods: statistical downscaling model (SDSM) and generalized linear modeling (GLM). The downscaled precipitation is evaluated with reference to recorded precipitation at 57 gauging stations located within the study region. The spatial and temporal robustness of the downscaling methods is evaluated using seven precipitation based indices. Results indicate that SP method-based models perform best in downscaling precipitation followed by GLM, followed by the SDSM model. Best performing models are thereafter used to downscale future precipitations made by three global circulation models (GCMs) following two emission scenarios: representative concentration pathway (RCP) 2.6 and RCP 8.5 over the twenty-first century. The downscaled future precipitation projections indicate an increase in mean and maximum precipitation intensity as well as a decrease in the total number of dry days. Further an increase in the frequency of short (1-day), moderately long (2-4 day), and long (more than 5-day) precipitation events is projected.

Large-scale Validation of AMIP II Land-surface Simulations: Preliminary Results for Ten Models

Energy Technology Data Exchange (ETDEWEB)

Phillips, T J; Henderson-Sellers, A; Irannejad, P; McGuffie, K; Zhang, H

2005-12-01

This report summarizes initial findings of a large-scale validation of the land-surface simulations of ten atmospheric general circulation models that are entries in phase II of the Atmospheric Model Intercomparison Project (AMIP II). This validation is conducted by AMIP Diagnostic Subproject 12 on Land-surface Processes and Parameterizations, which is focusing on putative relationships between the continental climate simulations and the associated models' land-surface schemes. The selected models typify the diversity of representations of land-surface climate that are currently implemented by the global modeling community. The current dearth of global-scale terrestrial observations makes exacting validation of AMIP II continental simulations impractical. Thus, selected land-surface processes of the models are compared with several alternative validation data sets, which include merged in-situ/satellite products, climate reanalyses, and off-line simulations of land-surface schemes that are driven by observed forcings. The aggregated spatio-temporal differences between each simulated process and a chosen reference data set then are quantified by means of root-mean-square error statistics; the differences among alternative validation data sets are similarly quantified as an estimate of the current observational uncertainty in the selected land-surface process. Examples of these metrics are displayed for land-surface air temperature, precipitation, and the latent and sensible heat fluxes. It is found that the simulations of surface air temperature, when aggregated over all land and seasons, agree most closely with the chosen reference data, while the simulations of precipitation agree least. In the latter case, there also is considerable inter-model scatter in the error statistics, with the reanalyses estimates of precipitation resembling the AMIP II simulations more than to the chosen reference data. In aggregate, the simulations of land-surface latent and

GLUE Based Uncertainty Estimation of Urban Drainage Modeling Using Weather Radar Precipitation Estimates

DEFF Research Database (Denmark)

Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

2011-01-01

Distributed weather radar precipitation measurements are used as rainfall input for an urban drainage model, to simulate the runoff from a small catchment of Denmark. It is demonstrated how the Generalized Likelihood Uncertainty Estimation (GLUE) methodology can be implemented and used to estimate...

Fundamental chemistry of precipitation and mineral scale formation

Science.gov (United States)

Alan W. Rudie; Peter W. Hart

2005-01-01

The mineral scale that deposits in digesters and bleach plants is formed by a chemical precipitation process. As such, it is accurately described or modeled using the solubility product equilibrium constant. Although solubility product identifies the primary conditions that need to be met for a scale problem to exist, the acid base equilibria of the scaling anions...

Simultaneous imaging of aurora on small scale in OI (777.4 nm and N21P to estimate energy and flux of precipitation

Directory of Open Access Journals (Sweden)

N. Ivchenko

2009-07-01

Full Text Available Simultaneous images of the aurora in three emissions, N21P (673.0 nm, OII (732.0 nm and OI (777.4 nm, have been analysed; the ratio of atomic oxygen to molecular nitrogen has been used to provide estimates of the changes in energy and flux of precipitation within scale sizes of 100 m, and with temporal resolution of 32 frames per second. The choice of filters for the imagers is discussed, with particular emphasis on the choice of the atomic oxygen line at 777.4 nm as one of the three emissions measured. The optical measurements have been combined with radar measurements and compared with the results of an auroral model, hence showing that the ratio of emission rates OI/N2 can be used to estimate the energy within the smallest auroral structures. In the event chosen, measurements were made from mainland Norway, near Tromso, (69.6 N, 19.2 E. The peak energies of precipitation were between 1–15 keV. In a narrow curling arc, it was found that the arc filaments resulted from energies in excess of 10 keV and fluxes of approximately 7 mW/m2. These filaments of the order of 100 m in width were embedded in a region of lower energies (about 5–10 keV and fluxes of about 3 mW/m2. The modelling results show that the method promises to be most powerful for detecting low energy precipitation, more prevalent at the higher latitudes of Svalbard where the multispectral imager, known as ASK, is now installed.

Simultaneous imaging of aurora on small scale in OI (777.4 nm and N21P to estimate energy and flux of precipitation

Directory of Open Access Journals (Sweden)

B. S. Lanchester

2009-07-01

Full Text Available Simultaneous images of the aurora in three emissions, N21P (673.0 nm, OII (732.0 nm and OI (777.4 nm, have been analysed; the ratio of atomic oxygen to molecular nitrogen has been used to provide estimates of the changes in energy and flux of precipitation within scale sizes of 100 m, and with temporal resolution of 32 frames per second. The choice of filters for the imagers is discussed, with particular emphasis on the choice of the atomic oxygen line at 777.4 nm as one of the three emissions measured. The optical measurements have been combined with radar measurements and compared with the results of an auroral model, hence showing that the ratio of emission rates OI/N2 can be used to estimate the energy within the smallest auroral structures. In the event chosen, measurements were made from mainland Norway, near Troms\\o, (69.6 N, 19.2 E. The peak energies of precipitation were between 1–15 keV. In a narrow curling arc, it was found that the arc filaments resulted from energies in excess of 10 keV and fluxes of approximately 7 mW/m2. These filaments of the order of 100 m in width were embedded in a region of lower energies (about 5–10 keV and fluxes of about 3 mW/m2. The modelling results show that the method promises to be most powerful for detecting low energy precipitation, more prevalent at the higher latitudes of Svalbard where the multispectral imager, known as ASK, is now installed.

Evaluating the Global Precipitation Measurement mission with NOAA/NSSL Multi-Radar Multisensor: current status and future directions.

Science.gov (United States)

Kirstetter, P. E.; Petersen, W. A.; Gourley, J. J.; Kummerow, C.; Huffman, G. J.; Turk, J.; Tanelli, S.; Maggioni, V.; Anagnostou, E. N.; Hong, Y.; Schwaller, M.

2017-12-01

Accurate characterization of uncertainties in space-borne precipitation estimates is critical for many applications including water budget studies or prediction of natural hazards at the global scale. The GPM precipitation Level II (active and passive) and Level III (IMERG) estimates are compared to the high quality and high resolution NEXRAD-based precipitation estimates derived from the NOAA/NSSL's Multi-Radar, Multi-Sensor (MRMS) platform. A surface reference is derived from the MRMS suite of products to be accurate with known uncertainty bounds and measured at a resolution below the pixel sizes of any GPM estimate, providing great flexibility in matching to grid scales or footprints. It provides an independent and consistent reference research framework for directly evaluating GPM precipitation products across a large number of meteorological regimes as a function of resolution, accuracy and sample size. The consistency of the ground and space-based sensors in term of precipitation detection, typology and quantification are systematically evaluated. Satellite precipitation retrievals are further investigated in terms of precipitation distributions, systematic biases and random errors, influence of precipitation sub-pixel variability and comparison between satellite products. Prognostic analysis directly provides feedback to algorithm developers on how to improve the satellite estimates. Specific factors for passive (e.g. surface conditions for GMI) and active (e.g. non uniform beam filling for DPR) sensors are investigated. This cross products characterization acts as a bridge to intercalibrate microwave measurements from the GPM constellation satellites and propagate to the combined and global precipitation estimates. Precipitation features previously used to analyze Level II satellite estimates under various precipitation processes are now intoduced for Level III to test several assumptions in the IMERG algorithm. Specifically, the contribution of Level II is

The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.

Science.gov (United States)

Pang, Haotian; Liu, Han; Vanderbei, Robert

2014-02-01

We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package efficiently implements the parametric simplex algorithm, which provides a scalable and sophisticated tool for solving large-scale linear programs. As an illustrative example, one use of our LP solver is to implement an important sparse precision matrix estimation method called CLIME (Constrained L 1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems.

Rain cell-based identification of the vertical profile of reflectivity as observed by weather radar and its use for precipitation uncertainty estimation

Science.gov (United States)

Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Uijlenhoet, R.

2012-04-01

The wide scale implementation of weather radar systems over the last couple of decades has increased our understanding concerning spatio-temporal precipitation dynamics. However, the quantitative estimation of precipitation by these devices is affected by many sources of error. A very dominant source of error results from vertical variations in the hydrometeor size distribution known as the vertical profile of reflectivity (VPR). Since the height of the measurement as well as the beam volume increases with distance from the radar, for stratiform precipitation this results in a serious underestimation (overestimation) of the surface reflectivity while sampling within the snow (bright band) region. This research presents a precipitation cell-based implementation to correct volumetric weather radar measurements for VPR effects. Using the properties of a flipping carpenter square, a contour-based identification technique was developed, which is able to identify and track precipitation cells in real time, distinguishing between convective, stratiform and undefined precipitation. For the latter two types of systems, for each individual cell, a physically plausible vertical profile of reflectivity is estimated using a Monte Carlo optimization method. Since it can be expected that the VPR will vary within a given precipitation cell, a method was developed to take the uncertainty of the VPR estimate into account. As a result, we are able to estimate the amount of precipitation uncertainty as observed by weather radar due to VPR for a given precipitation type and storm cell. We demonstrate the possibilities of this technique for a number of winter precipitation systems observed within the Belgian Ardennes. For these systems, in general, the precipitation uncertainty estimate due to vertical reflectivity profile variations varies between 10-40%.

National scale biomass estimators for United States tree species

Science.gov (United States)

Jennifer C. Jenkins; David C. Chojnacky; Linda S. Heath; Richard A. Birdsey

2003-01-01

Estimates of national-scale forest carbon (C) stocks and fluxes are typically based on allometric regression equations developed using dimensional analysis techniques. However, the literature is inconsistent and incomplete with respect to large-scale forest C estimation. We compiled all available diameter-based allometric regression equations for estimating total...

Development of fine-resolution analyses and expanded large-scale forcing properties: 2. Scale awareness and application to single-column model experiments

Science.gov (United States)

Feng, Sha; Li, Zhijin; Liu, Yangang; Lin, Wuyin; Zhang, Minghua; Toto, Tami; Vogelmann, Andrew M.; Endo, Satoshi

2015-01-01

three-dimensional fields have been produced using the Community Gridpoint Statistical Interpolation (GSI) data assimilation system for the U.S. Department of Energy's Atmospheric Radiation Measurement Program (ARM) Southern Great Plains region. The GSI system is implemented in a multiscale data assimilation framework using the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. From the fine-resolution three-dimensional fields, large-scale forcing is derived explicitly at grid-scale resolution; a subgrid-scale dynamic component is derived separately, representing subgrid-scale horizontal dynamic processes. Analyses show that the subgrid-scale dynamic component is often a major component over the large-scale forcing for grid scales larger than 200 km. The single-column model (SCM) of the Community Atmospheric Model version 5 is used to examine the impact of the grid-scale and subgrid-scale dynamic components on simulated precipitation and cloud fields associated with a mesoscale convective system. It is found that grid-scale size impacts simulated precipitation, resulting in an overestimation for grid scales of about 200 km but an underestimation for smaller grids. The subgrid-scale dynamic component has an appreciable impact on the simulations, suggesting that grid-scale and subgrid-scale dynamic components should be considered in the interpretation of SCM simulations.

Modelling and on-line estimation of zinc sulphide precipitation in

NARCIS (Netherlands)

Grootscholten, T.I.M.; Keesman, K.J.; Lens, P.N.L.

2008-01-01

In this paper the ZnS precipitation in a continuously stirred tank reactor (CSTR) is modelled using mass balances. The dynamics analysis of the model reveals that the ZnS precipitation shows a two time-scales behaviour with inherent numerical stability problems, which therefore needs special

Insights into mountain precipitation and snowpack from a basin-scale wireless-sensor network

Science.gov (United States)

Zhang, Z.; Glaser, S.; Bales, R.; Conklin, M.; Rice, R.; Marks, D.

2017-08-01

A spatially distributed wireless-sensor network, installed across the 2154 km2 portion of the 5311 km2 American River basin above 1500 m elevation, provided spatial measurements of temperature, relative humidity, and snow depth in the Sierra Nevada, California. The network consisted of 10 sensor clusters, each with 10 measurement nodes, distributed to capture the variability in topography and vegetation cover. The sensor network captured significant spatial heterogeneity in rain versus snow precipitation for water-year 2014, variability that was not apparent in the more limited operational data. Using daily dew-point temperature to track temporal elevational changes in the rain-snow transition, the amount of snow accumulation at each node was used to estimate the fraction of rain versus snow. This resulted in an underestimate of total precipitation below the 0°C dew-point elevation, which averaged 1730 m across 10 precipitation events, indicating that measuring snow does not capture total precipitation. We suggest blending lower elevation rain gauge data with higher-elevation sensor-node data for each event to estimate total precipitation. Blended estimates were on average 15-30% higher than using either set of measurements alone. Using data from the current operational snow-pillow sites gives even lower estimates of basin-wide precipitation. Given the increasing importance of liquid precipitation in a warming climate, a strategy that blends distributed measurements of both liquid and solid precipitation will provide more accurate basin-wide precipitation estimates, plus spatial and temporal patters of snow accumulation and melt in a basin.

Identification and uncertainty estimation of vertical reflectivity profiles using a Lagrangian approach to support quantitative precipitation measurements by weather radar

Science.gov (United States)

Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Delrieu, G.; Uijlenhoet, R.

2013-09-01

This paper presents a novel approach to estimate the vertical profile of reflectivity (VPR) from volumetric weather radar data using both a traditional Eulerian as well as a newly proposed Lagrangian implementation. For this latter implementation, the recently developed Rotational Carpenter Square Cluster Algorithm (RoCaSCA) is used to delineate precipitation regions at different reflectivity levels. A piecewise linear VPR is estimated for either stratiform or neither stratiform/convective precipitation. As a second aspect of this paper, a novel approach is presented which is able to account for the impact of VPR uncertainty on the estimated radar rainfall variability. Results show that implementation of the VPR identification and correction procedure has a positive impact on quantitative precipitation estimates from radar. Unfortunately, visibility problems severely limit the impact of the Lagrangian implementation beyond distances of 100 km. However, by combining this procedure with the global Eulerian VPR estimation procedure for a given rainfall type (stratiform and neither stratiform/convective), the quality of the quantitative precipitation estimates increases up to a distance of 150 km. Analyses of the impact of VPR uncertainty shows that this aspect accounts for a large fraction of the differences between weather radar rainfall estimates and rain gauge measurements.

The shared and unique values of optical, fluorescence, thermal and microwave satellite data for estimating large-scale crop yields

Science.gov (United States)

Large-scale crop monitoring and yield estimation are important for both scientific research and practical applications. Satellite remote sensing provides an effective means for regional and global cropland monitoring, particularly in data-sparse regions that lack reliable ground observations and rep...

Key drivers of precipitation isotopes in Windhoek, Namibia (2012-2016)

Science.gov (United States)

Kaseke, K. F.; Wang, L.; Wanke, H.

2017-12-01

Southern African climate is characterized by large variability with precipitation model estimates varying by as much as 70% during summer. This difference between model estimates is partly because most models associate precipitation over Southern Africa with moisture inputs from the Indian Ocean while excluding inputs from the Atlantic Ocean. However, growing evidence suggests that the Atlantic Ocean may also contribute significant amounts of moisture to the region. This four-year (2012-2016) study investigates the isotopic composition (δ18O, δ2H and δ17O) of event-scale precipitation events, the key drivers of isotope variations and the origins of precipitation experienced in Windhoek, Namibia. Results indicate large storm-to-storm isotopic variability δ18O (25‰), δ2H (180‰) and δ17O (13‰) over the study period. Univariate analysis showed significant correlations between event precipitation isotopes and local meteorological parameters; lifted condensation level, relative humidity (RH), precipitation amount, average wind speed, surface and air temperature (p < 0.05). The number of significant correlations between local meteorological parameters and monthly isotopes was much lower suggesting loss of information through data aggregation. Nonetheless, the most significant isotope driver at both event and monthly scales was RH, consistent with the semi-arid classification of the site. Multiple linear regression analysis suggested RH, precipitation amount and air temperature were the most significant local drivers of precipitation isotopes accounting for about 50% of the variation implying that about 50% could be attributed to source origins. HYSLPIT trajectories indicated that 78% of precipitation originated from the Indian Ocean while 21% originated from the Atlantic Ocean. Given that three of the four study years were droughts while two of the three drought years were El Niño related, our data also suggests that δ'17O-δ'18O could be a useful tool to

The impact of reflectivity correction and accounting for raindrop size distribution variability to improve precipitation estimation by weather radar for an extreme low-land mesoscale convective system

Science.gov (United States)

Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

2014-11-01

disdrometer information, the best results were obtained in case no differentiation between precipitation type (convective, stratiform and undefined) was made, increasing the event accumulations to more than 80% of those observed by gauges. For the randomly optimized procedure, radar precipitation estimates further improve and closely resemble observations in case one differentiates between precipitation type. However, the optimal parameter sets are very different from those derived from disdrometer observations. It is therefore questionable if single disdrometer observations are suitable for large-scale quantitative precipitation estimation, especially if the disdrometer is located relatively far away from the main rain event, which was the case in this study. In conclusion, this study shows the benefit of applying detailed error correction methods to improve the quality of the weather radar product, but also confirms the need to be cautious using locally obtained disdrometer measurements.

Precipitation-productivity Relation in Grassland in Northern China: Investigations at Multiple Spatiotemporal Scales

Science.gov (United States)

Hu, Z.

2017-12-01

Climate change is predicted to cause dramatic variability in precipitation regime, not only in terms of change in annual precipitation amount, but also in precipitation seasonal distribution and precipitation event characteristics (high frenquency extrem precipitation, larger but fewer precipitation events), which combined to influence productivity of grassland in arid and semiarid regions. In this study, combining remote sensing products with in-situ measurements of aboveground net primary productivity (ANPP) and gross primary productivity (GPP) data from eddy covariance system in grassland of northern China, we quantified the effects of spatio-temporal vairation in precipitation on productivity from local sites to region scale. We found that, for an individual precipitation event, the duration of GPP-response to the individual precipitation event and the maximum absolute GPP response induced by the individual precipitation event increased linearly with the size of precipitation events. Comparison of the productivity-precipitation relationships between multi-sites determined that the predominant characteristics of precipitation events (PEC) that affected GPP differed remarkably between the water-limited temperate steppe and the temperature-limited alpine meadow. The number of heavy precipitation events (>10 mm d-1) was the most important PEC to impact GPP in the temperate steppe through affecting soil moisture at different soil profiles, while precipitation interval was the factor that affected GPP most in the alpine meadow via its effects on temperature. At the region scale, shape of ANPP-precipitation relationship varies with distinct spatial scales, and besides annual precipitation, precipitation seasonal distribution also has comparable impacts on spatial variation in ANPP. Temporal variability in ANPP was lower at both the dry and wet end, and peaked at a precipitation of 243.1±3.5mm, which is the transition region between typical steppe and desert steppe

How the Internet Will Help Large-Scale Assessment Reinvent Itself

Directory of Open Access Journals (Sweden)

Randy Elliot Bennett

2001-02-01

Full Text Available Large-scale assessment in the United States is undergoing enormous pressure to change. That pressure stems from many causes. Depending upon the type of test, the issues precipitating change include an outmoded cognitive-scientific basis for test design; a mismatch with curriculum; the differential performance of population groups; a lack of information to help individuals improve; and inefficiency. These issues provide a strong motivation to reconceptualize both the substance and the business of large-scale assessment. At the same time, advances in technology, measurement, and cognitive science are providing the means to make that reconceptualization a reality. The thesis of this paper is that the largest facilitating factor will be technological, in particular the Internet. In the same way that it is already helping to revolutionize commerce, education, and even social interaction, the Internet will help revolutionize the business and substance of large-scale assessment.

Uncertainty Estimation using Bootstrapped Kriging Predictions for Precipitation Isoscapes

Science.gov (United States)

Ma, C.; Bowen, G. J.; Vander Zanden, H.; Wunder, M.

2017-12-01

Isoscapes are spatial models representing the distribution of stable isotope values across landscapes. Isoscapes of hydrogen and oxygen in precipitation are now widely used in a diversity of fields, including geology, biology, hydrology, and atmospheric science. To generate isoscapes, geostatistical methods are typically applied to extend predictions from limited data measurements. Kriging is a popular method in isoscape modeling, but quantifying the uncertainty associated with the resulting isoscapes is challenging. Applications that use precipitation isoscapes to determine sample origin require estimation of uncertainty. Here we present a simple bootstrap method (SBM) to estimate the mean and uncertainty of the krigged isoscape and compare these results with a generalized bootstrap method (GBM) applied in previous studies. We used hydrogen isotopic data from IsoMAP to explore these two approaches for estimating uncertainty. We conducted 10 simulations for each bootstrap method and found that SBM results in more kriging predictions (9/10) compared to GBM (4/10). Prediction from SBM was closer to the original prediction generated without bootstrapping and had less variance than GBM. SBM was tested on different datasets from IsoMAP with different numbers of observation sites. We determined that predictions from the datasets with fewer than 40 observation sites using SBM were more variable than the original prediction. The approaches we used for estimating uncertainty will be compiled in an R package that is under development. We expect that these robust estimates of precipitation isoscape uncertainty can be applied in diagnosing the origin of samples ranging from various type of waters to migratory animals, food products, and humans.

Rainfall estimation in SWAT: An alternative method to simulate orographic precipitation

Science.gov (United States)

Galván, L.; Olías, M.; Izquierdo, T.; Cerón, J. C.; Fernández de Villarán, R.

2014-02-01

The input of water from precipitation is one of the most important aspects of a hydrologic model because it controls the basin's water budget. The model should reproduce the amount and distribution of rainfall in the basin, spatially and temporally. SWAT (Soil and Water Assessment Tool) is one of the most widely used hydrologic models. In this paper the rainfall estimation in SWAT is revised, focusing on the treatment of orographic precipitation. SWAT was applied to the Odiel river basin (SW Spain), with a surface of 2300 km2. Results show that SWAT does not reflect reallisticaly the spatial distribution of rainfall in the basin. In relation to orographic precipitation, SWAT estimates the daily precipitation in elevation bands by adding a constant amount to the recorded precipitation in the rain gauge, which depends on the increase in precipitation with altitude and the difference between the mean elevation of each band and the elevation of the recording gauge. This does not reflect rainfall in the subbasin because the increase in precipitation with altitude actually it is not constant, but depends on the amount of rainfall. An alternative methodology to represent the temporal distribution of orographic precipitation is proposed. After simulation, the deviation of runoff volume using the SWAT elevation bands was appreciably higher than that obtained with the proposed methodology.

Large scale electrolysers

International Nuclear Information System (INIS)

B Bello; M Junker

2006-01-01

Hydrogen production by water electrolysis represents nearly 4 % of the world hydrogen production. Future development of hydrogen vehicles will require large quantities of hydrogen. Installation of large scale hydrogen production plants will be needed. In this context, development of low cost large scale electrolysers that could use 'clean power' seems necessary. ALPHEA HYDROGEN, an European network and center of expertise on hydrogen and fuel cells, has performed for its members a study in 2005 to evaluate the potential of large scale electrolysers to produce hydrogen in the future. The different electrolysis technologies were compared. Then, a state of art of the electrolysis modules currently available was made. A review of the large scale electrolysis plants that have been installed in the world was also realized. The main projects related to large scale electrolysis were also listed. Economy of large scale electrolysers has been discussed. The influence of energy prices on the hydrogen production cost by large scale electrolysis was evaluated. (authors)

Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network

Science.gov (United States)

Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron

2016-02-01

Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the

Analysis of precipitation data in Bangladesh through hierarchical clustering and multidimensional scaling

Science.gov (United States)

Rahman, Md. Habibur; Matin, M. A.; Salma, Umma

2017-12-01

The precipitation patterns of seventeen locations in Bangladesh from 1961 to 2014 were studied using a cluster analysis and metric multidimensional scaling. In doing so, the current research applies four major hierarchical clustering methods to precipitation in conjunction with different dissimilarity measures and metric multidimensional scaling. A variety of clustering algorithms were used to provide multiple clustering dendrograms for a mixture of distance measures. The dendrogram of pre-monsoon rainfall for the seventeen locations formed five clusters. The pre-monsoon precipitation data for the areas of Srimangal and Sylhet were located in two clusters across the combination of five dissimilarity measures and four hierarchical clustering algorithms. The single linkage algorithm with Euclidian and Manhattan distances, the average linkage algorithm with the Minkowski distance, and Ward's linkage algorithm provided similar results with regard to monsoon precipitation. The results of the post-monsoon and winter precipitation data are shown in different types of dendrograms with disparate combinations of sub-clusters. The schematic geometrical representations of the precipitation data using metric multidimensional scaling showed that the post-monsoon rainfall of Cox's Bazar was located far from those of the other locations. The results of a box-and-whisker plot, different clustering techniques, and metric multidimensional scaling indicated that the precipitation behaviour of Srimangal and Sylhet during the pre-monsoon season, Cox's Bazar and Sylhet during the monsoon season, Maijdi Court and Cox's Bazar during the post-monsoon season, and Cox's Bazar and Khulna during the winter differed from those at other locations in Bangladesh.

Large scale air pollution estimation method combining land use regression and chemical transport modeling in a geostatistical framework.

Science.gov (United States)

Akita, Yasuyuki; Baldasano, Jose M; Beelen, Rob; Cirach, Marta; de Hoogh, Kees; Hoek, Gerard; Nieuwenhuijsen, Mark; Serre, Marc L; de Nazelle, Audrey

2014-04-15

In recognition that intraurban exposure gradients may be as large as between-city variations, recent air pollution epidemiologic studies have become increasingly interested in capturing within-city exposure gradients. In addition, because of the rapidly accumulating health data, recent studies also need to handle large study populations distributed over large geographic domains. Even though several modeling approaches have been introduced, a consistent modeling framework capturing within-city exposure variability and applicable to large geographic domains is still missing. To address these needs, we proposed a modeling framework based on the Bayesian Maximum Entropy method that integrates monitoring data and outputs from existing air quality models based on Land Use Regression (LUR) and Chemical Transport Models (CTM). The framework was applied to estimate the yearly average NO2 concentrations over the region of Catalunya in Spain. By jointly accounting for the global scale variability in the concentration from the output of CTM and the intraurban scale variability through LUR model output, the proposed framework outperformed more conventional approaches.

Shifts in Summertime Precipitation Accumulation Distributions over the US

Science.gov (United States)

Martinez-Villalobos, C.; Neelin, J. D.

2017-12-01

Precipitation accumulations, i.e., the amount of precipitation integrated over the course of an event, is a variable with both important physical and societal implications. Previous observational studies show that accumulation distributions have a characteristic shape, with an approximately power law decrease at first, followed by a sharp decrease at a characteristic large event cutoff scale. This cutoff scale is important as it limits the biggest accumulation events. Stochastic prototypes show that the resulting distributions, and importantly the large event cutoff scale, can be understood as a result of the interplay between moisture loss by precipitation and changes in moisture sinks/sources due to fluctuations in moisture divergence over the course of a precipitation event. The strength of this fluctuating moisture sink/source term is expected to increase under global warming, with both theory and climate model simulations predicting a concomitant increase in the large event cutoff scale. This cutoff scale increase has important consequences as it implies an approximately exponential increase for the largest accumulation events. Given its importance, in this study we characterize and track changes in the distribution of precipitation events accumulations over the contiguous US. Accumulation distributions are calculated using hourly precipitation data from 1700 stations, covering the 1974-2013 period over May-October. The resulting distributions largely follow the aforementioned shape, with individual cutoff scales depending on the local climate. An increase in the large event cutoff scale over this period is observed over several regions over the US, most notably over the eastern third of the US. In agreement with the increase in the cutoff, almost exponential increases in the highest accumulation percentiles occur over these regions, with increases in the 99.9 percentile in the Northeast of 70% for example. The relationship to changes in daily precipitation

Precipitation Analysis at Fine Time Scales Using Multiple Satellites: Real-time and Research Products and Applications

Science.gov (United States)

Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold

2004-01-01

Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) in 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O"N-5O0S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

Estimating the Effectiveness of Special Education Using Large-Scale Assessment Data

Science.gov (United States)

Ewing, Katherine Anne

2009-01-01

The inclusion of students with disabilities in large scale assessment and accountability programs has provided new opportunities to examine the impact of special education services on student achievement. Hanushek, Kain, and Rivkin (1998, 2002) evaluated the effectiveness of special education programs by examining students' gains on a large-scale…

STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

Science.gov (United States)

Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

2014-05-01

We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present

Global monsoon precipitation responses to large volcanic eruptions.

Science.gov (United States)

Liu, Fei; Chai, Jing; Wang, Bin; Liu, Jian; Zhang, Xiao; Wang, Zhiyuan

2016-04-11

Climate variation of global monsoon (GM) precipitation involves both internal feedback and external forcing. Here, we focus on strong volcanic forcing since large eruptions are known to be a dominant mechanism in natural climate change. It is not known whether large volcanoes erupted at different latitudes have distinctive effects on the monsoon in the Northern Hemisphere (NH) and the Southern Hemisphere (SH). We address this issue using a 1500-year volcanic sensitivity simulation by the Community Earth System Model version 1.0 (CESM1). Volcanoes are classified into three types based on their meridional aerosol distributions: NH volcanoes, SH volcanoes and equatorial volcanoes. Using the model simulation, we discover that the GM precipitation in one hemisphere is enhanced significantly by the remote volcanic forcing occurring in the other hemisphere. This remote volcanic forcing-induced intensification is mainly through circulation change rather than moisture content change. In addition, the NH volcanic eruptions are more efficient in reducing the NH monsoon precipitation than the equatorial ones, and so do the SH eruptions in weakening the SH monsoon, because the equatorial eruptions, despite reducing moisture content, have weaker effects in weakening the off-equatorial monsoon circulation than the subtropical-extratropical volcanoes do.

RESTRUCTURING OF THE LARGE-SCALE SPRINKLERS

Directory of Open Access Journals (Sweden)

Paweł Kozaczyk

2016-09-01

Full Text Available One of the best ways for agriculture to become independent from shortages of precipitation is irrigation. In the seventies and eighties of the last century a number of large-scale sprinklers in Wielkopolska was built. At the end of 1970’s in the Poznan province 67 sprinklers with a total area of 6400 ha were installed. The average size of the sprinkler reached 95 ha. In 1989 there were 98 sprinklers, and the area which was armed with them was more than 10 130 ha. The study was conducted on 7 large sprinklers with the area ranging from 230 to 520 hectares in 1986÷1998. After the introduction of the market economy in the early 90’s and ownership changes in agriculture, large-scale sprinklers have gone under a significant or total devastation. Land on the State Farms of the State Agricultural Property Agency has leased or sold and the new owners used the existing sprinklers to a very small extent. This involved a change in crop structure, demand structure and an increase in operating costs. There has also been a threefold increase in electricity prices. Operation of large-scale irrigation encountered all kinds of barriers in practice and limitations of system solutions, supply difficulties, high levels of equipment failure which is not inclined to rational use of available sprinklers. An effect of a vision of the local area was to show the current status of the remaining irrigation infrastructure. The adopted scheme for the restructuring of Polish agriculture was not the best solution, causing massive destruction of assets previously invested in the sprinkler system.

Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

Science.gov (United States)

Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

2016-12-01

Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong

Local likelihood estimation of complex tail dependence structures in high dimensions, applied to US precipitation extremes

KAUST Repository

Camilo, Daniela Castro

2017-10-02

In order to model the complex non-stationary dependence structure of precipitation extremes over the entire contiguous U.S., we propose a flexible local approach based on factor copula models. Our sub-asymptotic spatial modeling framework yields non-trivial tail dependence structures, with a weakening dependence strength as events become more extreme, a feature commonly observed with precipitation data but not accounted for in classical asymptotic extreme-value models. To estimate the local extremal behavior, we fit the proposed model in small regional neighborhoods to high threshold exceedances, under the assumption of local stationarity. This allows us to gain in flexibility, while making inference for such a large and complex dataset feasible. Adopting a local censored likelihood approach, inference is made on a fine spatial grid, and local estimation is performed taking advantage of distributed computing resources and of the embarrassingly parallel nature of this estimation procedure. The local model is efficiently fitted at all grid points, and uncertainty is measured using a block bootstrap procedure. An extensive simulation study shows that our approach is able to adequately capture complex, non-stationary dependencies, while our study of U.S. winter precipitation data reveals interesting differences in local tail structures over space, which has important implications on regional risk assessment of extreme precipitation events. A comparison between past and current data suggests that extremes in certain areas might be slightly wider in extent nowadays than during the first half of the twentieth century.

Local likelihood estimation of complex tail dependence structures in high dimensions, applied to US precipitation extremes

KAUST Repository

Camilo, Daniela Castro; Huser, Raphaë l

2017-01-01

In order to model the complex non-stationary dependence structure of precipitation extremes over the entire contiguous U.S., we propose a flexible local approach based on factor copula models. Our sub-asymptotic spatial modeling framework yields non-trivial tail dependence structures, with a weakening dependence strength as events become more extreme, a feature commonly observed with precipitation data but not accounted for in classical asymptotic extreme-value models. To estimate the local extremal behavior, we fit the proposed model in small regional neighborhoods to high threshold exceedances, under the assumption of local stationarity. This allows us to gain in flexibility, while making inference for such a large and complex dataset feasible. Adopting a local censored likelihood approach, inference is made on a fine spatial grid, and local estimation is performed taking advantage of distributed computing resources and of the embarrassingly parallel nature of this estimation procedure. The local model is efficiently fitted at all grid points, and uncertainty is measured using a block bootstrap procedure. An extensive simulation study shows that our approach is able to adequately capture complex, non-stationary dependencies, while our study of U.S. winter precipitation data reveals interesting differences in local tail structures over space, which has important implications on regional risk assessment of extreme precipitation events. A comparison between past and current data suggests that extremes in certain areas might be slightly wider in extent nowadays than during the first half of the twentieth century.

SCALES: SEVIRI and GERB CaL/VaL area for large-scale field experiments

Science.gov (United States)

Lopez-Baeza, Ernesto; Belda, Fernando; Bodas, Alejandro; Crommelynck, Dominique; Dewitte, Steven; Domenech, Carlos; Gimeno, Jaume F.; Harries, John E.; Jorge Sanchez, Joan; Pineda, Nicolau; Pino, David; Rius, Antonio; Saleh, Kauzar; Tarruella, Ramon; Velazquez, Almudena

2004-02-01

The main objective of the SCALES Project is to exploit the unique opportunity offered by the recent launch of the first European METEOSAT Second Generation geostationary satellite (MSG-1) to generate and validate new radiation budget and cloud products provided by the GERB (Geostationary Earth Radiation Budget) instrument. SCALES" specific objectives are: (i) definition and characterization of a large reasonably homogeneous area compatible to GERB pixel size (around 50 x 50 km2), (ii) validation of GERB TOA radiances and fluxes derived by means of angular distribution models, (iii) development of algorithms to estimate surface net radiation from GERB TOA measurements, and (iv) development of accurate methodologies to measure radiation flux divergence and analyze its influence on the thermal regime and dynamics of the atmosphere, also using GERB data. SCALES is highly innovative: it focuses on a new and unique space instrument and develops a new specific validation methodology for low resolution sensors that is based on the use of a robust reference meteorological station (Valencia Anchor Station) around which 3D high resolution meteorological fields are obtained from the MM5 Meteorological Model. During the 1st GERB Ground Validation Campaign (18th-24th June, 2003), CERES instruments on Aqua and Terra provided additional radiance measurements to support validation efforts. CERES instruments operated in the PAPS mode (Programmable Azimuth Plane Scanning) focusing the station. Ground measurements were taken by lidar, sun photometer, GPS precipitable water content, radiosounding ascents, Anchor Station operational meteorological measurements at 2m and 15m., 4 radiation components at 2m, and mobile stations to characterize a large area. In addition, measurements during LANDSAT overpasses on June 14th and 30th were also performed. These activities were carried out within the GIST (GERB International Science Team) framework, during GERB Commissioning Period.

Impact of time displaced precipitation estimates for on-line updated models

DEFF Research Database (Denmark)

Borup, Morten; Grum, Morten; Mikkelsen, Peter Steen

2012-01-01

When an online runoff model is updated from system measurements the requirements to the precipitation estimates change. Using rain gauge data as precipitation input there will be a displacement between the time where the rain intensity hits the gauge and the time where the rain hits the actual...

Hydroclimatic variability in the Lake Mondsee region and its relationships with large-scale climate anomaly patterns

Science.gov (United States)

Rimbu, Norel; Ionita, Monica; Swierczynski, Tina; Brauer, Achim; Kämpf, Lucas; Czymzik, Markus

2017-04-01

Flood triggered detrital layers in varved sediments of Lake Mondsee, located at the northern fringe of the European Alps (47°48'N,13°23'E), provide an important archive of regional hydroclimatic variability during the mid- to late Holocene. To improve the interpretation of the flood layer record in terms of large-scale climate variability, we investigate the relationships between observational hydrological records from the region, like the Mondsee lake level, the runoff of the lake's main inflow Griesler Ache, with observed precipitation and global climate patterns. The lake level shows a strong positive linear trend during the observational period in all seasons. Additionally, lake level presents important interannual to multidecadal variations. These variations are associated with distinct seasonal atmospheric circulation patterns. A pronounced anomalous anticyclonic center over the Iberian Peninsula is associated with high lake levels values during winter. This center moves southwestward during spring, summer and autumn. In the same time, a cyclonic anomaly center is recorded over central and western Europe. This anomalous circulation extends southwestward from winter to autumn. Similar atmospheric circulation patterns are associated with river runoff and precipitation variability from the region. High lake levels are associated with positive local precipitation anomalies in all seasons as well as with negative local temperature anomalies during spring, summer and autumn. A correlation analysis reveals that lake level, runoff and precipitation variability is related to large-scale sea surface temperature anomaly patterns in all seasons suggesting a possible impact of large-scale climatic modes, like the North Atlantic Oscillation and Atlantic Multidecadal Oscillation on hydroclimatic variability in the Lake Mondsee region. The results presented in this study can be used for a more robust interpretation of the long flood layer record from Lake Mondsee sediments

How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?

Science.gov (United States)

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.

Dominant Large-Scale Atmospheric Circulation Systems for the Extreme Precipitation over the Western Sichuan Basin in Summer 2013

Directory of Open Access Journals (Sweden)

Yamin Hu

2015-01-01

Full Text Available The western Sichuan Basin (WSB is a rainstorm center influenced by complicated factors such as topography and circulation. Based on multivariable empirical orthogonal function technique for extreme precipitation processes (EPP in WSB in 2013, this study reveals the dominant circulation patterns. Results indicate that the leading modes are characterized by “Saddle” and “Sandwich” structures, respectively. In one mode, a TC from the South China Sea (SCS converts into the inverted trough and steers warm moist airflow northward into the WSB. At the same time, WPSH extends westward over the Yangtze River and conveys a southeasterly warm humid flow. In the other case, WPSH is pushed westward by TC in the Western Pacific and then merges with an anomalous anticyclone over SCS. The anomalous anticyclone and WPSH form a conjunction belt and convey the warm moist southwesterly airflow to meet with the cold flow over the WSB. The configurations of WPSH and TC in the tropic and the blocking and trough in the midhigh latitudes play important roles during the EPPs over the WSB. The persistence of EPPs depends on the long-lived large-scale circulation configuration steady over the suitable positions.

Large-scale perturbations from the waterfall field in hybrid inflation

International Nuclear Information System (INIS)

Fonseca, José; Wands, David; Sasaki, Misao

2010-01-01

We estimate large-scale curvature perturbations from isocurvature fluctuations in the waterfall field during hybrid inflation, in addition to the usual inflaton field perturbations. The tachyonic instability at the end of inflation leads to an explosive growth of super-Hubble scale perturbations, but they retain the steep blue spectrum characteristic of vacuum fluctuations in a massive field during inflation. The power spectrum thus peaks around the Hubble-horizon scale at the end of inflation. We extend the usual δN formalism to include the essential role of these small fluctuations when estimating the large-scale curvature perturbation. The resulting curvature perturbation due to fluctuations in the waterfall field is second-order and the spectrum is expected to be of order 10 −54 on cosmological scales

The influence of control parameter estimation on large scale geomorphological interpretation of pointclouds

Science.gov (United States)

Dorninger, P.; Koma, Z.; Székely, B.

2012-04-01

either automatically (i.e. estimated of the given data) or manually (i.e. supervised parameter estimation). Additionally, the result might be influenced if data processing is performed locally (i.e. using tiles) or globally. Local processing of the data has the advantages of generally performing faster, having less hardware requirements, and enabling the determination of more detailed information. By contrast, especially in geomorphological interpretation, a global data processing enables determining large scale relations within the dataset analyzed. We investigated the influence of control parameter settings on the geomorphological interpretation on airborne and terrestrial laser scanning data sets of the landslide at Doren (Vorarlberg, Austria), on airborne laser scanning data of the western cordilleras of the central Andes, and on HRSC terrain data of the Mars surface. Topics discussed are the suitability of automated versus manual determination of control parameters, the influence of the definition of the area of interest (local versus global application) as well as computational performance.

Strengthening effect of nano-scaled precipitates in Ta alloying layer induced by high current pulsed electron beam

Energy Technology Data Exchange (ETDEWEB)

Tang, Guangze; Luo, Dian; Fan, Guohua [School of Material Science & Engineering, Harbin Institute of Technology, Harbin 150001 (China); Ma, Xinxin, E-mail: maxin@hit.edu.cn [State Key Laboratory of Advanced Welding and Joining, Harbin Institute of Technology, Harbin 150001 (China); Wang, Liqin [School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001 (China)

2017-05-01

Highlights: • Ta alloying layer are fabricated by magnetron sputtering and high current pulsed electron beam. • Nano-scaled TaC precipitates forms within the δ-Fe grain after tempering treatment. • The mean diameter of TaC particles is about 5–8 nm. • The hardness of alloying layer increased by over 50% after formation of nano-scaled TaC particle. - Abstract: In this study, the combination of magnetron sputtering and high current pulsed electron beam are used for surface alloying treatment of Ta film on high speed steel. And the Ta alloying layer is about 6 μm. After tempering treatment, TaC phase forms in Ta alloying layer when the treated temperature is over 823 K. Through the TEM and HRTEM observation, a large amount of nano-scaled precipitates (mean diameter 5–8 nm) form within the δ-Fe grain in Ta alloying layer after tempering treatment and these nano-scaled precipitates are confirmed as TaC particles, which contribute to the strengthening effect of the surface alloying layer. The hardness of tempered alloying layer can reach to 18.1 GPa when the treated temperature is 823 K which increase by 50% comparing with the untreated steel sample before surface alloying treatment.

Global monsoon precipitation responses to large volcanic eruptions

Science.gov (United States)

Liu, Fei; Chai, Jing; Wang, Bin; Liu, Jian; Zhang, Xiao; Wang, Zhiyuan

2016-01-01

Climate variation of global monsoon (GM) precipitation involves both internal feedback and external forcing. Here, we focus on strong volcanic forcing since large eruptions are known to be a dominant mechanism in natural climate change. It is not known whether large volcanoes erupted at different latitudes have distinctive effects on the monsoon in the Northern Hemisphere (NH) and the Southern Hemisphere (SH). We address this issue using a 1500-year volcanic sensitivity simulation by the Community Earth System Model version 1.0 (CESM1). Volcanoes are classified into three types based on their meridional aerosol distributions: NH volcanoes, SH volcanoes and equatorial volcanoes. Using the model simulation, we discover that the GM precipitation in one hemisphere is enhanced significantly by the remote volcanic forcing occurring in the other hemisphere. This remote volcanic forcing-induced intensification is mainly through circulation change rather than moisture content change. In addition, the NH volcanic eruptions are more efficient in reducing the NH monsoon precipitation than the equatorial ones, and so do the SH eruptions in weakening the SH monsoon, because the equatorial eruptions, despite reducing moisture content, have weaker effects in weakening the off-equatorial monsoon circulation than the subtropical-extratropical volcanoes do. PMID:27063141

The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

Science.gov (United States)

Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2018-01-01

Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

Directory of Open Access Journals (Sweden)

A. F. Van Loon

2012-11-01

Full Text Available Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological drought? To answer this question, we evaluated the simulation of drought propagation in an ensemble mean of ten large-scale models, both land-surface models and global hydrological models, that participated in the model intercomparison project of WATCH (WaterMIP. For a selection of case study areas, we studied drought characteristics (number of droughts, duration, severity, drought propagation features (pooling, attenuation, lag, lengthening, and hydrological drought typology (classical rainfall deficit drought, rain-to-snow-season drought, wet-to-dry-season drought, cold snow season drought, warm snow season drought, composite drought.

Drought characteristics simulated by large-scale models clearly reflected drought propagation; i.e. drought events became fewer and longer when moving through the hydrological cycle. However, more differentiation was expected between fast and slowly responding systems, with slowly responding systems having fewer and longer droughts in runoff than fast responding systems. This was not found using large-scale models. Drought propagation features were poorly reproduced by the large-scale models, because runoff reacted immediately to precipitation, in all case study areas. This fast reaction to precipitation, even in cold climates in winter and in semi-arid climates in summer, also greatly influenced the hydrological drought typology as identified by the large-scale models. In general, the large-scale models had the correct representation of drought types, but the percentages of occurrence had some important mismatches, e.g. an overestimation of classical rainfall deficit droughts, and an

GPM SLH: Convective Latent Heating Estimated with GPM Dual-frequency Precipitation Radar Data

Science.gov (United States)

Takayabu, Y. N.; Hamada, A.; Yokoyama, C.; Ikuta, Y.; Shige, S.; Yamaji, M.; Kubota, T.

2017-12-01

Three dimensional diabatic heating distribution plays essential roles to determine large-scale circulation, as well as to generate mesoscale circulation associated with tropical convection (e.g. Hartmann et al., 1984; Houze et al. 1982). For mid-latitude systems also, diabatic heating contributes to generate PVs resulting in, for example, explosive intensifications of mid-lattitude storms (Boettcher and Wernli, 2011). Previously, with TRMM PR data, we developed a Spectral Latent Heating algorithm (SLH; Shige et al. 2004, etc.) for 36N-36S region. It was based on the spectral LH tables produced from a simulation utilizing the Goddard Cloud Ensemble Model forced with the TOGA-COARE data. With GPM DPR, the observation region is extended to 65N-65S. Here, we introduce a new version of SLH algorithm which is applicable also to the mid-latitude precipitation. A new global GPM SLH ver.5 product is released as one of NASA/JAXA GPM standard products on July 11, 2017. For GPM SLH mid-latitude algorithm, we employ the Japan Meteorological Agency (JMA)'s high resolution (horizontally 2km) Local Forecast Model (LFM) to construct the LUTs. With collaborations of JMA's forecast group, forecast data for 8 extratropical cyclone cases are collected and utilized. For mid-latitude precipitation, we have to deal with large temperature gradients and complex relationship between the freezing level and cloud base levels. LUTs are constructed for LH, Q1-QR, and Q2 (Yanai et al. 1973), for six different precipitation types: Convective and shallow stratiform LUTs are made against precipitation top heights. For deep stratiform and other precipitation, LUTs are made against maximum precipitation to handle the unknown cloud-bases. Finally, three-dimensional convective latent heating is retrieved, utilizing the LUTs and precipitation profile data from GPM 2AKu. We can confirm that retrieved LH looks very similar to simulated LH, for a consistency check. We also confirm a good continuities of

High-strength wrought magnesium alloy with dense nano-scale spherical precipitate

Institute of Scientific and Technical Information of China (English)

YU WenBin; CHEN ZhiQian; CHENG NanPu; GAN BingTai; HE Hong; LI XueLian; HU JinZhu

2007-01-01

This paper reported the influences of Yb addition on the precipitate and mechanical properties of wrought magnesium alloy ZK60. The ingots of ZK60-1.78Yb (wt%,0.26 at%) alloys were cast using permanent mould and extruded at 370℃. By means of TEM and HRTEM,it was observed that Yb affected the precipitate and precipitation of ZK60-1.78Yb alloys significantly. Dynamic precipitation occurred in the as-extruded alloy and spherical nano-scale precipitate with high density and homogeneity exhibited in the aged alloys. The precipitate particles were about 5-20 nm in diameter,10-30 nm in average space length. The tensile test results showed that the ZK60-1.78Yb alloy had excellent precipitation strengthening response with the maximum tensile strength 417.5 MPa at ambient temperature.

Using GRACE to constrain precipitation amount over cold mountainous basins

Science.gov (United States)

Behrangi, Ali; Gardner, Alex S.; Reager, John T.; Fisher, Joshua B.

2017-01-01

Despite the importance for hydrology and climate-change studies, current quantitative knowledge on the amount and distribution of precipitation in mountainous and high-elevation regions is limited due to instrumental and retrieval shortcomings. Here by focusing on two large endorheic basins in High Mountain Asia, we show that satellite gravimetry (Gravity Recovery and Climate Experiment (GRACE)) can be used to provide an independent estimate of monthly accumulated precipitation using mass balance equation. Results showed that the GRACE-based precipitation estimate has the highest agreement with most of the commonly used precipitation products in summer, but it deviates from them in cold months, when the other products are expected to have larger errors. It was found that most of the products capture about or less than 50% of the total precipitation estimated using GRACE in winter. Overall, Global Precipitation Climatology Project (GPCP) showed better agreement with GRACE estimate than other products. Yet on average GRACE showed 30% more annual precipitation than GPCP in the study basins. In basins of appropriate size with an absence of dense ground measurements, as is a typical case in cold mountainous regions, we find GRACE can be a viable alternative to constrain monthly and seasonal precipitation estimates from other remotely sensed precipitation products that show large bias.

Global Precipitation Measurement. Report 7; Bridging from TRMM to GPM to 3-Hourly Precipitation Estimates

Science.gov (United States)

Shepherd, J. Marshall; Smith, Eric A.; Adams, W. James (Editor)

2002-01-01

Historically, multi-decadal measurements of precipitation from surface-based rain gauges have been available over continents. However oceans remained largely unobserved prior to the beginning of the satellite era. Only after the launch of the first Defense Meteorological Satellite Program (DMSP) satellite in 1987 carrying a well-calibrated and multi-frequency passive microwave radiometer called Special Sensor Microwave/Imager (SSM/I) have systematic and accurate precipitation measurements over oceans become available on a regular basis; see Smith et al. (1994, 1998). Recognizing that satellite-based data are a foremost tool for measuring precipitation, NASA initiated a new research program to measure precipitation from space under its Mission to Planet Earth program in the 1990s. As a result, the Tropical Rainfall Measuring Mission (TRMM), a collaborative mission between NASA and NASDA, was launched in 1997 to measure tropical and subtropical rain. See Simpson et al. (1996) and Kummerow et al. (2000). Motivated by the success of TRMM, and recognizing the need for more comprehensive global precipitation measurements, NASA and NASDA have now planned a new mission, i.e., the Global Precipitation Measurement (GPM) mission. The primary goal of GPM is to extend TRMM's rainfall time series while making substantial improvements in precipitation observations, specifically in terms of measurement accuracy, sampling frequency, Earth coverage, and spatial resolution. This report addresses four fundamental questions related to the transition from current to future global precipitation observations as denoted by the TRMM and GPM eras, respectively.

Regime-dependent forecast uncertainty of convective precipitation

Energy Technology Data Exchange (ETDEWEB)

Keil, Christian; Craig, George C. [Muenchen Univ. (Germany). Meteorologisches Inst.

2011-04-15

Forecast uncertainty of convective precipitation is influenced by all scales, but in different ways in different meteorological situations. Forecasts of the high resolution ensemble prediction system COSMO-DE-EPS of Deutscher Wetterdienst (DWD) are used to examine the dominant sources of uncertainty of convective precipitation. A validation with radar data using traditional as well as spatial verification measures highlights differences in precipitation forecast performance in differing weather regimes. When the forecast uncertainty can primarily be associated with local, small-scale processes individual members run with the same variation of the physical parameterisation driven by different global models outperform all other ensemble members. In contrast when the precipitation is governed by the large-scale flow all ensemble members perform similarly. Application of the convective adjustment time scale confirms this separation and shows a regime-dependent forecast uncertainty of convective precipitation. (orig.)

Improving Frozen Precipitation Density Estimation in Land Surface Modeling

Science.gov (United States)

Sparrow, K.; Fall, G. M.

2017-12-01

The Office of Water Prediction (OWP) produces high-value water supply and flood risk planning information through the use of operational land surface modeling. Improvements in diagnosing frozen precipitation density will benefit the NWS's meteorological and hydrological services by refining estimates of a significant and vital input into land surface models. A current common practice for handling the density of snow accumulation in a land surface model is to use a standard 10:1 snow-to-liquid-equivalent ratio (SLR). Our research findings suggest the possibility of a more skillful approach for assessing the spatial variability of precipitation density. We developed a 30-year SLR climatology for the coterminous US from version 3.22 of the Daily Global Historical Climatology Network - Daily (GHCN-D) dataset. Our methods followed the approach described by Baxter (2005) to estimate mean climatological SLR values at GHCN-D sites in the US, Canada, and Mexico for the years 1986-2015. In addition to the Baxter criteria, the following refinements were made: tests were performed to eliminate SLR outliers and frequent reports of SLR = 10, a linear SLR vs. elevation trend was fitted to station SLR mean values to remove the elevation trend from the data, and detrended SLR residuals were interpolated using ordinary kriging with a spherical semivariogram model. The elevation values of each station were based on the GMTED 2010 digital elevation model and the elevation trend in the data was established via linear least squares approximation. The ordinary kriging procedure was used to interpolate the data into gridded climatological SLR estimates for each calendar month at a 0.125 degree resolution. To assess the skill of this climatology, we compared estimates from our SLR climatology with observations from the GHCN-D dataset to consider the potential use of this climatology as a first guess of frozen precipitation density in an operational land surface model. The difference in

Strong increase in convective precipitation in response to higher temperatures

DEFF Research Database (Denmark)

Berg, P.; Moseley, C.; Härter, Jan Olaf Mirko

2013-01-01

Precipitation changes can affect society more directly than variations in most other meteorological observables, but precipitation is difficult to characterize because of fluctuations on nearly all temporal and spatial scales. In addition, the intensity of extreme precipitation rises markedly...... at higher temperature, faster than the rate of increase in the atmosphere's water-holding capacity, termed the Clausius-Clapeyron rate. Invigoration of convective precipitation (such as thunderstorms) has been favoured over a rise in stratiform precipitation (such as large-scale frontal precipitation......) as a cause for this increase , but the relative contributions of these two types of precipitation have been difficult to disentangle. Here we combine large data sets from radar measurements and rain gauges over Germany with corresponding synoptic observations and temperature records, and separate convective...

Estimation of Truck Trips on Large-Scale Irrigation Project: A Combinatory Input-Output Commodity-Based Approach

Directory of Open Access Journals (Sweden)

Ackchai Sirikijpanichkul

2015-01-01

Full Text Available For the agricultural-based countries, the requirement on transportation infrastructure should not only be limited to accommodate general traffic but also the transportation of crop and agricultural products during the harvest seasons. Most of the past researches focus on the development of truck trip estimation techniques for urban, statewide, or nationwide freight movement but neglect the importance of rural freight movement which contributes to pavement deterioration on rural roads especially during harvest seasons. Recently, the Thai Government initiated a plan to construct a network of reservoirs within the northeastern region, aiming at improving existing irrigation system particularly in the areas where a more effective irrigation system is needed. It is expected to bring in new opportunities on expanding the cultivation areas, increasing the economy of scale and enlarging the extent market of area. As a consequence, its effects on truck trip generation needed to be investigated to assure the service quality of related transportation infrastructure. This paper proposes a combinatory input-output commodity-based approach to estimate truck trips on rural highway infrastructure network. The large-scale irrigation project for the northeastern of Thailand is demonstrated as a case study.

Potential climatic impacts and reliability of large-scale offshore wind farms

International Nuclear Information System (INIS)

Wang Chien; Prinn, Ronald G

2011-01-01

The vast availability of wind power has fueled substantial interest in this renewable energy source as a potential near-zero greenhouse gas emission technology for meeting future world energy needs while addressing the climate change issue. However, in order to provide even a fraction of the estimated future energy needs, a large-scale deployment of wind turbines (several million) is required. The consequent environmental impacts, and the inherent reliability of such a large-scale usage of intermittent wind power would have to be carefully assessed, in addition to the need to lower the high current unit wind power costs. Our previous study (Wang and Prinn 2010 Atmos. Chem. Phys. 10 2053) using a three-dimensional climate model suggested that a large deployment of wind turbines over land to meet about 10% of predicted world energy needs in 2100 could lead to a significant temperature increase in the lower atmosphere over the installed regions. A global-scale perturbation to the general circulation patterns as well as to the cloud and precipitation distribution was also predicted. In the later study reported here, we conducted a set of six additional model simulations using an improved climate model to further address the potential environmental and intermittency issues of large-scale deployment of offshore wind turbines for differing installation areas and spatial densities. In contrast to the previous land installation results, the offshore wind turbine installations are found to cause a surface cooling over the installed offshore regions. This cooling is due principally to the enhanced latent heat flux from the sea surface to lower atmosphere, driven by an increase in turbulent mixing caused by the wind turbines which was not entirely offset by the concurrent reduction of mean wind kinetic energy. We found that the perturbation of the large-scale deployment of offshore wind turbines to the global climate is relatively small compared to the case of land

A Gossip-based Churn Estimator for Large Dynamic Networks

NARCIS (Netherlands)

Giuffrida, C.; Ortolani, S.

2010-01-01

Gossip-based aggregation is an emerging paradigm to perform distributed computations and measurements in a large-scale setting. In this paper we explore the possibility of using gossip-based aggregation to estimate churn in arbitrarily large networks. To this end, we introduce a new model to compute

Auroral electrojet dynamics during magnetic storms, connection with plasma precipitation and large-scale structure of the magnetospheric magnetic field

Directory of Open Access Journals (Sweden)

Y. I. Feldstein

1999-04-01

magnetospheric magnetic field paraboloid model the influence of the ring current and magnetospheric tail plasma sheet currents on large-scale magnetosphere structure is considered.Key words. Ionosphere (particle precipitation · Magnetospheric physics (current systems; magnetospheric configuration and dynamics.

Correlation Lengths for Estimating the Large-Scale Carbon and Heat Content of the Southern Ocean

Science.gov (United States)

Mazloff, M. R.; Cornuelle, B. D.; Gille, S. T.; Verdy, A.

2018-02-01

The spatial correlation scales of oceanic dissolved inorganic carbon, heat content, and carbon and heat exchanges with the atmosphere are estimated from a realistic numerical simulation of the Southern Ocean. Biases in the model are assessed by comparing the simulated sea surface height and temperature scales to those derived from optimally interpolated satellite measurements. While these products do not resolve all ocean scales, they are representative of the climate scale variability we aim to estimate. Results show that constraining the carbon and heat inventory between 35°S and 70°S on time-scales longer than 90 days requires approximately 100 optimally spaced measurement platforms: approximately one platform every 20° longitude by 6° latitude. Carbon flux has slightly longer zonal scales, and requires a coverage of approximately 30° by 6°. Heat flux has much longer scales, and thus a platform distribution of approximately 90° by 10° would be sufficient. Fluxes, however, have significant subseasonal variability. For all fields, and especially fluxes, sustained measurements in time are required to prevent aliasing of the eddy signals into the longer climate scale signals. Our results imply a minimum of 100 biogeochemical-Argo floats are required to monitor the Southern Ocean carbon and heat content and air-sea exchanges on time-scales longer than 90 days. However, an estimate of formal mapping error using the current Argo array implies that in practice even an array of 600 floats (a nominal float density of about 1 every 7° longitude by 3° latitude) will result in nonnegligible uncertainty in estimating climate signals.

The Relative Performance of High Resolution Quantitative Precipitation Estimates in the Russian River Basin

Science.gov (United States)

Bytheway, J. L.; Biswas, S.; Cifelli, R.; Hughes, M.

2017-12-01

The Russian River carves a 110 mile path through Mendocino and Sonoma counties in western California, providing water for thousands of residents and acres of agriculture as well as a home for several species of endangered fish. The Russian River basin receives almost all of its precipitation during the October through March wet season, and the systems bringing this precipitation are often impacted by atmospheric river events as well as the complex topography of the region. This study will examine the performance of several high resolution (hourly, products and forecasts over the 2015-2016 and 2016-2017 wet seasons. Comparisons of event total rainfall as well as hourly rainfall will be performed using 1) rain gauges operated by the National Oceanic and Atmospheric Administration (NOAA) Physical Sciences Division (PSD), 2) products from the Multi-Radar/Multi-Sensor (MRMS) QPE dataset, and 3) quantitative precipitation forecasts from the High Resolution Rapid Refresh (HRRR) model at 1, 3, 6, and 12 hour lead times. Further attention will be given to cases or locations representing large disparities between the estimates.

Evaluation of performance of seasonal precipitation prediction at regional scale over India

Science.gov (United States)

Mohanty, U. C.; Nageswararao, M. M.; Sinha, P.; Nair, A.; Singh, A.; Rai, R. K.; Kar, S. C.; Ramesh, K. J.; Singh, K. K.; Ghosh, K.; Rathore, L. S.; Sharma, R.; Kumar, A.; Dhekale, B. S.; Maurya, R. K. S.; Sahoo, R. K.; Dash, G. P.

2018-03-01

The seasonal scale precipitation amount is an important ingredient in planning most of the agricultural practices (such as a type of crops, and showing and harvesting schedules). India being an agroeconomic country, the seasonal scale prediction of precipitation is directly linked to the socioeconomic growth of the nation. At present, seasonal precipitation prediction at regional scale is a challenging task for the scientific community. In the present study, an attempt is made to develop multi-model dynamical-statistical approach for seasonal precipitation prediction at the regional scale (meteorological subdivisions) over India for four prominent seasons which are winter (from December to February; DJF), pre-monsoon (from March to May; MAM), summer monsoon (from June to September; JJAS), and post-monsoon (from October to December; OND). The present prediction approach is referred as extended range forecast system (ERFS). For this purpose, precipitation predictions from ten general circulation models (GCMs) are used along with the India Meteorological Department (IMD) rainfall analysis data from 1982 to 2008 for evaluation of the performance of the GCMs, bias correction of the model results, and development of the ERFS. An extensive evaluation of the performance of the ERFS is carried out with dependent data (1982-2008) as well as independent predictions for the period 2009-2014. In general, the skill of the ERFS is reasonably better and consistent for all the seasons and different regions over India as compared to the GCMs and their simple mean. The GCM products failed to explain the extreme precipitation years, whereas the bias-corrected GCM mean and the ERFS improved the prediction and well represented the extremes in the hindcast period. The peak intensity, as well as regions of maximum precipitation, is better represented by the ERFS than the individual GCMs. The study highlights the improvement of forecast skill of the ERFS over 34 meteorological subdivisions

Radar rainfall estimation for the identification of debris-flow precipitation thresholds

Science.gov (United States)

Marra, Francesco; Nikolopoulos, Efthymios I.; Creutin, Jean-Dominique; Borga, Marco

2014-05-01

Identification of rainfall thresholds for the prediction of debris-flow occurrence is a common approach for warning procedures. Traditionally the debris-flow triggering rainfall is derived from the closest available raingauge. However, the spatial and temporal variability of intense rainfall on mountainous areas, where debris flows take place, may lead to large uncertainty in point-based estimates. Nikolopoulos et al. (2014) have shown that this uncertainty translates into a systematic underestimation of the rainfall thresholds, leading to a step degradation of the performances of the rainfall threshold for identification of debris flows occurrence under operational conditions. A potential solution to this limitation lies on use of rainfall estimates from weather radar. Thanks to their high spatial and temporal resolutions, these estimates offer the advantage of providing rainfall information over the actual debris flow location. The aim of this study is to analyze the value of radar precipitation estimations for the identification of debris flow precipitation thresholds. Seven rainfall events that triggered debris flows in the Adige river basin (Eastern Italian Alps) are analyzed using data from a dense raingauge network and a C-Band weather radar. Radar data are elaborated by using a set of correction algorithms specifically developed for weather radar rainfall application in mountainous areas. Rainfall thresholds for the triggering of debris flows are identified in the form of average intensity-duration power law curves using a frequentist approach by using both radar rainfall estimates and raingauge data. Sampling uncertainty associated to the derivation of the thresholds is assessed by using a bootstrap technique (Peruccacci et al. 2012). Results show that radar-based rainfall thresholds are largely exceeding those obtained by using raingauge data. Moreover, the differences between the two thresholds may be related to the spatial characteristics (i.e., spatial

Wind and Photovoltaic Large-Scale Regional Models for hourly production evaluation

DEFF Research Database (Denmark)

Marinelli, Mattia; Maule, Petr; Hahmann, Andrea N.

2015-01-01

This work presents two large-scale regional models used for the evaluation of normalized power output from wind turbines and photovoltaic power plants on a European regional scale. The models give an estimate of renewable production on a regional scale with 1 h resolution, starting from a mesosca...... of the transmission system, especially regarding the cross-border power flows. The tuning of these regional models is done using historical meteorological data acquired on a per-country basis and using publicly available data of installed capacity.......This work presents two large-scale regional models used for the evaluation of normalized power output from wind turbines and photovoltaic power plants on a European regional scale. The models give an estimate of renewable production on a regional scale with 1 h resolution, starting from a mesoscale...

Evaluation of spatial and spatiotemporal estimation methods in simulation of precipitation variability patterns

Science.gov (United States)

Bayat, Bardia; Zahraie, Banafsheh; Taghavi, Farahnaz; Nasseri, Mohsen

2013-08-01

Identification of spatial and spatiotemporal precipitation variations plays an important role in different hydrological applications such as missing data estimation. In this paper, the results of Bayesian maximum entropy (BME) and ordinary kriging (OK) are compared for modeling spatial and spatiotemporal variations of annual precipitation with and without incorporating elevation variations. The study area of this research is Namak Lake watershed located in the central part of Iran with an area of approximately 90,000 km2. The BME and OK methods have been used to model the spatial and spatiotemporal variations of precipitation in this watershed, and their performances have been evaluated using cross-validation statistics. The results of the case study have shown the superiority of BME over OK in both spatial and spatiotemporal modes. The results have shown that BME estimates are less biased and more accurate than OK. The improvements in the BME estimates are mostly related to incorporating hard and soft data in the estimation process, which resulted in more detailed and reliable results. Estimation error variance for BME results is less than OK estimations in the study area in both spatial and spatiotemporal modes.

Revising the potential of large-scale Jatropha oil production in Tanzania: An economic land evaluation assessment

International Nuclear Information System (INIS)

Segerstedt, Anna; Bobert, Jans

2013-01-01

Following up the rather sobering results of the biofuels boom in Tanzania, we analyze the preconditions that would make large-scale oil production from the feedstock Jatropha curcas viable. We do this by employing an economic land evaluation approach; first, we estimate the physical land suitability and the necessary inputs to reach certain amounts of yields. Subsequently, we estimate costs and benefits for different input-output levels. Finally, to incorporate the increased awareness of sustainability in the export sector, we introduce also certification criteria. Using data from an experimental farm in Kilosa, we find that high yields are crucial for the economic feasibility and that they can only be obtained on good soils at high input rates. Costs of compliance with certification criteria depend on site specific characteristics such as land suitability and precipitation. In general, both domestic production and (certified) exports are too expensive to be able to compete with conventional diesel/rapeseed oil from the EU. Even though the crop may have potential for large scale production as a niche product, there is still a lot of risk involved and more experimental research is needed. - Highlights: ► We use an economic land evaluation analysis to reassess the potential of large-scale Jatropha oil. ► High yields are possible only at high input rates and for good soil qualities. ► Production costs are still too high to break even on the domestic and export market. ► More research is needed to stabilize yields and improve the oil content. ► Focus should be on broadening our knowledge-base rather than promoting new Jatropha investments

Precipitation Analysis at Fine Time Scales using TRMM and Other Satellites: Realtime and Research Products and Applications

Science.gov (United States)

Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold; Gu, Guojon

2004-01-01

Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the TRMM Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) by the end of 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25 deg latitude-longitude resolution over the latitude range from 50 deg N-50 deg S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

Simulating the convective precipitation diurnal cycle in a North American scale convection-permitting model

Science.gov (United States)

Scaff, L.; Li, Y.; Prein, A. F.; Liu, C.; Rasmussen, R.; Ikeda, K.

2017-12-01

A better representation of the diurnal cycle of convective precipitation is essential for the analysis of the energy balance and the water budget components such as runoff, evaporation and infiltration. Convection-permitting regional climate modeling (CPM) has been shown to improve the models' performance of summer precipitation, allowing to: (1) simulate the mesoscale processes in more detail and (2) to provide more insights in future changes in convective precipitation under climate change. In this work we investigate the skill of the Weather Research and Forecast model (WRF) in simulating the summer precipitation diurnal cycle over most of North America. We use 4 km horizontal grid spacing in a 13-years long current and future period. The future scenario is assuming no significant changes in large-scale weather patterns and aims to answer how the weather of the current climate would change if it would reoccur at the end of the century under a high-end emission scenario (Pseudo Global Warming). We emphasize on a region centered on the lee side of the Canadian Rocky Mountains, where the summer precipitation amount shows a regional maximum. The historical simulations are capable to correctly represent the diurnal cycle. At the lee-side of the Canadian Rockies the increase in the convective available potential energy as well as pronounced low-level moisture flux from the southeast Prairies explains the local maximum in summer precipitation. The PGW scenario shows an increase in summer precipitation amount and intensity in this region, consistently with a stronger source of moisture and convective energy.

Estimating Reservoir Inflow Using RADAR Forecasted Precipitation and Adaptive Neuro Fuzzy Inference System

Science.gov (United States)

Yi, J.; Choi, C.

2014-12-01

Rainfall observation and forecasting using remote sensing such as RADAR(Radio Detection and Ranging) and satellite images are widely used to delineate the increased damage by rapid weather changeslike regional storm and flash flood. The flood runoff was calculated by using adaptive neuro-fuzzy inference system, the data driven models and MAPLE(McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as the input variables.The result of flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated by comparing it with the actual data.The Adaptive Neuro Fuzzy method was applied to the Chungju Reservoir basin in Korea. The six rainfall events during the flood seasons in 2010 and 2011 were used for the input data.The reservoir inflow estimation results were comparedaccording to the rainfall data used for training, checking and testing data in the model setup process. The results of the 15 models with the combination of the input variables were compared and analyzed. Using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation in this study.The model using the MAPLE forecasted precipitation data showed better result for inflow estimation in the Chungju Reservoir.

Characterisation of extreme winter precipitation in Mediterranean coastal sites and associated anomalous atmospheric circulation patterns

Science.gov (United States)

Toreti, A.; Xoplaki, E.; Maraun, D.; Kuglitsch, F. G.; Wanner, H.; Luterbacher, J.

2010-05-01

We present an analysis of daily extreme precipitation events for the extended winter season (October-March) at 20 Mediterranean coastal sites covering the period 1950-2006. The heavy tailed behaviour of precipitation extremes and estimated return levels, including associated uncertainties, are derived applying a procedure based on the Generalized Pareto Distribution, in combination with recently developed methods. Precipitation extremes have an important contribution to make seasonal totals (approximately 60% for all series). Three stations (one in the western Mediterranean and the others in the eastern basin) have a 5-year return level above 100 mm, while the lowest value (estimated for two Italian series) is equal to 58 mm. As for the 50-year return level, an Italian station (Genoa) has the highest value of 264 mm, while the other values range from 82 to 200 mm. Furthermore, six series (from stations located in France, Italy, Greece, and Cyprus) show a significant negative tendency in the probability of observing an extreme event. The relationship between extreme precipitation events and the large scale atmospheric circulation at the upper, mid and low troposphere is investigated by using NCEP/NCAR reanalysis data. A 2-step classification procedure identifies three significant anomaly patterns both for the western-central and eastern part of the Mediterranean basin. In the western Mediterranean, the anomalous southwesterly surface to mid-tropospheric flow is connected with enhanced moisture transport from the Atlantic. During ≥5-year return level events, the subtropical jet stream axis is aligned with the African coastline and interacts with the eddy-driven jet stream. This is connected with enhanced large scale ascending motions, instability and leads to the development of severe precipitation events. For the eastern Mediterranean extreme precipitation events, the identified anomaly patterns suggest warm air advection connected with anomalous ascent motions

Characterisation of extreme winter precipitation in Mediterranean coastal sites and associated anomalous atmospheric circulation patterns

Directory of Open Access Journals (Sweden)

A. Toreti

2010-05-01

Full Text Available We present an analysis of daily extreme precipitation events for the extended winter season (October–March at 20 Mediterranean coastal sites covering the period 1950–2006. The heavy tailed behaviour of precipitation extremes and estimated return levels, including associated uncertainties, are derived applying a procedure based on the Generalized Pareto Distribution, in combination with recently developed methods. Precipitation extremes have an important contribution to make seasonal totals (approximately 60% for all series. Three stations (one in the western Mediterranean and the others in the eastern basin have a 5-year return level above 100 mm, while the lowest value (estimated for two Italian series is equal to 58 mm. As for the 50-year return level, an Italian station (Genoa has the highest value of 264 mm, while the other values range from 82 to 200 mm. Furthermore, six series (from stations located in France, Italy, Greece, and Cyprus show a significant negative tendency in the probability of observing an extreme event. The relationship between extreme precipitation events and the large scale atmospheric circulation at the upper, mid and low troposphere is investigated by using NCEP/NCAR reanalysis data. A 2-step classification procedure identifies three significant anomaly patterns both for the western-central and eastern part of the Mediterranean basin. In the western Mediterranean, the anomalous southwesterly surface to mid-tropospheric flow is connected with enhanced moisture transport from the Atlantic. During ≥5-year return level events, the subtropical jet stream axis is aligned with the African coastline and interacts with the eddy-driven jet stream. This is connected with enhanced large scale ascending motions, instability and leads to the development of severe precipitation events. For the eastern Mediterranean extreme precipitation events, the identified anomaly patterns suggest warm air advection connected with anomalous

Quantitative precipitation estimation based on high-resolution numerical weather prediction and data assimilation with WRF – a performance test

Directory of Open Access Journals (Sweden)

Hans-Stefan Bauer

2015-04-01

Full Text Available Quantitative precipitation estimation and forecasting (QPE and QPF are among the most challenging tasks in atmospheric sciences. In this work, QPE based on numerical modelling and data assimilation is investigated. Key components are the Weather Research and Forecasting (WRF model in combination with its 3D variational assimilation scheme, applied on the convection-permitting scale with sophisticated model physics over central Europe. The system is operated in a 1-hour rapid update cycle and processes a large set of in situ observations, data from French radar systems, the European GPS network and satellite sensors. Additionally, a free forecast driven by the ECMWF operational analysis is included as a reference run representing current operational precipitation forecasting. The verification is done both qualitatively and quantitatively by comparisons of reflectivity, accumulated precipitation fields and derived verification scores for a complex synoptic situation that developed on 26 and 27 September 2012. The investigation shows that even the downscaling from ECMWF represents the synoptic situation reasonably well. However, significant improvements are seen in the results of the WRF QPE setup, especially when the French radar data are assimilated. The frontal structure is more defined and the timing of the frontal movement is improved compared with observations. Even mesoscale band-like precipitation structures on the rear side of the cold front are reproduced, as seen by radar. The improvement in performance is also confirmed by a quantitative comparison of the 24-hourly accumulated precipitation over Germany. The mean correlation of the model simulations with observations improved from 0.2 in the downscaling experiment and 0.29 in the assimilation experiment without radar data to 0.56 in the WRF QPE experiment including the assimilation of French radar data.

Scaling of precipitation extremes with temperature in the French Mediterranean region: What explains the hook shape?

Science.gov (United States)

Drobinski, P.; Alonzo, B.; Bastin, S.; Silva, N. Da; Muller, C.

2016-04-01

Expected changes to future extreme precipitation remain a key uncertainty associated with anthropogenic climate change. Extreme precipitation has been proposed to scale with the precipitable water content in the atmosphere. Assuming constant relative humidity, this implies an increase of precipitation extremes at a rate of about 7% °C-1 globally as indicated by the Clausius-Clapeyron relationship. Increases faster and slower than Clausius-Clapeyron have also been reported. In this work, we examine the scaling between precipitation extremes and temperature in the present climate using simulations and measurements from surface weather stations collected in the frame of the HyMeX and MED-CORDEX programs in Southern France. Of particular interest are departures from the Clausius-Clapeyron thermodynamic expectation, their spatial and temporal distribution, and their origin. Looking at the scaling of precipitation extreme with temperature, two regimes emerge which form a hook shape: one at low temperatures (cooler than around 15°C) with rates of increase close to the Clausius-Clapeyron rate and one at high temperatures (warmer than about 15°C) with sub-Clausius-Clapeyron rates and most often negative rates. On average, the region of focus does not seem to exhibit super Clausius-Clapeyron behavior except at some stations, in contrast to earlier studies. Many factors can contribute to departure from Clausius-Clapeyron scaling: time and spatial averaging, choice of scaling temperature (surface versus condensation level), and precipitation efficiency and vertical velocity in updrafts that are not necessarily constant with temperature. But most importantly, the dynamical contribution of orography to precipitation in the fall over this area during the so-called "Cevenoles" events, explains the hook shape of the scaling of precipitation extremes.

Projections of the Ganges-Brahmaputra precipitation: downscaled from GCM predictors

Science.gov (United States)

Pervez, Md Shahriar; Henebry, Geoffrey M.

2014-01-01

Downscaling Global Climate Model (GCM) projections of future climate is critical for impact studies. Downscaling enables use of GCM experiments for regional scale impact studies by generating regionally specific forecasts connecting global scale predictions and regional scale dynamics. We employed the Statistical Downscaling Model (SDSM) to downscale 21st century precipitation for two data-sparse hydrologically challenging river basins in South Asia—the Ganges and the Brahmaputra. We used CGCM3.1 by Canadian Center for Climate Modeling and Analysis version 3.1 predictors in downscaling the precipitation. Downscaling was performed on the basis of established relationships between historical Global Summary of Day observed precipitation records from 43 stations and National Center for Environmental Prediction re-analysis large scale atmospheric predictors. Although the selection of predictors was challenging during the set-up of SDSM, they were found to be indicative of important physical forcings in the basins. The precipitation of both basins was largely influenced by geopotential height: the Ganges precipitation was modulated by the U component of the wind and specific humidity at 500 and 1000 h Pa pressure levels; whereas, the Brahmaputra precipitation was modulated by the V component of the wind at 850 and 1000 h Pa pressure levels. The evaluation of the SDSM performance indicated that model accuracy for reproducing precipitation at the monthly scale was acceptable, but at the daily scale the model inadequately simulated some daily extreme precipitation events. Therefore, while the downscaled precipitation may not be the suitable input to analyze future extreme flooding or drought events, it could be adequate for analysis of future freshwater availability. Analysis of the CGCM3.1 downscaled precipitation projection with respect to observed precipitation reveals that the precipitation regime in each basin may be significantly impacted by climate change

Evaluation of the WRF model for precipitation downscaling on orographic complex islands

Science.gov (United States)

Díaz, Juan P.; González, Albano; Expósito, Francisco; Pérez, Juan C.

2010-05-01

General Circulation Models (GCMs) have proven to be an effective tool to simulate many aspects of large-scale and global climate. However, their applicability to climate impact studies is limited by their capabilities to resolve regional scale situations. In this sense, dynamical downscaling techniques are an appropriate alternative to estimate high resolution regional climatologies. In this work, the Weather Research and Forecasting model (WRF) has been used to simulate precipitations over the Canary Islands region during 2009. The precipitation patterns over Canary Islands, located at North Atlantic region, show large gradients over a relatively small geographical area due to large scale factors such as Trade Winds regime predominant in the area and mesoscale factors mainly due to the complex terrain. Sensitivity study of simulated WRF precipitations to variations in model setup and parameterizations was carried out. Thus, WRF experiments were performed using two way nesting at 3 km horizontal grid spacing and 28 vertical levels in the Canaries inner domain. The initial and lateral and lower boundary conditions for the outer domain were provided at 6 hourly intervals by NCEP FNL (Final) Operational Global Analysis data on 1.0x1.0 degree resolution interpolated onto the WRF model grid. Numerous model options have been tested, including different microphysics schemes, cumulus parameterizations and nudging configuration Positive-definite moisture advection condition was also checked. Two integration approaches were analyzed: a 1-year continuous long-term integration and a consecutive short-term monthly reinitialized integration. To assess the accuracy of our simulations, model results are compared against observational datasets obtained from a network of meteorological stations in the region. In general, we can observe that the regional model is able to reproduce the spatial distribution of precipitation, but overestimates rainfall, mainly during strong

Large-scale structure of the Universe

International Nuclear Information System (INIS)

Doroshkevich, A.G.

1978-01-01

The problems, discussed at the ''Large-scale Structure of the Universe'' symposium are considered on a popular level. Described are the cell structure of galaxy distribution in the Universe, principles of mathematical galaxy distribution modelling. The images of cell structures, obtained after reprocessing with the computer are given. Discussed are three hypothesis - vortical, entropic, adiabatic, suggesting various processes of galaxy and galaxy clusters origin. A considerable advantage of the adiabatic hypothesis is recognized. The relict radiation, as a method of direct studying the processes taking place in the Universe is considered. The large-scale peculiarities and small-scale fluctuations of the relict radiation temperature enable one to estimate the turbance properties at the pre-galaxy stage. The discussion of problems, pertaining to studying the hot gas, contained in galaxy clusters, the interactions within galaxy clusters and with the inter-galaxy medium, is recognized to be a notable contribution into the development of theoretical and observational cosmology

A space and time scale-dependent nonlinear geostatistical approach for downscaling daily precipitation and temperature

KAUST Repository

Jha, Sanjeev Kumar

2015-07-21

A geostatistical framework is proposed to downscale daily precipitation and temperature. The methodology is based on multiple-point geostatistics (MPS), where a multivariate training image is used to represent the spatial relationship between daily precipitation and daily temperature over several years. Here, the training image consists of daily rainfall and temperature outputs from the Weather Research and Forecasting (WRF) model at 50 km and 10 km resolution for a twenty year period ranging from 1985 to 2004. The data are used to predict downscaled climate variables for the year 2005. The result, for each downscaled pixel, is daily time series of precipitation and temperature that are spatially dependent. Comparison of predicted precipitation and temperature against a reference dataset indicates that both the seasonal average climate response together with the temporal variability are well reproduced. The explicit inclusion of time dependence is explored by considering the climate properties of the previous day as an additional variable. Comparison of simulations with and without inclusion of time dependence shows that the temporal dependence only slightly improves the daily prediction because the temporal variability is already well represented in the conditioning data. Overall, the study shows that the multiple-point geostatistics approach is an efficient tool to be used for statistical downscaling to obtain local scale estimates of precipitation and temperature from General Circulation Models. This article is protected by copyright. All rights reserved.

Combining Radar and Daily Precipitation Data to Estimate Meaningful Sub-daily Precipitation Extremes

Science.gov (United States)

Pegram, G. G. S.; Bardossy, A.

2016-12-01

Short duration extreme rainfalls are important for design. The purpose of this presentation is not to improve the day by day estimation of precipitation, but to obtain reasonable statistics for the subdaily extremes at gauge locations. We are interested specifically in daily and sub-daily extreme values of precipitation at gauge locations. We do not employ the common procedure of using time series of control station to determine the missing data values in a target. We are interested in individual rare events, not sequences. The idea is to use radar to disaggregate daily totals to sub-daily amounts. In South Arica, an S-band radar operated relatively continuously at Bethlehem from 1998 to 2003, whose scan at 1.5 km above ground [CAPPI] overlapped a dense (10 km spacing) set of 45 pluviometers recording in the same 6-year period. Using this valuable set of data, we are only interested in rare extremes, therefore small to medium values of rainfall depth were neglected, leaving 12 days of ranked daily maxima in each set per year, whose sum typically comprised about 50% of each annual rainfall total. The method presented here uses radar for disaggregating daily gauge totals in subdaily intervals down to 15 minutes in order to extract the maxima of sub-hourly through to daily rainfall at each of 37 selected radar pixels [1 km square in plan] which contained one of the 45 pluviometers not masked out by the radar foot-print. The pluviometer data were aggregated to daily totals, to act as if they were daily read gauges; their only other task was to help in the cross-validation exercise. The extrema were obtained as quantiles by ordering the 12 daily maxima of each interval per year. The unusual and novel goal was not to obtain the reproduction of the precipitation matching in space and time, but to obtain frequency distributions of the gauge and radar extremes, by matching their ranks, which we found to be stable and meaningful in cross-validation tests. We provide and

Precipitation Dynamical Downscaling Over the Great Plains

Science.gov (United States)

Hu, Xiao-Ming; Xue, Ming; McPherson, Renee A.; Martin, Elinor; Rosendahl, Derek H.; Qiao, Lei

2018-02-01

Detailed, regional climate projections, particularly for precipitation, are critical for many applications. Accurate precipitation downscaling in the United States Great Plains remains a great challenge for most Regional Climate Models, particularly for warm months. Most previous dynamic downscaling simulations significantly underestimate warm-season precipitation in the region. This study aims to achieve a better precipitation downscaling in the Great Plains with the Weather Research and Forecast (WRF) model. To this end, WRF simulations with different physics schemes and nudging strategies are first conducted for a representative warm season. Results show that different cumulus schemes lead to more pronounced difference in simulated precipitation than other tested physics schemes. Simply choosing different physics schemes is not enough to alleviate the dry bias over the southern Great Plains, which is related to an anticyclonic circulation anomaly over the central and western parts of continental U.S. in the simulations. Spectral nudging emerges as an effective solution for alleviating the precipitation bias. Spectral nudging ensures that large and synoptic-scale circulations are faithfully reproduced while still allowing WRF to develop small-scale dynamics, thus effectively suppressing the large-scale circulation anomaly in the downscaling. As a result, a better precipitation downscaling is achieved. With the carefully validated configurations, WRF downscaling is conducted for 1980-2015. The downscaling captures well the spatial distribution of monthly climatology precipitation and the monthly/yearly variability, showing improvement over at least two previously published precipitation downscaling studies. With the improved precipitation downscaling, a better hydrological simulation over the trans-state Oologah watershed is also achieved.

Formation and Thermal Stability of Large Precipitates and Oxides in Titanium and Niobium Microalloyed Steel

Institute of Scientific and Technical Information of China (English)

ZHUO Xiao-jun; WOO Dae-hee; WANG Xin-hua; LEE Hae-geon

2008-01-01

As-cast CC slabs of microalloyed steels are prone to surface and sub-surface cracking. Precipitation phenomena in-itiated during solidification reduce ductility at high temperature. The unidirectional solidification unit is employed to sim-ulate the solidification process during continuous casting. Precipitation behavior and thermal stability are systemati-cally investigated. Samples of adding titanium and niobium to steels have been examined using field emission scanning electron microscope (FE-SEM), electron probe X-ray microanalyzer (EPMA), and transmission electron microscope (TEM). It has been found that the addition of titanium and niobium to high-strength low-alloyed (HSLA) steel resuited in undesirable large precipitation in the steels, i. e. , precipitation of large precipitates with various morphologies. The composition of the large precipitates has been determined. The effect of cooling rate on (Ti, Nb)(C, N) precipitate formation is investigated. With increasing the cooling rate, titanium-rich (Ti,Nb)(C, N) precipitates are transformed to niobium-rich (Ti,Nb)(C,N) precipitates. The thermal stability of these large precipitates and oxides have been assessed by carrying out various heat treatments such as holding and quenching from temperature at 800 and 1 200 ℃. It has been found that titanium-rich (Ti,Nb)(C,N) precipitate is stable at about 1 200 ℃ and niobi-um-rich (Ti,Nb)(C,N) precipitate is stable at about 800 ℃. After reheating at 1 200 ℃ for 1 h, (Ca, Mn)S and TiN are precipitated from Ca-Al oxide. However, during reheating at 800 ℃ for 1 h, Ca-Al-Ti oxide in specimens was stable. The thermodynamic calculation of simulating the thermal process is employed. The calculation results are in good agreement with the experimental results.

An "Ensemble Approach" to Modernizing Extreme Precipitation Estimation for Dam Safety Decision-Making

Science.gov (United States)

Cifelli, R.; Mahoney, K. M.; Webb, R. S.; McCormick, B.

2017-12-01

To ensure structural and operational safety of dams and other water management infrastructure, water resources managers and engineers require information about the potential for heavy precipitation. The methods and data used to estimate extreme rainfall amounts for managing risk are based on 40-year-old science and in need of improvement. The need to evaluate new approaches based on the best science available has led the states of Colorado and New Mexico to engage a body of scientists and engineers in an innovative "ensemble approach" to updating extreme precipitation estimates. NOAA is at the forefront of one of three technical approaches that make up the "ensemble study"; the three approaches are conducted concurrently and in collaboration with each other. One approach is the conventional deterministic, "storm-based" method, another is a risk-based regional precipitation frequency estimation tool, and the third is an experimental approach utilizing NOAA's state-of-the-art High Resolution Rapid Refresh (HRRR) physically-based dynamical weather prediction model. The goal of the overall project is to use the individual strengths of these different methods to define an updated and broadly acceptable state of the practice for evaluation and design of dam spillways. This talk will highlight the NOAA research and NOAA's role in the overarching goal to better understand and characterizing extreme precipitation estimation uncertainty. The research led by NOAA explores a novel high-resolution dataset and post-processing techniques using a super-ensemble of hourly forecasts from the HRRR model. We also investigate how this rich dataset may be combined with statistical methods to optimally cast the data in probabilistic frameworks. NOAA expertise in the physical processes that drive extreme precipitation is also employed to develop careful testing and improved understanding of the limitations of older estimation methods and assumptions. The process of decision making in the

Estimation of precipitable water from surface dew point temperature

International Nuclear Information System (INIS)

Abdel Wahab, M.; Sharif, T.A.

1991-09-01

The Reitan (1963) regression equation which is of the form lnw=a+bT d has been examined and tested to estimate precipitable water content from surface dew point temperature at different locations. The study confirms that the slope of this equation (b) remains constant at the value of .0681 deg. C., while the intercept (a) changes rapidly with the latitude. The use of the variable intercept can improve the estimated result by 2%. (author). 6 refs, 4 figs, 3 tabs

Climate change and precipitation: Detecting changes Climate change and precipitation: Detecting changes

International Nuclear Information System (INIS)

Van Boxel, John H

2001-01-01

Precipitation is one of the most, if not the most important climate parameter In most studies on climate change the emphasis is on temperature and sea level rise. Often too little attention is given to precipitation. For a large part this is due to the large spatial en temporal variability of precipitation, which makes the detection of changes difficult. This paper describes methods to detect changes in precipitation. In order to arrive at statistically significant changes one must use long time series and spatial averages containing the information from several stations. In the Netherlands the average yearly precipitation increased by 11% during the 20th century .In the temperate latitudes on the Northern Hemisphere (40-60QN) the average increase was about 7% over the 20th century and the globally averaged precipitation increased by about 3%. During the 20th century 38% of the land surface of the earth became wetter, 42% experienced little change (less than 5% change) and 20% became dryer. More important than the average precipitation is the occurrence of extremes. In the Netherlands there is a tendency to more extreme precipitations, whereas the occurrence of relatively dry months has not changed. Also in many other countries increases in heavy precipitation events are observed. All climate models predict a further increase of mean global precipitation if the carbon dioxide concentration doubles. Nevertheless some areas get dryer, others have little change and consequently there are also areas where the increase is much more than the global average. On a regional scale however there are large differences between the models. Climate models do not yet provide adequate information on changes in extreme precipitations

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

Science.gov (United States)

Liu, Jianbo; Kummerow, Christian D.; Elsaesser, Gregory S.

2016-01-01

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

LARGE SCALE METHOD FOR THE PRODUCTION AND PURIFICATION OF CURIUM

Science.gov (United States)

Higgins, G.H.; Crane, W.W.T.

1959-05-19

A large-scale process for production and purification of Cm/sup 242/ is described. Aluminum slugs containing Am are irradiated and declad in a NaOH-- NaHO/sub 3/ solution at 85 to 100 deg C. The resulting slurry filtered and washed with NaOH, NH/sub 4/OH, and H/sub 2/O. Recovery of Cm from filtrate and washings is effected by an Fe(OH)/sub 3/ precipitation. The precipitates are then combined and dissolved ln HCl and refractory oxides centrifuged out. These oxides are then fused with Na/sub 2/CO/sub 3/ and dissolved in HCl. The solution is evaporated and LiCl solution added. The Cm, rare earths, and anionic impurities are adsorbed on a strong-base anfon exchange resin. Impurities are eluted with LiCl--HCl solution, rare earths and Cm are eluted by HCl. Other ion exchange steps further purify the Cm. The Cm is then precipitated as fluoride and used in this form or further purified and processed. (T.R.H.)

GPM Precipitation Estimates over the Walnut Gulch Experimental Watershed/LTAR site in Southeastern Arizona

Science.gov (United States)

Goodrich, D. C.; Tan, J.; Petersen, W. A.; Unkrich, C. C.; Demaria, E. M.; Hazenberg, P.; Lakshmi, V.

2017-12-01

Precipitation profiles from the GPM Core Observatory Dual-frequency Precipitation Radar (DPR) form part of the a priori database used in GPM Goddard Profiling (GPROF) algorithm passive microwave radiometer retrievals of rainfall. The GPROF retrievals are in turn used as high quality precipitation estimates in gridded products such as IMERG. Due to the variability in and high surface emissivity of land surfaces, GPROF performs precipitation retrievals as a function of surface classes. As such, different surface types may possess different error characteristics, especially over arid regions where high quality ground measurements are often lacking. Importantly, the emissive properties of land also result in GPROF rainfall estimates being driven primarily by the higher frequency radiometer channels (e.g., > 89 GHz) where precipitation signals are most sensitive to coupling between the ice-phase and rainfall production. In this study, we evaluate the rainfall estimates from the Ku channel of the DPR as well as GPROF estimates from various passive microwave sensors. Our evaluation is conducted at the level of individual satellite pixels (5 to 15 km in diameter), against a dense network of weighing rain gauges (90 in 150 km2) in the USDA-ARS Walnut Gulch Experimental Watershed and Long-Term Agroecosystem Research (LTAR) site in southeastern Arizona. The multiple gauges in each satellite pixel and precise accumulation about the overpass time allow a spatially and temporally representative comparison between the satellite estimates and ground reference. Over Walnut Gulch, both the Ku and GPROF estimates are challenged to delineate between rain and no-rain. Probabilities of detection are relatively high, but false alarm ratios are also high. The rain intensities possess a negative bias across nearly all sensors. It is likely that storm types, arid conditions and the highly variable precipitation regime present a challenge to both rainfall retrieval algorithms. An array of

Large-scale assessment of soil erosion in Africa: satellites help to jointly account for dynamic rainfall and vegetation cover

Science.gov (United States)

Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

2015-04-01

Efforts to map and monitor soil erosion need to account for the erratic nature of the soil erosion process. Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff impact soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Due to data paucity and the relative ease of spatially overlaying geographical data layers into existing models like USLE (Universal Soil Loss Equation), many studies and mapping efforts merely use average annual values for erosivity and vegetation cover as input. We first show that rainfall erosivity can be estimated from satellite precipitation data. We obtained average annual erosivity estimates from 15 yr of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Using these TMPA erosivity retrievals, we demonstrate the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. We then calculate erosivity at a 10-daily time-step and combine this with vegetation cover development for selected locations in Africa using NDVI - normalized difference vegetation index - time series from SPOT VEGETATION. Although we do not integrate the data at this point, the joint analysis of both variables stresses the need for joint accounting for erosivity and vegetation cover for large-scale erosion assessment and monitoring.

Understanding convective extreme precipitation scaling using observations and an entraining plume model

NARCIS (Netherlands)

Loriaux, J.M.; Lenderink, G.; De Roode, S.R.; Siebesma, A.P.

2013-01-01

Previously observed twice-Clausius–Clapeyron (2CC) scaling for extreme precipitation at hourly time scales has led to discussions about its origin. The robustness of this scaling is assessed by analyzing a subhourly dataset of 10-min resolution over the Netherlands. The results confirm the validity

GPS Estimates of Integrated Precipitable Water Aid Weather Forecasters

Science.gov (United States)

Moore, Angelyn W.; Gutman, Seth I.; Holub, Kirk; Bock, Yehuda; Danielson, David; Laber, Jayme; Small, Ivory

2013-01-01

Global Positioning System (GPS) meteorology provides enhanced density, low-latency (30-min resolution), integrated precipitable water (IPW) estimates to NOAA NWS (National Oceanic and Atmospheric Adminis tration Nat ional Weather Service) Weather Forecast Offices (WFOs) to provide improved model and satellite data verification capability and more accurate forecasts of extreme weather such as flooding. An early activity of this project was to increase the number of stations contributing to the NOAA Earth System Research Laboratory (ESRL) GPS meteorology observing network in Southern California by about 27 stations. Following this, the Los Angeles/Oxnard and San Diego WFOs began using the enhanced GPS-based IPW measurements provided by ESRL in the 2012 and 2013 monsoon seasons. Forecasters found GPS IPW to be an effective tool in evaluating model performance, and in monitoring monsoon development between weather model runs for improved flood forecasting. GPS stations are multi-purpose, and routine processing for position solutions also yields estimates of tropospheric zenith delays, which can be converted into mm-accuracy PWV (precipitable water vapor) using in situ pressure and temperature measurements, the basis for GPS meteorology. NOAA ESRL has implemented this concept with a nationwide distribution of more than 300 "GPSMet" stations providing IPW estimates at sub-hourly resolution currently used in operational weather models in the U.S.

Precipitation areal-reduction factor estimation using an annual-maxima centered approach

Science.gov (United States)

Asquith, W.H.; Famiglietti, J.S.

2000-01-01

The adjustment of precipitation depth of a point storm to an effective (mean) depth over a watershed is important for characterizing rainfall-runoff relations and for cost-effective designs of hydraulic structures when design storms are considered. A design storm is the precipitation point depth having a specified duration and frequency (recurrence interval). Effective depths are often computed by multiplying point depths by areal-reduction factors (ARF). ARF range from 0 to 1, vary according to storm characteristics, such as recurrence interval; and are a function of watershed characteristics, such as watershed size, shape, and geographic location. This paper presents a new approach for estimating ARF and includes applications for the 1-day design storm in Austin, Dallas, and Houston, Texas. The approach, termed 'annual-maxima centered,' specifically considers the distribution of concurrent precipitation surrounding an annual-precipitation maxima, which is a feature not seen in other approaches. The approach does not require the prior spatial averaging of precipitation, explicit determination of spatial correlation coefficients, nor explicit definition of a representative area of a particular storm in the analysis. The annual-maxima centered approach was designed to exploit the wide availability of dense precipitation gauge data in many regions of the world. The approach produces ARF that decrease more rapidly than those from TP-29. Furthermore, the ARF from the approach decay rapidly with increasing recurrence interval of the annual-precipitation maxima. (C) 2000 Elsevier Science B.V.The adjustment of precipitation depth of a point storm to an effective (mean) depth over a watershed is important for characterizing rainfall-runoff relations and for cost-effective designs of hydraulic structures when design storms are considered. A design storm is the precipitation point depth having a specified duration and frequency (recurrence interval). Effective depths are

Towards Large-area Field-scale Operational Evapotranspiration for Water Use Mapping

Science.gov (United States)

Senay, G. B.; Friedrichs, M.; Morton, C.; Huntington, J. L.; Verdin, J.

2017-12-01

Field-scale evapotranspiration (ET) estimates are needed for improving surface and groundwater use and water budget studies. Ideally, field-scale ET estimates would be at regional to national levels and cover long time periods. As a result of large data storage and computational requirements associated with processing field-scale satellite imagery such as Landsat, numerous challenges remain to develop operational ET estimates over large areas for detailed water use and availability studies. However, the combination of new science, data availability, and cloud computing technology is enabling unprecedented capabilities for ET mapping. To demonstrate this capability, we used Google's Earth Engine cloud computing platform to create nationwide annual ET estimates with 30-meter resolution Landsat ( 16,000 images) and gridded weather data using the Operational Simplified Surface Energy Balance (SSEBop) model in support of the National Water Census, a USGS research program designed to build decision support capacity for water management agencies and other natural resource managers. By leveraging Google's Earth Engine Application Programming Interface (API) and developing software in a collaborative, open-platform environment, we rapidly advance from research towards applications for large-area field-scale ET mapping. Cloud computing of the Landsat image archive combined with other satellite, climate, and weather data, is creating never imagined opportunities for assessing ET model behavior and uncertainty, and ultimately providing the ability for more robust operational monitoring and assessment of water use at field-scales.

Precipitation Analysis at Fine Time Scales using TRMM and Other Satellites: Real-time and Research Products and Applications

Science.gov (United States)

Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold; Gu, Guo-Jon

2004-01-01

Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the TRMM Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) by the end of 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O0N-50"S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, includmg: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

Large-scale Estimates of Leaf Area Index from Active Remote Sensing Laser Altimetry

Science.gov (United States)

Hopkinson, C.; Mahoney, C.

2016-12-01

Leaf area index (LAI) is a key parameter that describes the spatial distribution of foliage within forest canopies which in turn control numerous relationships between the ground, canopy, and atmosphere. The retrieval of LAI has demonstrated success by in-situ (digital) hemispherical photography (DHP) and airborne laser scanning (ALS) data; however, field and ALS acquisitions are often spatially limited (100's km2) and costly. Large-scale (>1000's km2) retrievals have been demonstrated by optical sensors, however, accuracies remain uncertain due to the sensor's inability to penetrate the canopy. The spaceborne Geoscience Laser Altimeter System (GLAS) provides a possible solution in retrieving large-scale derivations whilst simultaneously penetrating the canopy. LAI retrieved by multiple DHP from 6 Australian sites, representing a cross-section of Australian ecosystems, were employed to model ALS LAI, which in turn were used to infer LAI from GLAS data at 5 other sites. An optimally filtered GLAS dataset was then employed in conjunction with a host of supplementary data to build a Random Forest (RF) model to infer predictions (and uncertainties) of LAI at a 250 m resolution across the forested regions of Australia. Predictions were validated against ALS-based LAI from 20 sites (R2=0.64, RMSE=1.1 m2m-2); MODIS-based LAI were also assessed against these sites (R2=0.30, RMSE=1.78 m2m-2) to demonstrate the strength of GLAS-based predictions. The large-scale nature of current predictions was also leveraged to demonstrate large-scale relationships of LAI with other environmental characteristics, such as: canopy height, elevation, and slope. The need for such wide-scale quantification of LAI is key in the assessment and modification of forest management strategies across Australia. Such work also assists Australia's Terrestrial Ecosystem Research Network, in fulfilling their government issued mandates.

Estimation of the characteristic energy of electron precipitation

Directory of Open Access Journals (Sweden)

C. F. del Pozo

2002-09-01

Full Text Available Data from simultaneous observations (on 13 February 1996, 9 November 1998, and 12 February 1999 with the IRIS, DASI and EISCAT systems are employed in the study of the energy distribution of the electron precipitation during substorm activity. The estimation of the characteristic energy of the electron precipitation over the common field of view of IRIS and DASI is discussed. In particular, we look closely at the physical basis of the correspondence between the characteristic energy, the flux-averaged energy, as defined below, and the logarithm of the ratio of the green-light intensity to the square of absorption. This study expands and corrects results presented in the paper by Kosch et al. (2001. It is noticed, moreover, that acceleration associated with diffusion processes in the magnetosphere long before precipitation may be controlling the shape of the energy spectrum. We propose and test a "mixed" distribution for the energy-flux spectrum, exponential at the lower energies and Maxwellian or modified power-law at the higher energies, with a threshold energy separating these two regimes. The energy-flux spectrum at Tromsø, in the 1–320 keV range, is derived from EISCAT electron density profiles in the 70–140 km altitude range and is applied in the "calibration" of the optical intensity and absorption distributions, in order to extrapolate the flux and characteristic energy maps.Key words. Ionosphere (auroral ionosphere; particle precipitation; particle acceleration

Estimation of the characteristic energy of electron precipitation

Directory of Open Access Journals (Sweden)

C. F. del Pozo

Full Text Available Data from simultaneous observations (on 13 February 1996, 9 November 1998, and 12 February 1999 with the IRIS, DASI and EISCAT systems are employed in the study of the energy distribution of the electron precipitation during substorm activity. The estimation of the characteristic energy of the electron precipitation over the common field of view of IRIS and DASI is discussed. In particular, we look closely at the physical basis of the correspondence between the characteristic energy, the flux-averaged energy, as defined below, and the logarithm of the ratio of the green-light intensity to the square of absorption. This study expands and corrects results presented in the paper by Kosch et al. (2001. It is noticed, moreover, that acceleration associated with diffusion processes in the magnetosphere long before precipitation may be controlling the shape of the energy spectrum. We propose and test a "mixed" distribution for the energy-flux spectrum, exponential at the lower energies and Maxwellian or modified power-law at the higher energies, with a threshold energy separating these two regimes. The energy-flux spectrum at Tromsø, in the 1–320 keV range, is derived from EISCAT electron density profiles in the 70–140 km altitude range and is applied in the "calibration" of the optical intensity and absorption distributions, in order to extrapolate the flux and characteristic energy maps.

Key words. Ionosphere (auroral ionosphere; particle precipitation; particle acceleration

Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model

Directory of Open Access Journals (Sweden)

Yuqi Guo

2017-08-01

Full Text Available In order to estimate traffic densities in a large-scale urban freeway network in an accurate and timely fashion when traffic sensors do not cover the freeway network completely and thus only local measurement data can be utilized, this paper proposes a decentralized state observer approach based on a macroscopic traffic flow model. Firstly, by using the well-known cell transmission model (CTM, the urban freeway network is modeled in the way of distributed systems. Secondly, based on the model, a decentralized observer is designed. With the help of the Lyapunov function and S-procedure theory, the observer gains are computed by using linear matrix inequality (LMI technique. So, the traffic densities of the whole road network can be estimated by the designed observer. Finally, this method is applied to the outer ring of the Beijing’s second ring road and experimental results demonstrate the effectiveness and applicability of the proposed approach.

REAL - Ensemble radar precipitation estimation for hydrology in a mountainous region

OpenAIRE

Germann, Urs; Berenguer Ferrer, Marc; Sempere Torres, Daniel; Zappa, Massimiliano

2009-01-01

An elegant solution to characterise the residual errors in radar precipitation estimates is to generate an ensemble of precipitation fields. The paper proposes a radar ensemble generator designed for usage in the Alps using LU decomposition (REAL), and presents first results from a real-time implementation coupling the radar ensemble with a semi-distributed rainfall–runoff model for flash flood modelling in a steep Alpine catchment. Each member of the radar ensemble is a possible realisati...

The estimation of probable maximum precipitation: the case of Catalonia.

Science.gov (United States)

Casas, M Carmen; Rodríguez, Raül; Nieto, Raquel; Redaño, Angel

2008-12-01

A brief overview of the different techniques used to estimate the probable maximum precipitation (PMP) is presented. As a particular case, the 1-day PMP over Catalonia has been calculated and mapped with a high spatial resolution. For this purpose, the annual maximum daily rainfall series from 145 pluviometric stations of the Instituto Nacional de Meteorología (Spanish Weather Service) in Catalonia have been analyzed. In order to obtain values of PMP, an enveloping frequency factor curve based on the actual rainfall data of stations in the region has been developed. This enveloping curve has been used to estimate 1-day PMP values of all the 145 stations. Applying the Cressman method, the spatial analysis of these values has been achieved. Monthly precipitation climatological data, obtained from the application of Geographic Information Systems techniques, have been used as the initial field for the analysis. The 1-day PMP at 1 km(2) spatial resolution over Catalonia has been objectively determined, varying from 200 to 550 mm. Structures with wavelength longer than approximately 35 km can be identified and, despite their general concordance, the obtained 1-day PMP spatial distribution shows remarkable differences compared to the annual mean precipitation arrangement over Catalonia.

The Regional Differences of Gpp Estimation by Solar Induced Fluorescence

Science.gov (United States)

Wang, X.; Lu, S.

2018-04-01

Estimating gross primary productivity (GPP) at large spatial scales is important for studying the global carbon cycle and global climate change. In this study, the relationship between solar-induced chlorophyll fluorescence (SIF) and GPP is analysed in different levels of annual average temperature and annual total precipitation respectively using simple linear regression analysis. The results showed high correlation between SIF and GPP, when the area satisfied annual average temperature in the range of -5 °C to 15 °C and the annual total precipitation is higher than 200 mm. These results can provide a basis for future estimation of GPP research.

Storm induced large scale TIDs observed in GPS derived TEC

Directory of Open Access Journals (Sweden)

C. Borries

2009-04-01

Full Text Available This work is a first statistical analysis of large scale traveling ionospheric disturbances (LSTID in Europe using total electron content (TEC data derived from GNSS measurements. The GNSS receiver network in Europe is dense enough to map the ionospheric perturbation TEC with high horizontal resolution. The derived perturbation TEC maps are analysed studying the effect of space weather events on the ionosphere over Europe. Equatorward propagating storm induced wave packets have been identified during several geomagnetic storms. Characteristic parameters such as velocity, wavelength and direction were estimated from the perturbation TEC maps. Showing a mean wavelength of 2000 km, a mean period of 59 min and a phase speed of 684 ms−1 in average, the perturbations are allocated to LSTID. The comparison to LSTID observed over Japan shows an equal wavelength but a considerably faster phase speed. This might be attributed to the differences in the distance to the auroral region or inclination/declination of the geomagnetic field lines. The observed correlation between the LSTID amplitudes and the Auroral Electrojet (AE indicates that most of the wave like perturbations are exited by Joule heating. Particle precipitation effects could not be separated.

Radar rainfall estimation of stratiform winter precipitation in the Belgian Ardennes

Science.gov (United States)

Hazenberg, P.; Leijnse, H.; Uijlenhoet, R.

2011-02-01

Radars are known for their ability to obtain a wealth of information about spatial storm field characteristics. Unfortunately, rainfall estimates obtained by this instrument are known to be affected by multiple sources of error. Especially for stratiform precipitation systems, the quality of radar rainfall estimates starts to decrease at relatively close ranges. In the current study, the hydrological potential of weather radar is analyzed during a winter half-year for the hilly region of the Belgian Ardennes. A correction algorithm is proposed which corrects the radar data for errors related to attenuation, ground clutter, anomalous propagation, the vertical profile of reflectivity (VPR), and advection. No final bias correction with respect to rain gauge data was implemented because such an adjustment would not add to a better understanding of the quality of the radar data. The impact of the different corrections is assessed using rainfall information sampled by 42 hourly rain gauges. The largest improvement in the quality of the radar data is obtained by correcting for ground clutter. The impact of VPR correction and advection depends on the spatial variability and velocity of the precipitation system. Overall during the winter period, the radar underestimates the amount of precipitation as compared to the rain gauges. Remaining differences between both instruments can be attributed to spatial and temporal variability in the type of precipitation, which has not been taken into account.

Application of Statistical Methods of Rain Rate Estimation to Data From The TRMM Precipitation Radar

Science.gov (United States)

Meneghini, R.; Jones, J. A.; Iguchi, T.; Okamoto, K.; Liao, L.; Busalacchi, Antonio J. (Technical Monitor)

2000-01-01

The TRMM Precipitation Radar is well suited to statistical methods in that the measurements over any given region are sparsely sampled in time. Moreover, the instantaneous rain rate estimates are often of limited accuracy at high rain rates because of attenuation effects and at light rain rates because of receiver sensitivity. For the estimation of the time-averaged rain characteristics over an area both errors are relevant. By enlarging the space-time region over which the data are collected, the sampling error can be reduced. However. the bias and distortion of the estimated rain distribution generally will remain if estimates at the high and low rain rates are not corrected. In this paper we use the TRMM PR data to investigate the behavior of 2 statistical methods the purpose of which is to estimate the rain rate over large space-time domains. Examination of large-scale rain characteristics provides a useful starting point. The high correlation between the mean and standard deviation of rain rate implies that the conditional distribution of this quantity can be approximated by a one-parameter distribution. This property is used to explore the behavior of the area-time-integral (ATI) methods where fractional area above a threshold is related to the mean rain rate. In the usual application of the ATI method a correlation is established between these quantities. However, if a particular form of the rain rate distribution is assumed and if the ratio of the mean to standard deviation is known, then not only the mean but the full distribution can be extracted from a measurement of fractional area above a threshold. The second method is an extension of this idea where the distribution is estimated from data over a range of rain rates chosen in an intermediate range where the effects of attenuation and poor sensitivity can be neglected. The advantage of estimating the distribution itself rather than the mean value is that it yields the fraction of rain contributed by

Modeling Student Motivation and Students’ Ability Estimates From a Large-Scale Assessment of Mathematics

Directory of Open Access Journals (Sweden)

Carlos Zerpa

2011-09-01

Full Text Available When large-scale assessments (LSA do not hold personal stakes for students, students may not put forth their best effort. Low-effort examinee behaviors (e.g., guessing, omitting items result in an underestimate of examinee abilities, which is a concern when using results of LSA to inform educational policy and planning. The purpose of this study was to explore the relationship between examinee motivation as defined by expectancy-value theory, student effort, and examinee mathematics abilities. A principal components analysis was used to examine the data from Grade 9 students (n = 43,562 who responded to a self-report questionnaire on their attitudes and practices related to mathematics. The results suggested a two-component model where the components were interpreted as task-values in mathematics and student effort. Next, a hierarchical linear model was implemented to examine the relationship between examinee component scores and their estimated ability on a LSA. The results of this study provide evidence that motivation, as defined by the expectancy-value theory and student effort, partially explains student ability estimates and may have implications in the information that get transferred to testing organizations, school boards, and teachers while assessing students’ Grade 9 mathematics learning.

Extreme weather events in southern Germany - Climatological risk and development of a large-scale identification procedure

Science.gov (United States)

Matthies, A.; Leckebusch, G. C.; Rohlfing, G.; Ulbrich, U.

2009-04-01

Extreme weather events such as thunderstorms, hail and heavy rain or snowfall can pose a threat to human life and to considerable tangible assets. Yet there is a lack of knowledge about present day climatological risk and its economic effects, and its changes due to rising greenhouse gas concentrations. Therefore, parts of economy particularly sensitve to extreme weather events such as insurance companies and airports require regional risk-analyses, early warning and prediction systems to cope with such events. Such an attempt is made for southern Germany, in close cooperation with stakeholders. Comparing ERA40 and station data with impact records of Munich Re and Munich Airport, the 90th percentile was found to be a suitable threshold for extreme impact relevant precipitation events. Different methods for the classification of causing synoptic situations have been tested on ERA40 reanalyses. An objective scheme for the classification of Lamb's circulation weather types (CWT's) has proved to be most suitable for correct classification of the large-scale flow conditions. Certain CWT's have been turned out to be prone to heavy precipitation or on the other side to have a very low risk of such events. Other large-scale parameters are tested in connection with CWT's to find out a combination that has the highest skill to identify extreme precipitation events in climate model data (ECHAM5 and CLM). For example vorticity advection in 700 hPa shows good results, but assumes knowledge of regional orographic particularities. Therefore ongoing work is focused on additional testing of parameters that indicate deviations of a basic state of the atmosphere like the Eady Growth Rate or the newly developed Dynamic State Index. Evaluation results will be used to estimate the skill of the regional climate model CLM concerning the simulation of frequency and intensity of the extreme weather events. Data of the A1B scenario (2000-2050) will be examined for a possible climate change

Understanding dynamics of large-scale atmospheric vortices with moist-convective shallow water model

International Nuclear Information System (INIS)

Rostami, M.; Zeitlin, V.

2016-01-01

Atmospheric jets and vortices which, together with inertia-gravity waves, constitute the principal dynamical entities of large-scale atmospheric motions, are well described in the framework of one- or multi-layer rotating shallow water models, which are obtained by vertically averaging of full “primitive” equations. There is a simple and physically consistent way to include moist convection in these models by adding a relaxational parameterization of precipitation and coupling precipitation with convective fluxes with the help of moist enthalpy conservation. We recall the construction of moist-convective rotating shallow water model (mcRSW) model and give an example of application to upper-layer atmospheric vortices. (paper)

Intercomparison of PERSIANN-CDR and TRMM-3B42V7 precipitation estimates at monthly and daily time scales

Science.gov (United States)

Katiraie-Boroujerdy, Pari-Sima; Akbari Asanjan, Ata; Hsu, Kuo-lin; Sorooshian, Soroosh

2017-09-01

In the first part of this paper, monthly precipitation data from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission 3B42 algorithm Version 7 (TRMM-3B42V7) are evaluated over Iran using the Generalized Three-Cornered Hat (GTCH) method which is self-sufficient of reference data as input. Climate Data Unit (CRU) is added to the GTCH evaluations as an independent gauge-based dataset thus, the minimum requirement of three datasets for the model is satisfied. To ensure consistency of all datasets, the two satellite products were aggregated to 0.5° spatial resolution, which is the minimum resolution of CRU. The results show that the PERSIANN-CDR has higher Signal to Noise Ratio (SNR) than TRMM-3B42V7 for the monthly rainfall estimation, especially in the northern half of the country. All datasets showed low SNR in the mountainous area of southwestern Iran, as well as the arid parts in the southeast region of the country. Additionally, in order to evaluate the efficacy of PERSIANN-CDR and TRMM-3B42V7 in capturing extreme daily-precipitation amounts, an in-situ rain-gauge dataset collected by the Islamic Republic of the Iran Meteorological Organization (IRIMO) was employed. Given the sparsity of the rain gauges, only 0.25° pixels containing three or more gauges were used for this evaluation. There were 228 such pixels where daily and extreme rainfall from PERSIANN-CDR and TRMM-3B42V7 could be compared. However, TRMM-3B42V7 overestimates most of the intensity indices (correlation coefficients; R between 0.7648-0.8311, Root Mean Square Error; RMSE between 3.29mm/day-21.2mm/5day); PERSIANN-CDR underestimates these extremes (R between 0.6349-0.7791 and RMSE between 3.59mm/day-30.56mm/5day). Both satellite products show higher correlation coefficients and lower RMSEs for the annual mean of consecutive dry spells than wet spells. The results show that TRMM-3B42V7

Maximum likely scale estimation

DEFF Research Database (Denmark)

Loog, Marco; Pedersen, Kim Steenstrup; Markussen, Bo

2005-01-01

A maximum likelihood local scale estimation principle is presented. An actual implementation of the estimation principle uses second order moments of multiple measurements at a fixed location in the image. These measurements consist of Gaussian derivatives possibly taken at several scales and/or ...

Dose monitoring in large-scale flowing aqueous media

International Nuclear Information System (INIS)

Kuruca, C.N.

1995-01-01

The Miami Electron Beam Research Facility (EBRF) has been in operation for six years. The EBRF houses a 1.5 MV, 75 KW DC scanned electron beam. Experiments have been conducted to evaluate the effectiveness of high-energy electron irradiation in the removal of toxic organic chemicals from contaminated water and the disinfection of various wastewater streams. The large-scale plant operates at approximately 450 L/min (120 gal/min). The radiation dose absorbed by the flowing aqueous streams is estimated by measuring the difference in water temperature before and after it passes in front of the beam. Temperature measurements are made using resistance temperature devices (RTDs) and recorded by computer along with other operating parameters. Estimated dose is obtained from the measured temperature differences using the specific heat of water. This presentation will discuss experience with this measurement system, its application to different water presentation devices, sources of error, and the advantages and disadvantages of its use in large-scale process applications

Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

Science.gov (United States)

Mortensen, Eric; Wu, Shu; Notaro, Michael; Vavrus, Stephen; Montgomery, Rob; De Piérola, José; Sánchez, Carlos; Block, Paul

2018-01-01

Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet-dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought.

Extreme daily precipitation in Western Europe with climate change at appropriate spatial scales

NARCIS (Netherlands)

Booij, Martijn J.

2002-01-01

Extreme daily precipitation for the current and changed climate at appropriate spatial scales is assessed. This is done in the context of the impact of climate change on flooding in the river Meuse in Western Europe. The objective is achieved by determining and comparing extreme precipitation from

Large-scale solar purchasing

International Nuclear Information System (INIS)

1999-01-01

The principal objective of the project was to participate in the definition of a new IEA task concerning solar procurement (''the Task'') and to assess whether involvement in the task would be in the interest of the UK active solar heating industry. The project also aimed to assess the importance of large scale solar purchasing to UK active solar heating market development and to evaluate the level of interest in large scale solar purchasing amongst potential large scale purchasers (in particular housing associations and housing developers). A further aim of the project was to consider means of stimulating large scale active solar heating purchasing activity within the UK. (author)

Improving Estimation of Betweenness Centrality for Scale-Free Graphs

Energy Technology Data Exchange (ETDEWEB)

Bromberger, Seth A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Klymko, Christine F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Henderson, Keith A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pearce, Roger [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sanders, Geoff [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-11-07

Betweenness centrality is a graph statistic used to nd vertices that are participants in a large number of shortest paths in a graph. This centrality measure is commonly used in path and network interdiction problems and its complete form requires the calculation of all-pairs shortest paths for each vertex. This leads to a time complexity of O(jV jjEj), which is impractical for large graphs. Estimation of betweenness centrality has focused on performing shortest-path calculations on a subset of randomly- selected vertices. This reduces the complexity of the centrality estimation to O(jSjjEj); jSj < jV j, which can be scaled appropriately based on the computing resources available. An estimation strategy that uses random selection of vertices for seed selection is fast and simple to implement, but may not provide optimal estimation of betweenness centrality when the number of samples is constrained. Our experimentation has identi ed a number of alternate seed-selection strategies that provide lower error than random selection in common scale-free graphs. These strategies are discussed and experimental results are presented.

European Wintertime Windstorms and its Links to Large-Scale Variability Modes

Science.gov (United States)

Befort, D. J.; Wild, S.; Walz, M. A.; Knight, J. R.; Lockwood, J. F.; Thornton, H. E.; Hermanson, L.; Bett, P.; Weisheimer, A.; Leckebusch, G. C.

2017-12-01

Winter storms associated with extreme wind speeds and heavy precipitation are the most costly natural hazard in several European countries. Improved understanding and seasonal forecast skill of winter storms will thus help society, policy-makers and (re-) insurance industry to be better prepared for such events. We firstly assess the ability to represent extra-tropical windstorms over the Northern Hemisphere of three seasonal forecast ensemble suites: ECMWF System3, ECMWF System4 and GloSea5. Our results show significant skill for inter-annual variability of windstorm frequency over parts of Europe in two of these forecast suites (ECMWF-S4 and GloSea5) indicating the potential use of current seasonal forecast systems. In a regression model we further derive windstorm variability using the forecasted NAO from the seasonal model suites thus estimating the suitability of the NAO as the only predictor. We find that the NAO as the main large-scale mode over Europe can explain some of the achieved skill and is therefore an important source of variability in the seasonal models. However, our results show that the regression model fails to reproduce the skill level of the directly forecast windstorm frequency over large areas of central Europe. This suggests that the seasonal models also capture other sources of variability/predictability of windstorms than the NAO. In order to investigate which other large-scale variability modes steer the interannual variability of windstorms we develop a statistical model using a Poisson GLM. We find that the Scandinavian Pattern (SCA) in fact explains a larger amount of variability for Central Europe during the 20th century than the NAO. This statistical model is able to skilfully reproduce the interannual variability of windstorm frequency especially for the British Isles and Central Europe with correlations up to 0.8.

Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France

Science.gov (United States)

Caillouet, Laurie; Vidal, Jean-Philippe; Sauquet, Eric; Graff, Benjamin

2016-03-01

This work proposes a daily high-resolution probabilistic reconstruction of precipitation and temperature fields in France over the 1871-2012 period built on the NOAA Twentieth Century global extended atmospheric reanalysis (20CR). The objective is to fill in the spatial and temporal data gaps in surface observations in order to improve our knowledge on the local-scale climate variability from the late nineteenth century onwards. The SANDHY (Stepwise ANalogue Downscaling method for HYdrology) statistical downscaling method, initially developed for quantitative precipitation forecast, is used here to bridge the scale gap between large-scale 20CR predictors and local-scale predictands from the Safran high-resolution near-surface reanalysis, available from 1958 onwards only. SANDHY provides a daily ensemble of 125 analogue dates over the 1871-2012 period for 608 climatically homogeneous zones paving France. Large precipitation biases in intermediary seasons are shown to occur in regions with high seasonal asymmetry like the Mediterranean. Moreover, winter and summer temperatures are respectively over- and under-estimated over the whole of France. Two analogue subselection methods are therefore developed with the aim of keeping the structure of the SANDHY method unchanged while reducing those seasonal biases. The calendar selection keeps the analogues closest to the target calendar day. The stepwise selection applies two new analogy steps based on similarity of the sea surface temperature (SST) and the large-scale 2 m temperature (T). Comparisons to the Safran reanalysis over 1959-2007 and to homogenized series over the whole twentieth century show that biases in the interannual cycle of precipitation and temperature are reduced with both methods. The stepwise subselection moreover leads to a large improvement of interannual correlation and reduction of errors in seasonal temperature time series. When the calendar subselection is an easily applicable method suitable in

Evaluating Uncertainties in Sap Flux Scaled Estimates of Forest Transpiration, Canopy Conductance and Photosynthesis

Science.gov (United States)

Ward, E. J.; Bell, D. M.; Clark, J. S.; Kim, H.; Oren, R.

2009-12-01

Thermal dissipation probes (TDPs) are a common method for estimating forest transpiration and canopy conductance from sap flux rates in trees, but their implementation is plagued by uncertainties arising from missing data and variability in the diameter and canopy position of trees, as well as sapwood conductivity within individual trees. Uncertainties in estimates of canopy conductance also translate into uncertainties in carbon assimilation in models such as the Canopy Conductance Constrained Carbon Assimilation (4CA) model that combine physiological and environmental data to estimate photosynthetic rates. We developed a method to propagate these uncertainties in the scaling and imputation of TDP data to estimates of canopy transpiration and conductance using a state-space Jarvis-type conductance model in a hierarchical Bayesian framework. This presentation will focus on the impact of these uncertainties on estimates of water and carbon fluxes using 4CA and data from the Duke Free Air Carbon Enrichment (FACE) project, which incorporates both elevated carbon dioxide and soil nitrogen treatments. We will also address the response of canopy conductance to vapor pressure deficit, incident radiation and soil moisture, as well as the effect of treatment-related stand structure differences in scaling TDP measurements. Preliminary results indicate that in 2006, a year of normal precipitation (1127 mm), canopy transpiration increased in elevated carbon dioxide ~8% on a ground area basis. In 2007, a year with a pronounced drought (800 mm precipitation), this increase was only present in the combined carbon dioxide and fertilization treatment. The seasonal dynamics of water and carbon fluxes will be discussed in detail.

A Stream Tilling Approach to Surface Area Estimation for Large Scale Spatial Data in a Shared Memory System

Directory of Open Access Journals (Sweden)

Liu Jiping

2017-12-01

Full Text Available Surface area estimation is a widely used tool for resource evaluation in the physical world. When processing large scale spatial data, the input/output (I/O can easily become the bottleneck in parallelizing the algorithm due to the limited physical memory resources and the very slow disk transfer rate. In this paper, we proposed a stream tilling approach to surface area estimation that first decomposed a spatial data set into tiles with topological expansions. With these tiles, the one-to-one mapping relationship between the input and the computing process was broken. Then, we realized a streaming framework towards the scheduling of the I/O processes and computing units. Herein, each computing unit encapsulated a same copy of the estimation algorithm, and multiple asynchronous computing units could work individually in parallel. Finally, the performed experiment demonstrated that our stream tilling estimation can efficiently alleviate the heavy pressures from the I/O-bound work, and the measured speedup after being optimized have greatly outperformed the directly parallel versions in shared memory systems with multi-core processors.

Sample preparation for large-scale bioanalytical studies based on liquid chromatographic techniques.

Science.gov (United States)

Medvedovici, Andrei; Bacalum, Elena; David, Victor

2018-01-01

Quality of the analytical data obtained for large-scale and long term bioanalytical studies based on liquid chromatography depends on a number of experimental factors including the choice of sample preparation method. This review discusses this tedious part of bioanalytical studies, applied to large-scale samples and using liquid chromatography coupled with different detector types as core analytical technique. The main sample preparation methods included in this paper are protein precipitation, liquid-liquid extraction, solid-phase extraction, derivatization and their versions. They are discussed by analytical performances, fields of applications, advantages and disadvantages. The cited literature covers mainly the analytical achievements during the last decade, although several previous papers became more valuable in time and they are included in this review. Copyright © 2017 John Wiley & Sons, Ltd.

Impacts of large-scale climatic disturbances on the terrestrial carbon cycle

Directory of Open Access Journals (Sweden)

Lucht Wolfgang

2006-07-01

Full Text Available Abstract Background The amount of carbon dioxide in the atmosphere steadily increases as a consequence of anthropogenic emissions but with large interannual variability caused by the terrestrial biosphere. These variations in the CO2 growth rate are caused by large-scale climate anomalies but the relative contributions of vegetation growth and soil decomposition is uncertain. We use a biogeochemical model of the terrestrial biosphere to differentiate the effects of temperature and precipitation on net primary production (NPP and heterotrophic respiration (Rh during the two largest anomalies in atmospheric CO2 increase during the last 25 years. One of these, the smallest atmospheric year-to-year increase (largest land carbon uptake in that period, was caused by global cooling in 1992/93 after the Pinatubo volcanic eruption. The other, the largest atmospheric increase on record (largest land carbon release, was caused by the strong El Niño event of 1997/98. Results We find that the LPJ model correctly simulates the magnitude of terrestrial modulation of atmospheric carbon anomalies for these two extreme disturbances. The response of soil respiration to changes in temperature and precipitation explains most of the modelled anomalous CO2 flux. Conclusion Observed and modelled NEE anomalies are in good agreement, therefore we suggest that the temporal variability of heterotrophic respiration produced by our model is reasonably realistic. We therefore conclude that during the last 25 years the two largest disturbances of the global carbon cycle were strongly controlled by soil processes rather then the response of vegetation to these large-scale climatic events.

Responses of Cloud Type Distributions to the Large-Scale Dynamical Circulation: Water Budget-Related Dynamical Phase Space and Dynamical Regimes

Science.gov (United States)

Wong, Sun; Del Genio, Anthony; Wang, Tao; Kahn, Brian; Fetzer, Eric J.; L'Ecuyer, Tristan S.

2015-01-01

Goals: Water budget-related dynamical phase space; Connect large-scale dynamical conditions to atmospheric water budget (including precipitation); Connect atmospheric water budget to cloud type distributions.

Sensitivity of extreme precipitation to temperature: the variability of scaling factors from a regional to local perspective

Science.gov (United States)

Schroeer, K.; Kirchengast, G.

2018-06-01

Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale.

Regional Scale High Resolution δ18O Prediction in Precipitation Using MODIS EVI

Science.gov (United States)

Huang, Cho-Ying; Wang, Chung-Ho; Lin, Shou-De; Lo, Yi-Chen; Huang, Bo-Wen; Hatch, Kent A.; Shiu, Hau-Jie; You, Cheng-Feng; Chang, Yuan-Mou; Shen, Sheng-Feng

2012-01-01

The natural variation in stable water isotope ratio data, also known as water isoscape, is a spatiotemporal fingerprint and a powerful natural tracer that has been widely applied in disciplines as diverse as hydrology, paleoclimatology, ecology and forensic investigation. Although much effort has been devoted to developing a predictive water isoscape model, it remains a central challenge for scientists to generate high accuracy, fine scale spatiotemporal water isoscape prediction. Here we develop a novel approach of using the MODIS-EVI (the Moderate Resolution Imagining Spectroradiometer-Enhanced Vegetation Index), to predict δ18O in precipitation at the regional scale. Using a structural equation model, we show that the EVI and precipitated δ18O are highly correlated and thus the EVI is a good predictor of precipitated δ18O. We then test the predictability of our EVI-δ18O model and demonstrate that our approach can provide high accuracy with fine spatial (250×250 m) and temporal (16 days) scale δ18O predictions (annual and monthly predictabilities [r] are 0.96 and 0.80, respectively). We conclude the merging of the EVI and δ18O in precipitation can greatly extend the spatial and temporal data availability and thus enhance the applicability for both the EVI and water isoscape. PMID:23029053

The nonstationary impact of local temperature changes and ENSO on extreme precipitation at the global scale

Science.gov (United States)

Sun, Qiaohong; Miao, Chiyuan; Qiao, Yuanyuan; Duan, Qingyun

2017-12-01

The El Niño-Southern Oscillation (ENSO) and local temperature are important drivers of extreme precipitation. Understanding the impact of ENSO and temperature on the risk of extreme precipitation over global land will provide a foundation for risk assessment and climate-adaptive design of infrastructure in a changing climate. In this study, nonstationary generalized extreme value distributions were used to model extreme precipitation over global land for the period 1979-2015, with ENSO indicator and temperature as covariates. Risk factors were estimated to quantify the contrast between the influence of different ENSO phases and temperature. The results show that extreme precipitation is dominated by ENSO over 22% of global land and by temperature over 26% of global land. With a warming climate, the risk of high-intensity daily extreme precipitation increases at high latitudes but decreases in tropical regions. For ENSO, large parts of North America, southern South America, and southeastern and northeastern China are shown to suffer greater risk in El Niño years, with more than double the chance of intense extreme precipitation in El Niño years compared with La Niña years. Moreover, regions with more intense precipitation are more sensitive to ENSO. Global climate models were used to investigate the changing relationship between extreme precipitation and the covariates. The risk of extreme, high-intensity precipitation increases across high latitudes of the Northern Hemisphere but decreases in middle and lower latitudes under a warming climate scenario, and will likely trigger increases in severe flooding and droughts across the globe. However, there is some uncertainties associated with the influence of ENSO on predictions of future extreme precipitation, with the spatial extent and risk varying among the different models.

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

Science.gov (United States)

Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant

Expanded Large-Scale Forcing Properties Derived from the Multiscale Data Assimilation System and Its Application to Single-Column Models

Science.gov (United States)

Feng, S.; Li, Z.; Liu, Y.; Lin, W.; Toto, T.; Vogelmann, A. M.; Fridlind, A. M.

2013-12-01

We present an approach to derive large-scale forcing that is used to drive single-column models (SCMs) and cloud resolving models (CRMs)/large eddy simulation (LES) for evaluating fast physics parameterizations in climate models. The forcing fields are derived by use of a newly developed multi-scale data assimilation (MS-DA) system. This DA system is developed on top of the NCEP Gridpoint Statistical Interpolation (GSI) System and is implemented in the Weather Research and Forecasting (WRF) model at a cloud resolving resolution of 2 km. This approach has been applied to the generation of large scale forcing for a set of Intensive Operation Periods (IOPs) over the Atmospheric Radiation Measurement (ARM) Climate Research Facility's Southern Great Plains (SGP) site. The dense ARM in-situ observations and high-resolution satellite data effectively constrain the WRF model. The evaluation shows that the derived forcing displays accuracies comparable to the existing continuous forcing product and, overall, a better dynamic consistency with observed cloud and precipitation. One important application of this approach is to derive large-scale hydrometeor forcing and multiscale forcing, which is not provided in the existing continuous forcing product. It is shown that the hydrometeor forcing poses an appreciable impact on cloud and precipitation fields in the single-column model simulations. The large-scale forcing exhibits a significant dependency on domain-size that represents SCM grid-sizes. Subgrid processes often contribute a significant component to the large-scale forcing, and this contribution is sensitive to the grid-size and cloud-regime.

Real-Time Large Scale 3d Reconstruction by Fusing Kinect and Imu Data

Science.gov (United States)

Huai, J.; Zhang, Y.; Yilmaz, A.

2015-08-01

Kinect-style RGB-D cameras have been used to build large scale dense 3D maps for indoor environments. These maps can serve many purposes such as robot navigation, and augmented reality. However, to generate dense 3D maps of large scale environments is still very challenging. In this paper, we present a mapping system for 3D reconstruction that fuses measurements from a Kinect and an inertial measurement unit (IMU) to estimate motion. Our major achievements include: (i) Large scale consistent 3D reconstruction is realized by volume shifting and loop closure; (ii) The coarse-to-fine iterative closest point (ICP) algorithm, the SIFT odometry, and IMU odometry are combined to robustly and precisely estimate pose. In particular, ICP runs routinely to track the Kinect motion. If ICP fails in planar areas, the SIFT odometry provides incremental motion estimate. If both ICP and the SIFT odometry fail, e.g., upon abrupt motion or inadequate features, the incremental motion is estimated by the IMU. Additionally, the IMU also observes the roll and pitch angles which can reduce long-term drift of the sensor assembly. In experiments on a consumer laptop, our system estimates motion at 8Hz on average while integrating color images to the local map and saving volumes of meshes concurrently. Moreover, it is immune to tracking failures, and has smaller drift than the state-of-the-art systems in large scale reconstruction.

Towards large scale stochastic rainfall models for flood risk assessment in trans-national basins

Science.gov (United States)

Serinaldi, F.; Kilsby, C. G.

2012-04-01

While extensive research has been devoted to rainfall-runoff modelling for risk assessment in small and medium size watersheds, less attention has been paid, so far, to large scale trans-national basins, where flood events have severe societal and economic impacts with magnitudes quantified in billions of Euros. As an example, in the April 2006 flood events along the Danube basin at least 10 people lost their lives and up to 30 000 people were displaced, with overall damages estimated at more than half a billion Euros. In this context, refined analytical methods are fundamental to improve the risk assessment and, then, the design of structural and non structural measures of protection, such as hydraulic works and insurance/reinsurance policies. Since flood events are mainly driven by exceptional rainfall events, suitable characterization and modelling of space-time properties of rainfall fields is a key issue to perform a reliable flood risk analysis based on alternative precipitation scenarios to be fed in a new generation of large scale rainfall-runoff models. Ultimately, this approach should be extended to a global flood risk model. However, as the need of rainfall models able to account for and simulate spatio-temporal properties of rainfall fields over large areas is rather new, the development of new rainfall simulation frameworks is a challenging task involving that faces with the problem of overcoming the drawbacks of the existing modelling schemes (devised for smaller spatial scales), but keeping the desirable properties. In this study, we critically summarize the most widely used approaches for rainfall simulation. Focusing on stochastic approaches, we stress the importance of introducing suitable climate forcings in these simulation schemes in order to account for the physical coherence of rainfall fields over wide areas. Based on preliminary considerations, we suggest a modelling framework relying on the Generalized Additive Models for Location, Scale

Long-Term Precipitation Analysis and Estimation of Precipitation Concentration Index Using Three Support Vector Machine Methods

Directory of Open Access Journals (Sweden)

Milan Gocic

2016-01-01

Full Text Available The monthly precipitation data from 29 stations in Serbia during the period of 1946–2012 were considered. Precipitation trends were calculated using linear regression method. Three CLINO periods (1961–1990, 1971–2000, and 1981–2010 in three subregions were analysed. The CLINO 1981–2010 period had a significant increasing trend. Spatial pattern of the precipitation concentration index (PCI was presented. For the purpose of PCI prediction, three Support Vector Machine (SVM models, namely, SVM coupled with the discrete wavelet transform (SVM-Wavelet, the firefly algorithm (SVM-FFA, and using the radial basis function (SVM-RBF, were developed and used. The estimation and prediction results of these models were compared with each other using three statistical indicators, that is, root mean square error, coefficient of determination, and coefficient of efficiency. The experimental results showed that an improvement in predictive accuracy and capability of generalization can be achieved by the SVM-Wavelet approach. Moreover, the results indicated the proposed SVM-Wavelet model can adequately predict the PCI.

Comparison of NEXRAD multisensor precipitation estimates to rain gage observations in and near DuPage County, Illinois, 2002–12

Science.gov (United States)

Spies, Ryan R.; Over, Thomas M.; Ortel, Terry W.

2018-05-21

In this report, precipitation data from 2002 to 2012 from the hourly gridded Next-Generation Radar (NEXRAD)-based Multisensor Precipitation Estimate (MPE) precipitation product are compared to precipitation data from two rain gage networks—an automated tipping bucket network of 25 rain gages operated by the U.S. Geological Survey (USGS) and 51 rain gages from the volunteer-operated Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network—in and near DuPage County, Illinois, at a daily time step to test for long-term differences in space, time, and distribution. The NEXRAD–MPE data that are used are from the fifty 2.5-mile grid cells overlying the rain gages from the other networks. Because of the challenges of measuring of frozen precipitation, the analysis period is separated between days with or without the chance of freezing conditions. The NEXRAD–MPE and tipping-bucket rain gage precipitation data are adjusted to account for undercatch by multiplying by a previously determined factor of 1.14. Under nonfreezing conditions, the three precipitation datasets are broadly similar in cumulative depth and distribution of daily values when the data are combined spatially across the networks. However, the NEXRAD–MPE data indicate a significant trend relative to both rain gage networks as a function of distance from the NEXRAD radar just south of the study area. During freezing conditions, of the USGS network rain gages only the heated gages were considered, and these gages indicate substantial mean undercatch of 50 and 61 percent compared to the NEXRAD–MPE and the CoCoRaHS gages, respectively. The heated USGS rain gages also indicate substantially lower quantile values during freezing conditions, except during the most extreme (highest) events. Because NEXRAD precipitation products are continually evolving, the report concludes with a discussion of recent changes in those products and their potential for improved precipitation estimation. An appendix

The Day-1 GPM Combined Precipitation Algorithm: IMERG

Science.gov (United States)

Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.

2012-12-01

The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) algorithm will provide the at-launch combined-sensor precipitation dataset being produced by the U.S. GPM Science Team. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in three current U.S. algorithms: - the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; - the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following storm motion; and - the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures, and filters out some non-raining cold clouds. The goal is to provide a long-term, fine-scale record of global precipitation from the entire constellation of precipitation-relevant satellite sensors, with input from surface precipitation gauges. The record will begin January 1998 at the start of the Tropical Rainfall Measuring Mission (TRMM) and extend as GPM records additional data. Although homogeneity is considered desirable, the use of diverse and evolving data sources works against the strict long-term homogeneity that characterizes a Climate Data Record (CDR). This talk will briefly review the design requirements for IMERG, including multiple runs at different latencies (most likely around 4 hours, 12 hours, and 2 months after observation time), various intermediate data fields as part of the IMERG data file, and the plans to bring up IMERG with calibration by TRMM initially, transitioning to GPM when its individual-sensor precipitation algorithms are fully functional

Attenuation of Chemical Reactivity of Shale Matrixes following Scale Precipitation

Science.gov (United States)

Li, Q.; Jew, A. D.; Kohli, A. H.; Alalli, G.; Kiss, A. M.; Kovscek, A. R.; Zoback, M. D.; Brown, G. E.; Maher, K.; Bargar, J.

2017-12-01

Introduction of fracture fluids into shales initiates a myriad of fluid-rock reactions that can strongly influence migration of fluid and hydrocarbon through shale/fracture interfaces. Due to the extremely low permeability of shale matrixes, studies on chemical reactivity of shales have mostly focused on shale surfaces. Shale-fluid interactions inside within shale matrixes have not been examined, yet the matrix is the primary conduit through which hydrocarbons and potential contaminants are transmitted. To characterize changes in matrix mineralogy, porosity, diffusivity, and permeability during hydraulic stimulation, we reacted Marcellus (high clay and low carbonate) and Eagle Ford (low clay and high carbonate) shale cores with fracture fluids for 3 weeks at elevated pressure and temperature (80 oC, and 77 bars). In the carbonate-poor Marcellus system, fluid pH increased from 2 to 4, and secondary Fe(OH)3 precipitates were observed in the fluid. Sulfur X-ray fluorescence maps show that fluids had saturated and reacted with the entire 1-cm-diameter core. In the carbonate-rich Eagle Ford system, pH increased from 2 to 6 due to calcite dissolution. When additional Ba2+ and SO42- were present (log10(Q/K)=1.3), extensive barite precipitation was observed in the matrix of the Eagle Ford core (and on the surface). Barite precipitation was also observed on the surface of the Marcellus core, although to a lesser extent. In the Marcellus system, the presence of barite scale attenuated diffusivity in the matrix, as demonstrated by sharply reduced Fe leaching and much less sulfide oxidation. Systematic studies in homogeneous solution show that barite scale precipitation rates are highly sensitive to pH, salinity, and the presence of organic compounds. These findings imply that chemical reactions are not confined to shale/fluid interfaces but can penetrate into shale matrices, and that barite scale formation can clog diffusion pathways for both fluid and hydrocarbon.

Spatial-Scale Characteristics of Precipitation Simulated by Regional Climate Models and the Implications for Hydrological Modeling

DEFF Research Database (Denmark)

Rasmussen, S.H.; Christensen, J. H.; Drews, Martin

2012-01-01

Precipitation simulated by regional climate models (RCMs) is generally biased with respect to observations, especially at the local scale of a few tens of kilometers. This study investigates how well two different RCMs are able to reproduce the spatial correlation patterns of observed summer...... length scales on the order of 130 km are found in both observed data and RCM simulations. When simulations and observations are aggregated to different grid sizes, the pattern correlation significantly decreases when the aggregation length is less than roughly 100 km. Furthermore, the intermodel standard......, reflecting larger predictive certainty of the RCMs at larger scales. The findings on aggregated grid scales are shown to be largely independent of the underlying RCMs grid resolutions but not of the overall size of RCM domain. With regard to hydrological modeling applications, these findings indicate...

On the response of the tropical atmosphere to large-scale deforestation

Science.gov (United States)

Eltahir, E. A. B.; Bras, R. L.

1993-01-01

Recent studies on the Amazon deforestation problem predict that removal of the forest will result in a higher surface temperature, a significant reduction in evaporation and precipitation, and possibly significant changes in the tropical circulation. Here, we discuss the basic mechanisms contributing to the response of the tropical atmosphere to deforestation. A simple linear model of the tropical atmosphere is used in studying the effects of deforestation on climate. It is suggested that the impact of large-scale deforestation on the circulation of the tropical atmosphere consists of two components: the response of the tropical circulation to the negative change in precipitation (heating), and the response of the same circulation to the positive change in surface temperature. Owing to their different signs, the changes in predicted temperature and precipitation excite competing responses working in opposite directions. The predicted change in tropical circulation determines the change, if any, in atmospheric moisture convergence, which is equivalent to the change in run-off. The dependence of run-off predictions on the relative magnitudes of the predicted changes in precipitation and surface temperature implies that the predictions about run-off are highly sensitive, which explains, at least partly, the disagreement between the different models concerning the sign of the predicted change in Amazonian run-off.

THE REGIONAL DIFFERENCES OF GPP ESTIMATION BY SOLAR INDUCED FLUORESCENCE

Directory of Open Access Journals (Sweden)

X. Wang

2018-04-01

Full Text Available Estimating gross primary productivity (GPP at large spatial scales is important for studying the global carbon cycle and global climate change. In this study, the relationship between solar-induced chlorophyll fluorescence (SIF and GPP is analysed in different levels of annual average temperature and annual total precipitation respectively using simple linear regression analysis. The results showed high correlation between SIF and GPP, when the area satisfied annual average temperature in the range of −5 °C to 15 °C and the annual total precipitation is higher than 200 mm. These results can provide a basis for future estimation of GPP research.

Estimating the electricity prices, generation costs and CO_2 emissions of large scale wind energy exports from Ireland to Great Britain

International Nuclear Information System (INIS)

Cleary, Brendan; Duffy, Aidan; Bach, Bjarne; Vitina, Aisma; O’Connor, Alan; Conlon, Michael

2016-01-01

The share of wind generation in the Irish and British electricity markets is set to increase by 2020 due to renewable energy (RE) targets. The United Kingdom (UK) and Ireland have set ambitious targets which require 30% and 40% of electricity demand to come from RE, mainly wind, by 2020, respectively. Ireland has sufficient indigenous onshore wind energy resources to exceed the RE target, while the UK faces uncertainty in achieving its target. A possible solution for the UK is to import RE directly from large scale onshore and offshore wind energy projects in Ireland; this possibility has recently been explored by both governments but is currently on hold. Thus, the aim of this paper is to estimate the effects of large scale wind energy in the Irish and British electricity markets in terms of wholesale system marginal prices, total generation costs and CO_2 emissions. The results indicate when the large scale Irish-based wind energy projects are connected directly to the UK there is a decrease of 0.6% and 2% in the Irish and British wholesale system marginal prices under the UK National Grid slow progression scenario, respectively. - Highlights: • Modelling the Irish and British electricity markets. • Investigating the impacts of large scale wind energy within the markets. • Results indicate a reduction in wholesale system marginal prices in both markets. • Decrease in total generation costs and CO_2 emissions in both markets.

Concepts for Large Scale Hydrogen Production

OpenAIRE

Jakobsen, Daniel; Åtland, Vegar

2016-01-01

The objective of this thesis is to perform a techno-economic analysis of large-scale, carbon-lean hydrogen production in Norway, in order to evaluate various production methods and estimate a breakeven price level. Norway possesses vast energy resources and the export of oil and gas is vital to the country s economy. The results of this thesis indicate that hydrogen represents a viable, carbon-lean opportunity to utilize these resources, which can prove key in the future of Norwegian energy e...

Accuracy assessment of planimetric large-scale map data for decision-making

Directory of Open Access Journals (Sweden)

Doskocz Adam

2016-06-01

Full Text Available This paper presents decision-making risk estimation based on planimetric large-scale map data, which are data sets or databases which are useful for creating planimetric maps on scales of 1:5,000 or larger. The studies were conducted on four data sets of large-scale map data. Errors of map data were used for a risk assessment of decision-making about the localization of objects, e.g. for land-use planning in realization of investments. An analysis was performed for a large statistical sample set of shift vectors of control points, which were identified with the position errors of these points (errors of map data.

Precipitation evidences on X-Band Synthetic Aperture Radar imagery: an approach for quantitative detection and estimation

Science.gov (United States)

Mori, Saverio; Marzano, Frank S.; Montopoli, Mario; Pulvirenti, Luca; Pierdicca, Nazzareno

2017-04-01

Spaceborne synthetic aperture radars (SARs) operating at L-band and above are nowadays a well-established tool for Earth remote sensing; among the numerous civil applications we can indicate flood areas detection and monitoring, earthquakes analysis, digital elevation model production, land use monitoring and classification. Appealing characteristics of this kind of instruments is the high spatial resolution ensured in almost all-weather conditions and with a reasonable duty cycle and coverage. This result has achieved by the by the most recent generation of SAR missions, which moreover allow polarimetric observation of the target. Nevertheless, atmospheric clouds, in particular the precipitating ones, can significantly affect the signal backscattered from the ground surface (e.g. Ferrazzoli and Schiavon, 1997), on both amplitude and phase, with effects increasing with the operating frequency. In this respect, proofs are given by several recent works (e.g. Marzano et al., 2010, Baldini et al., 2014) using X-Band SAR data by COSMO-SkyMed (CSK) and TerraSAR-X (TSX) missions. On the other hand, this sensitivity open interesting perspectives towards the SAR observation, and eventually quantification, of precipitations. In this respect, a proposal approach for X-SARs precipitation maps production and cloud masking arise from our work. Cloud masking allows detection of precipitation compromised areas. Respect precipitation maps, satellite X-SARs offer the unique possibility to ingest within flood forecasting model precipitation data at the catchment scale. This aspect is particularly innovative, even if work has been done the late years, and some aspects need to still address. Our developed processing framework allows, within the cloud masking stage, distinguishing flooded areas, precipitating clouds together with permanent water bodies, all appearing dark in the SAR image. The procedure is mainly based on image segmentation techniques and fuzzy logic (e.g. Pulvirenti et

Large-scale wind power integration and wholesale electricity trading benefits: Estimation via an ex post approach

International Nuclear Information System (INIS)

Gil, Hugo A.; Gomez-Quiles, Catalina; Riquelme, Jesus

2012-01-01

The integration of large-scale wind power has brought about a series of challenges to the power industry, but at the same time a number of benefits are being realized. Among those, the ability of wind power to cause a decline in the electricity market prices has been recognized. In quantifying this effect, some models used in recent years are based on simulations of the market supply-side and the price clearing process. The accuracy of the estimates depend on the quality of the input data, the veracity of the adopted scenarios and the rigorousness of the solution technique. In this work, a series of econometric techniques based on actual ex post wind power and electricity price data are implemented for the estimation of the impact of region-wide wind power integration on the local electricity market clearing prices and the trading savings that stem from this effect. The model is applied to the case of Spain, where the estimated savings are compared against actual credit and bonus expenses to ratepayers. The implications and extent of these results for current and future renewable energy policy-making are discussed. - Highlights: ► Wholesale electricity market trading benefits by wind power are quantified. ► Actual wind power forecast-based bids and electricity price data from Spain are used. ► Different econometric tools are used and compared for improved estimation accuracy. ► Estimated benefits outweigh current credit overhead paid to wind farms in Spain. ► An economically efficient benefit surplus allocation framework is proposed.

State estimation for large-scale wastewater treatment plants.

Science.gov (United States)

Busch, Jan; Elixmann, David; Kühl, Peter; Gerkens, Carine; Schlöder, Johannes P; Bock, Hans G; Marquardt, Wolfgang

2013-09-01

Many relevant process states in wastewater treatment are not measurable, or their measurements are subject to considerable uncertainty. This poses a serious problem for process monitoring and control. Model-based state estimation can provide estimates of the unknown states and increase the reliability of measurements. In this paper, an integrated approach is presented for the optimization-based sensor network design and the estimation problem. Using the ASM1 model in the reference scenario BSM1, a cost-optimal sensor network is designed and the prominent estimators EKF and MHE are evaluated. Very good estimation results for the system comprising 78 states are found requiring sensor networks of only moderate complexity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Merging Satellite Precipitation Products for Improved Streamflow Simulations

Science.gov (United States)

Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

2017-12-01

Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical

Contribution of large-scale circulation anomalies to changes in extreme precipitation frequency in the United States

Science.gov (United States)

Lejiang Yu; Shiyuan Zhong; Lisi Pei; Xindi (Randy) Bian; Warren E. Heilman

2016-01-01

The mean global climate has warmed as a result of the increasing emission of greenhouse gases induced by human activities. This warming is considered the main reason for the increasing number of extreme precipitation events in the US. While much attention has been given to extreme precipitation events occurring over several days, which are usually responsible for...

Radar rainfall estimation of stratiform winter precipitation in the Belgian Ardennes

NARCIS (Netherlands)

Hazenberg, P.; Leijnse, H.; Uijlenhoet, R.

2011-01-01

Radars are known for their ability to obtain a wealth of information about spatial storm field characteristics. Unfortunately, rainfall estimates obtained by this instrument are known to be affected by multiple sources of error. Especially for stratiform precipitation systems, the quality of radar

Climatological studies on precipitation features and large-scale atmospheric fields on the heavy rainfall days in the eastern part of Japan from the Baiu to midsummer season

Science.gov (United States)

Matsumoto, Kengo; Kato, Kuranoshin; Otani, Kazuo

2017-04-01

In East Asia the significant subtropical frontal zone called the Meiyu (in China) / Baiu (in Japan) appears in early summer (just before the midsummer) and the huge rainfall is brought due to the frequent appearance of the "heavy rainfall days" (referred to as HRDs hereafter) mainly in that western part. On the other hand, large-scale fields around the front in eastern Japan is rather different from that in western Japan but the total precipitation in the eastern Japan is still considerable compared to that in the other midlatitude regions. Thus, it is also interesting to examine how the rainfall characteristics and large-scale atmospheric fields on HRDs (with more than 50 mm/day) in the eastern Japan in the mature stage of the Baiu season (16 June 15 July), together with those in midsummer (1 31 August). Based on such scientific background, further analyses were performed in this study mainly with the daily and the hourly precipitation data and the NCEP/NCAR re-analysis date from 1971 to 2010, succeeding to our previous results (e.g., EGU2015). As reported at EGU2014 and 2015, about half of HRDs at Tokyo (eastern Japan) were related to the typhoon even in the Baiu season. Interestingly, half of HRDs were characterized by the large contribution of moderate rain less than 10 mm/h. While, the precipitation on HRDs at Tokyo in midsummer was mainly brought by the intense rainfall with more than 10 mm/h, in association with the typhoons. In the present study, we examined the composite meridional structure of the rainfall area along 140E. In the pattern only associated with a typhoons in the Baiu season (Pattern A), the heavy rainfall area (more than 50 mm/day) with large contribution of the intense rain (stronger than 10 mm/h) showed rather wide meridional extension. The area was characterized by the duration of the intermittent enhancement of the rainfall. In the pattern associated with a typhoon and a front (Pattern B), while the contribution ratio of the rainfall

Large transverse momentum processes in a non-scaling parton model

International Nuclear Information System (INIS)

Stirling, W.J.

1977-01-01

The production of large transverse momentum mesons in hadronic collisions by the quark fusion mechanism is discussed in a parton model which gives logarithmic corrections to Bjorken scaling. It is found that the moments of the large transverse momentum structure function exhibit a simple scale breaking behaviour similar to the behaviour of the Drell-Yan and deep inelastic structure functions of the model. An estimate of corresponding experimental consequences is made and the extent to which analogous results can be expected in an asymptotically free gauge theory is discussed. A simple set of rules is presented for incorporating the logarithmic corrections to scaling into all covariant parton model calculations. (Auth.)

Large-scale Homogenization of Bulk Materials in Mammoth Silos

NARCIS (Netherlands)

Schott, D.L.

2004-01-01

This doctoral thesis concerns the large-scale homogenization of bulk materials in mammoth silos. The objective of this research was to determine the best stacking and reclaiming method for homogenization in mammoth silos. For this purpose a simulation program was developed to estimate the

Where Does the Irrigation Water Go? An Estimate of the Contribution of Irrigation to Precipitation Using MERRA

Science.gov (United States)

Wei, Jiangfeng; Dirmeyer, Paul A.; Wisser, Dominik; Bosilovich, Michael G.; Mocko, David M.

2013-01-01

Irrigation is an important human activity that may impact local and regional climate, but current climate model simulations and data assimilation systems generally do not explicitly include it. The European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) shows more irrigation signal in surface evapotranspiration (ET) than the Modern-Era Retrospective Analysis for Research and Applications (MERRA) because ERA-Interim adjusts soil moisture according to the observed surface temperature and humidity while MERRA has no explicit consideration of irrigation at the surface. But, when compared with the results from a hydrological model with detailed considerations of agriculture, the ET from both reanalyses show large deficiencies in capturing the impact of irrigation. Here, a back-trajectory method is used to estimate the contribution of irrigation to precipitation over local and surrounding regions, using MERRA with observation-based corrections and added irrigation-caused ET increase from the hydrological model. Results show substantial contributions of irrigation to precipitation over heavily irrigated regions in Asia, but the precipitation increase is much less than the ET increase over most areas, indicating that irrigation could lead to water deficits over these regions. For the same increase in ET, precipitation increases are larger over wetter areas where convection is more easily triggered, but the percentage increase in precipitation is similar for different areas. There are substantial regional differences in the patterns of irrigation impact, but, for all the studied regions, the highest percentage contribution to precipitation is over local land.

Multi-Point Measurements to Characterize Radiation Belt Electron Precipitation Loss

Science.gov (United States)

Blum, L. W.

2017-12-01

Multipoint measurements in the inner magnetosphere allow the spatial and temporal evolution of various particle populations and wave modes to be disentangled. To better characterize and quantify radiation belt precipitation loss, we utilize multi-point measurements both to study precipitating electrons directly as well as the potential drivers of this loss process. Magnetically conjugate CubeSat and balloon measurements are combined to estimate of the temporal and spatial characteristics of dusk-side precipitation features and quantify loss due to these events. To then understand the drivers of precipitation events, and what determines their spatial structure, we utilize measurements from the dual Van Allen Probes to estimate spatial and temporal scales of various wave modes in the inner magnetosphere, and compare these to precipitation characteristics. The structure, timing, and spatial extent of waves are compared to those of MeV electron precipitation during a few individual events to determine when and where EMIC waves cause radiation belt electron precipitation. Magnetically conjugate measurements provide observational support of the theoretical picture of duskside interaction of EMIC waves and MeV electrons leading to radiation belt loss. Finally, understanding the drivers controlling the spatial scales of wave activity in the inner magnetosphere is critical for uncovering the underlying physics behind the wave generation as well as for better predicting where and when waves will be present. Again using multipoint measurements from the Van Allen Probes, we estimate the spatial and temporal extents and evolution of plasma structures and their gradients in the inner magnetosphere, to better understand the drivers of magnetospheric wave characteristic scales. In particular, we focus on EMIC waves and the plasma parameters important for their growth, namely cold plasma density and cool and warm ion density, anisotropy, and composition.

Simulating the impact of the large-scale circulation on the 2-m temperature and precipitation climatology

Science.gov (United States)

The impact of the simulated large-scale atmospheric circulation on the regional climate is examined using the Weather Research and Forecasting (WRF) model as a regional climate model. The purpose is to understand the potential need for interior grid nudging for dynamical downscal...

Compositional variations for small-scale gamma prime (γ′) precipitates formed at different cooling rates in an advanced Ni-based superalloy

International Nuclear Information System (INIS)

Chen, Y.Q.; Francis, E.; Robson, J.; Preuss, M.; Haigh, S.J.

2015-01-01

Size-dependent compositional variations under different cooling regimes have been investigated for ordered L1 2 -structured gamma prime (γ′) precipitates in the commercial powder metallurgy Ni-based superalloy RR1000. Using scanning transmission electron microscope imaging combined with absorption-corrected energy-dispersive X-ray spectroscopy, we have discovered large differences in the Al, Ti and Co compositions for γ′ precipitates in the size range 10–300 nm. Our experimental results, coupled with complementary thermodynamic calculations, demonstrate the importance of kinetic factors on precipitate composition in Ni-based superalloys. In particular, these results provide new evidence for the role of elemental diffusion kinetics and aluminium antisite atoms on the low-temperature growth kinetics of fine-scale γ′ precipitates. Our findings have important implications for understanding the microstructure and precipitation behaviour of Ni-based superalloys, suggesting a transition in the mechanism of vacancy-mediated diffusion of Al from intrasublattice exchange at high temperatures to intersublattice antisite-assisted exchange at low temperatures

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.

Energy transfers in large-scale and small-scale dynamos

Science.gov (United States)

Samtaney, Ravi; Kumar, Rohit; Verma, Mahendra

2015-11-01

We present the energy transfers, mainly energy fluxes and shell-to-shell energy transfers in small-scale dynamo (SSD) and large-scale dynamo (LSD) using numerical simulations of MHD turbulence for Pm = 20 (SSD) and for Pm = 0.2 on 10243 grid. For SSD, we demonstrate that the magnetic energy growth is caused by nonlocal energy transfers from the large-scale or forcing-scale velocity field to small-scale magnetic field. The peak of these energy transfers move towards lower wavenumbers as dynamo evolves, which is the reason for the growth of the magnetic fields at the large scales. The energy transfers U2U (velocity to velocity) and B2B (magnetic to magnetic) are forward and local. For LSD, we show that the magnetic energy growth takes place via energy transfers from large-scale velocity field to large-scale magnetic field. We observe forward U2U and B2B energy flux, similar to SSD.

Storm induced large scale TIDs observed in GPS derived TEC

Directory of Open Access Journals (Sweden)

C. Borries

2009-04-01

Full Text Available This work is a first statistical analysis of large scale traveling ionospheric disturbances (LSTID in Europe using total electron content (TEC data derived from GNSS measurements. The GNSS receiver network in Europe is dense enough to map the ionospheric perturbation TEC with high horizontal resolution. The derived perturbation TEC maps are analysed studying the effect of space weather events on the ionosphere over Europe.

Equatorward propagating storm induced wave packets have been identified during several geomagnetic storms. Characteristic parameters such as velocity, wavelength and direction were estimated from the perturbation TEC maps. Showing a mean wavelength of 2000 km, a mean period of 59 min and a phase speed of 684 ms⁻¹ in average, the perturbations are allocated to LSTID. The comparison to LSTID observed over Japan shows an equal wavelength but a considerably faster phase speed. This might be attributed to the differences in the distance to the auroral region or inclination/declination of the geomagnetic field lines.

The observed correlation between the LSTID amplitudes and the Auroral Electrojet (AE indicates that most of the wave like perturbations are exited by Joule heating. Particle precipitation effects could not be separated.

Evolutionary leap in large-scale flood risk assessment needed

OpenAIRE

Vorogushyn, Sergiy; Bates, Paul D.; de Bruijn, Karin; Castellarin, Attilio; Kreibich, Heidi; Priest, Sally J.; Schröter, Kai; Bagli, Stefano; Blöschl, Günter; Domeneghetti, Alessio; Gouldby, Ben; Klijn, Frans; Lammersen, Rita; Neal, Jeffrey C.; Ridder, Nina

2018-01-01

Current approaches for assessing large-scale flood risks contravene the fundamental principles of the flood risk system functioning because they largely ignore basic interactions and feedbacks between atmosphere, catchments, river-floodplain systems and socio-economic processes. As a consequence, risk analyses are uncertain and might be biased. However, reliable risk estimates are required for prioritizing national investments in flood risk mitigation or for appraisal and management of insura...

Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal

Directory of Open Access Journals (Sweden)

Tarendra Lakhankar

2013-08-01

Full Text Available Precipitation in mountain regions is often highly variable and poorly observed, limiting abilities to manage water resource challenges. Here, we evaluate remote sensing and ground station-based gridded precipitation products over Nepal against weather station precipitation observations on a monthly timescale. We find that the Tropical Rainfall Measuring Mission (TRMM 3B-43 precipitation product exhibits little mean bias and reasonable skill in giving precipitation over Nepal. Compared to station observations, the TRMM precipitation product showed an overall Nash-Sutcliffe efficiency of 0.49, which is similar to the skill of the gridded station-based product Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE. The other satellite precipitation products considered (Global Satellite Mapping of Precipitation (GSMaP, the Climate Prediction Center Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS were less skillful, as judged by Nash-Sutcliffe efficiency, and, on average, substantially underestimated precipitation compared to station observations, despite their, in some cases, higher nominal spatial resolution compared to TRMM. None of the products fully captured the dependence of mean precipitation on elevation seen in the station observations. Overall, the TRMM product is promising for use in water resources applications.

Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

Directory of Open Access Journals (Sweden)

M. P. Mittermaier

2008-05-01

Full Text Available A simple measure of the uncertainty associated with using radar-derived rainfall estimates as "truth" has been introduced to the Numerical Weather Prediction (NWP verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radar-composite were used.

The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.

Novel probabilistic and distributed algorithms for guidance, control, and nonlinear estimation of large-scale multi-agent systems

Science.gov (United States)

Bandyopadhyay, Saptarshi

Multi-agent systems are widely used for constructing a desired formation shape, exploring an area, surveillance, coverage, and other cooperative tasks. This dissertation introduces novel algorithms in the three main areas of shape formation, distributed estimation, and attitude control of large-scale multi-agent systems. In the first part of this dissertation, we address the problem of shape formation for thousands to millions of agents. Here, we present two novel algorithms for guiding a large-scale swarm of robotic systems into a desired formation shape in a distributed and scalable manner. These probabilistic swarm guidance algorithms adopt an Eulerian framework, where the physical space is partitioned into bins and the swarm's density distribution over each bin is controlled using tunable Markov chains. In the first algorithm - Probabilistic Swarm Guidance using Inhomogeneous Markov Chains (PSG-IMC) - each agent determines its bin transition probabilities using a time-inhomogeneous Markov chain that is constructed in real-time using feedback from the current swarm distribution. This PSG-IMC algorithm minimizes the expected cost of the transitions required to achieve and maintain the desired formation shape, even when agents are added to or removed from the swarm. The algorithm scales well with a large number of agents and complex formation shapes, and can also be adapted for area exploration applications. In the second algorithm - Probabilistic Swarm Guidance using Optimal Transport (PSG-OT) - each agent determines its bin transition probabilities by solving an optimal transport problem, which is recast as a linear program. In the presence of perfect feedback of the current swarm distribution, this algorithm minimizes the given cost function, guarantees faster convergence, reduces the number of transitions for achieving the desired formation, and is robust to disturbances or damages to the formation. We demonstrate the effectiveness of these two proposed swarm

Precipitation, landsliding, and erosion across the Olympic Mountains, Washington State, USA

Science.gov (United States)

Smith, Stephen G.; Wegmann, Karl W.

2018-01-01

In the Olympic Mountains of Washington State, landsliding is the primary surface process by which bedrock and hillslope regolith are delivered to river networks. However, the relative importance of large earthquakes versus high magnitude precipitation events to the total volume of landslide material transported to valley bottoms remains unknown in part due to the absence of large historical earthquakes. To test the hypothesis that erosion is linked to precipitation, approximately 1000 landslides were mapped from Google Earth imagery between 1990 and 2015 along a 15 km-wide × 85 km-long (1250 km2) swath across the range. The volume of hillslope material moved by each slide was calculated using previously published area-volume scaling relationships, and the spatial distribution of landslide volume was compared to mean annual precipitation data acquired from the PRISM climate group for the period 1981-2010. Statistical analysis reveals a significant correlation (r = 0.55; p landslide volume and mean annual precipitation, with 98% of landslide volume occurring along the windward, high-precipitation side of the range during the 25-year interval. Normalized to area, this volume yields a basin-wide erosion rate of 0.28 ± 0.11 mm yr- 1, which is similar to previous time-variable estimates of erosion throughout the Olympic Mountains, including those from river sediment yield, cosmogenic 10Be, fluvial terrace incision, and thermochronometry. The lack of large historic earthquakes makes it difficult to assess the relative contributions of precipitation and seismic shaking to total erosion, but our results suggest that climate, and more specifically a sharp precipitation gradient, plays an important role in controlling erosion and landscape evolution over both short and long timescales across the Olympic Mountains.

Estimation of precipitable water at different locations using surface dew-point

Science.gov (United States)

Abdel Wahab, M.; Sharif, T. A.

1995-09-01

The Reitan (1963) regression equation of the form ln w = a + bT d has been examined and tested to estimate precipitable water vapor content from the surface dew point temperature at different locations. The results of this study indicate that the slope b of the above equation has a constant value of 0.0681, while the intercept a changes rapidly with latitude. The use of the variable intercept technique can improve the estimated result by about 2%.

Global Precipitation Measurement (GPM) Core Observatory Falling Snow Estimates

Science.gov (United States)

Skofronick Jackson, G.; Kulie, M.; Milani, L.; Munchak, S. J.; Wood, N.; Levizzani, V.

2017-12-01

Retrievals of falling snow from space represent an important data set for understanding and linking the Earth's atmospheric, hydrological, and energy cycles. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. This work focuses on comparing the first stable falling snow retrieval products (released May 2017) for the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO), which was launched February 2014, and carries both an active dual frequency (Ku- and Ka-band) precipitation radar (DPR) and a passive microwave radiometer (GPM Microwave Imager-GMI). Five separate GPM-CO falling snow retrieval algorithm products are analyzed including those from DPR Matched (Ka+Ku) Scan, DPR Normal Scan (Ku), DPR High Sensitivity Scan (Ka), combined DPR+GMI, and GMI. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new, the different on-orbit instruments don't capture all snow rates equally, and retrieval algorithms differ. Thus a detailed comparison among the GPM-CO products elucidates advantages and disadvantages of the retrievals. GPM and CloudSat global snowfall evaluation exercises are natural investigative pathways to explore, but caution must be undertaken when analyzing these datasets for comparative purposes. This work includes outlining the challenges associated with comparing GPM-CO to CloudSat satellite snow estimates due to the different sampling, algorithms, and instrument capabilities. We will highlight some factors and assumptions that can be altered or statistically normalized and applied in an effort to make comparisons between GPM and CloudSat global satellite falling snow products as equitable as possible.

Thermal anchoring of wires in large scale superconducting coil test experiment

International Nuclear Information System (INIS)

Patel, Dipak; Sharma, A.N.; Prasad, Upendra; Khristi, Yohan; Varmora, Pankaj; Doshi, Kalpesh; Pradhan, S.

2013-01-01

Highlights: • We addressed how thermal anchoring in large scale coil test is different compare to small cryogenic apparatus? • We did precise estimation of thermal anchoring length at 77 K and 4.2 K heat sink in large scale superconducting coil test experiment. • We addressed, the quality of anchoring without covering entire wires using Kapton/Teflon tape. • We obtained excellent results in temperature measurement without using GE Varnish by doubling estimated anchoring length. -- Abstract: Effective and precise thermal anchoring of wires in cryogenic experiment is mandatory to measure temperature in milikelvin accuracy and to avoid unnecessary cooling power due to additional heat conduction from room temperature (RT) to operating temperature (OT) through potential, field, displacement and stress measurement instrumentation wires. Instrumentation wires used in large scale superconducting coil test experiments are different compare to cryogenic apparatus in terms of unique construction and overall diameter/area due to errorless measurement in large time-varying magnetic field compare to small cryogenic apparatus, often shielded wires are used. Hence, along with other variables, anchoring techniques and required thermal anchoring length are entirely different in this experiment compare to cryogenic apparatus. In present paper, estimation of thermal anchoring length of five different types of instrumentation wires used in coils test campaign at Institute for Plasma Research (IPR), India has been discussed and some temperature measurement results of coils test campaign have been presented

Centralized manure digestion. Selection of locations and estimation of costs of large-scale manure storage application

International Nuclear Information System (INIS)

1995-03-01

A study to assess the possibilities and the consequences of the use of existing Dutch large scale manure silos at centralised anaerobic digestion plants (CAD-plants) for manure and energy-rich organic wastes is carried out. Reconstruction of these large scale manure silos into digesters for a CAD-plant is not self-evident due to the high height/diameter ratio of these silos and the extra investments that have to be made for additional facilities for roofing, insulation, mixing and heating. From the results of an inventory and selection of large scale manure silos with a storage capacity above 1,500 m 3 it appeared that there are 21 locations in The Netherlands that can be qualified for realisation of a CAD plant with a processing capacity of 100 m 3 biomass (80% manure, 20% additives) per day. These locations are found in particular at the 'shortage-areas' for manure fertilisation in the Dutch provinces Groningen and Drenthe. Three of these 21 locations with large scale silos are considered to be the most suitable for realisation of a large scale CAD-plant. The selection is based on an optimal scale for a CAD-plant of 300 m 3 material (80% manure, 20% additives) to be processed per day and the most suitable consuming markets for the biogas produced at the CAD-plant. The three locations are at Middelharnis, Veendam, and Klazinaveen. Applying the conditions as used in this study and accounting for all costs for transport of manure, additives and end-product including the costs for the storage facilities, a break-even operation might be realised at a minimum income for the additives of approximately 50 Dutch guilders per m 3 (including TAV). This income price is considerably lower than the prevailing costs for tipping or processing of organic wastes in The Netherlands. This study revealed that a break-even exploitation of a large scale CAD-plant for the processing of manure with energy-rich additives is possible. (Abstract Truncated)

Exploring the correlation between annual precipitation and potential evaporation

Science.gov (United States)

Chen, X.; Buchberger, S. G.

2017-12-01

The interdependence between precipitation and potential evaporation is closely related to the classic Budyko framework. In this study, a systematic investigation of the correlation between precipitation and potential evaporation at the annual time step is conducted at both point scale and watershed scale. The point scale precipitation and potential evaporation data over the period of 1984-2015 are collected from 259 weather stations across the United States. The watershed scale precipitation data of 203 watersheds across the United States are obtained from the Model Parameter Estimation Experiment (MOPEX) dataset from 1983 to 2002; and potential evaporation data of these 203 watersheds in the same period are obtained from a remote-sensing algorithm. The results show that majority of the weather stations (77%) and watersheds (79%) exhibit a statistically significant negative correlation between annual precipitation and annual potential evaporation. The aggregated data cloud of precipitation versus potential evaporation follows a curve based on the combination of the Budyko-type equation and Bouchet's complementary relationship. Our result suggests that annual precipitation and potential evaporation are not independent when both Budyko's hypothesis and Bouchet's hypothesis are valid. Furthermore, we find that the wet surface evaporation, which is controlled primarily by short wave radiation as defined in Bouchet's hypothesis, exhibits less dependence on precipitation than the potential evaporation. As a result, we suggest that wet surface evaporation is a better representation of energy supply than potential evaporation in the Budyko framework.

Simulating space-time uncertainty in continental-scale gridded precipitation fields for agrometeorological modelling

NARCIS (Netherlands)

Wit, de A.J.W.; Bruin, de S.

2006-01-01

Previous analyses of the effects of uncertainty in precipitation fields on the output of EU Crop Growth Monitoring System (CGMS) demonstrated that the influence on simulated crop yield was limited at national scale, but considerable at local and regional scales. We aim to propagate uncertainty due

Analysis for preliminary evaluation of discrete fracture flow and large-scale permeability in sedimentary rocks

International Nuclear Information System (INIS)

Kanehiro, B.Y.; Lai, C.H.; Stow, S.H.

1987-05-01

Conceptual models for sedimentary rock settings that could be used in future evaluation and suitability studies are being examined through the DOE Repository Technology Program. One area of concern for the hydrologic aspects of these models is discrete fracture flow analysis as related to the estimation of the size of the representative elementary volume, evaluation of the appropriateness of continuum assumptions and estimation of the large-scale permeabilities of sedimentary rocks. A basis for preliminary analysis of flow in fracture systems of the types that might be expected to occur in low permeability sedimentary rocks is presented. The approach used involves numerical modeling of discrete fracture flow for the configuration of a large-scale hydrologic field test directed at estimation of the size of the representative elementary volume and large-scale permeability. Analysis of fracture data on the basis of this configuration is expected to provide a preliminary indication of the scale at which continuum assumptions can be made

Large-scale data analytics

CERN Document Server

Gkoulalas-Divanis, Aris

2014-01-01

Provides cutting-edge research in large-scale data analytics from diverse scientific areas Surveys varied subject areas and reports on individual results of research in the field Shares many tips and insights into large-scale data analytics from authors and editors with long-term experience and specialization in the field

Spatial Downscaling of TRMM Precipitation using MODIS product in the Korean Peninsula

Science.gov (United States)

Cho, H.; Choi, M.

2013-12-01

Precipitation is a major driving force in the water cycle. But, it is difficult to provide spatially distributed precipitation data from isolated individual in situ. The Tropical Rainfall Monitoring Mission (TRMM) satellite can provide precipitation data with relatively coarse spatial resolution (0.25° scale) at daily basis. In order to overcome the coarse spatial resolution of TRMM precipitation products, we conducted a downscaling technique using a scaling parameter from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor. In this study, statistical relations between precipitation estimates derived from the TRMM satellite and the normalized difference vegetation index (NDVI) which is obtained from the MODIS sensor in TERRA satellite are found for different spatial scales on the Korean peninsula in northeast Asia. We obtain the downscaled precipitation mapping by regression equation between yearly TRMM precipitations values and annual average NDVI aggregating 1km to 25 degree. The downscaled precipitation is validated using time series of the ground measurements precipitation dataset provided by Korea Meteorological Organization (KMO) from 2002 to 2005. To improve the spatial downscaling of precipitation, we will conduct a study about correlation between precipitation and land surface temperature, perceptible water and other hydrological parameters.

Basin-scale estimates of pelagic and coral reef calcification in the Red Sea and Western Indian Ocean.

Science.gov (United States)

Steiner, Zvi; Erez, Jonathan; Shemesh, Aldo; Yam, Ruth; Katz, Amitai; Lazar, Boaz

2014-11-18

Basin-scale calcification rates are highly important in assessments of the global oceanic carbon cycle. Traditionally, such estimates were based on rates of sedimentation measured with sediment traps or in deep sea cores. Here we estimated CaCO3 precipitation rates in the surface water of the Red Sea from total alkalinity depletion along their axial flow using the water flux in the straits of Bab el Mandeb. The relative contribution of coral reefs and open sea plankton were calculated by fitting a Rayleigh distillation model to the increase in the strontium to calcium ratio. We estimate the net amount of CaCO3 precipitated in the Red Sea to be 7.3 ± 0.4·10(10) kg·y(-1) of which 80 ± 5% is by pelagic calcareous plankton and 20 ± 5% is by the flourishing coastal coral reefs. This estimate for pelagic calcification rate is up to 40% higher than published sedimentary CaCO3 accumulation rates for the region. The calcification rate of the Gulf of Aden was estimated by the Rayleigh model to be ∼1/2 of the Red Sea, and in the northwestern Indian Ocean, it was smaller than our detection limit. The results of this study suggest that variations of major ions on a basin scale may potentially help in assessing long-term effects of ocean acidification on carbonate deposition by marine organisms.

Integrating weather and geotechnical monitoring data for assessing the stability of large scale surface mining operations

Directory of Open Access Journals (Sweden)

Steiakakis Chrysanthos

2016-01-01

Full Text Available The geotechnical challenges for safe slope design in large scale surface mining operations are enormous. Sometimes one degree of slope inclination can significantly reduce the overburden to ore ratio and therefore dramatically improve the economics of the operation, while large scale slope failures may have a significant impact on human lives. Furthermore, adverse weather conditions, such as high precipitation rates, may unfavorably affect the already delicate balance between operations and safety. Geotechnical, weather and production parameters should be systematically monitored and evaluated in order to safely operate such pits. Appropriate data management, processing and storage are critical to ensure timely and informed decisions.

An Investigation of the High Efficiency Estimation Approach of the Large-Scale Scattered Point Cloud Normal Vector

Directory of Open Access Journals (Sweden)

Xianglin Meng

2018-03-01

Full Text Available The normal vector estimation of the large-scale scattered point cloud (LSSPC plays an important role in point-based shape editing. However, the normal vector estimation for LSSPC cannot meet the great challenge of the sharp increase of the point cloud that is mainly attributed to its low computational efficiency. In this paper, a novel, fast method-based on bi-linear interpolation is reported on the normal vector estimation for LSSPC. We divide the point sets into many small cubes to speed up the local point search and construct interpolation nodes on the isosurface expressed by the point cloud. On the premise of calculating the normal vectors of these interpolated nodes, a normal vector bi-linear interpolation of the points in the cube is realized. The proposed approach has the merits of accurate, simple, and high efficiency, because the algorithm only needs to search neighbor and calculates normal vectors for interpolation nodes that are usually far less than the point cloud. The experimental results of several real and simulated point sets show that our method is over three times faster than the Elliptic Gabriel Graph-based method, and the average deviation is less than 0.01 mm.

Constraining precipitation amount and distribution over cold regions using GRACE

Science.gov (United States)

Behrangi, A.; Reager, J. T., II; Gardner, A. S.; Fisher, J.

2017-12-01

Current quantitative knowledge on the amount and distribution of precipitation in high-elevation and high latitude regions is limited due to instrumental and retrieval shortcomings. Here we demonstrate how that satellite gravimetry (Gravity Recovery and Climate Experiment, GRACE) can be used to provide an independent estimate of monthly accumulated precipitation using mass balance. Results showed that the GRACE-based precipitation estimate has the highest agreement with most of the commonly used precipitation products in summer, but it deviates from them in cold months, when the other products are expected to have larger error. We also observed that as near surface temperature decreases products tend to underestimate accumulated precipitation retrieved from GRACE. The analysis performed using various products such as GPCP, GPCC, TRMM, and gridded station data over vast regions in high latitudes and two large endorheic basins in High Mountain Asia. Based on the analysis over High Mountain Asia it was found that most of the products capture about or less than 50% of the total precipitation estimated using GRACE in winter. Overall, GPCP showed better agreement with GRACE estimate than other products. Yet on average GRACE showed 30% more annual precipitation than GPCP in the study basin.

Precipitation Pattern Controls on the Dynamics and Subsequent Export of Large Wood from River Catchments

Science.gov (United States)

Seo, J.; Nakamura, F.; Chun, K.; Grant, G. E.

2011-12-01

In-stream large wood (LW) has a critical impact on the geomorphic and ecological character in river catchments, yet relatively little is known about variations in its dynamics and subsequent export in relation to different precipitation patterns and intensities. To understand these variations we used the annual volume of LW removed from 42 reservoirs in Japan and daily precipitation at or near the reservoir sites. Daily precipitation data were transformed into effective precipitation to evaluate trends in both current and antecedent precipitation, and these data were then used to explain basin variation in LW export. Model selection with generalized linear mixed models revealed that the precipitation pattern and intensity controlling LW export in small, intermediate, and large watersheds differed with latitude along the Japanese archipelago. LW export in small watersheds was well explained by effective precipitation greater than 120 mm, and showed little latitudinal variation. In contrast, LW export in intermediate and large watersheds was well explained by daily precipitation greater than 40 mm and 60 mm, respectively, and varied with latitude. In small watersheds with narrow channels and low stream discharges, mass movements (such as landslides and debris flows) are major factors in the production and transport of LW. Thus LW export in small watersheds appears to be regulated by the effective precipitation required to initiate mass movements, and shows little latitudinal change. In intermediate and large watersheds with wide channels and high stream discharges, heavy rainfall and subsequent floods regulate buoyant depth influencing the initiation of LW mobility, and thus control the amount of LW exported. In southern and central Japan, intense rainfall accompanying typhoons or localized torrential downpours lead to geomorphic disturbances, which produce massive amounts of LW delivery into channels. However, these pieces are constantly removed by high streamflows

Large scale CMB anomalies from thawing cosmic strings

Energy Technology Data Exchange (ETDEWEB)

Ringeval, Christophe [Centre for Cosmology, Particle Physics and Phenomenology, Institute of Mathematics and Physics, Louvain University, 2 Chemin du Cyclotron, 1348 Louvain-la-Neuve (Belgium); Yamauchi, Daisuke; Yokoyama, Jun' ichi [Research Center for the Early Universe (RESCEU), Graduate School of Science, The University of Tokyo, Tokyo 113-0033 (Japan); Bouchet, François R., E-mail: christophe.ringeval@uclouvain.be, E-mail: yamauchi@resceu.s.u-tokyo.ac.jp, E-mail: yokoyama@resceu.s.u-tokyo.ac.jp, E-mail: bouchet@iap.fr [Institut d' Astrophysique de Paris, UMR 7095-CNRS, Université Pierre et Marie Curie, 98bis boulevard Arago, 75014 Paris (France)

2016-02-01

Cosmic strings formed during inflation are expected to be either diluted over super-Hubble distances, i.e., invisible today, or to have crossed our past light cone very recently. We discuss the latter situation in which a few strings imprint their signature in the Cosmic Microwave Background (CMB) Anisotropies after recombination. Being almost frozen in the Hubble flow, these strings are quasi static and evade almost all of the previously derived constraints on their tension while being able to source large scale anisotropies in the CMB sky. Using a local variance estimator on thousand of numerically simulated Nambu-Goto all sky maps, we compute the expected signal and show that it can mimic a dipole modulation at large angular scales while being negligible at small angles. Interestingly, such a scenario generically produces one cold spot from the thawing of a cosmic string loop. Mixed with anisotropies of inflationary origin, we find that a few strings of tension GU = O(1) × 10{sup −6} match the amplitude of the dipole modulation reported in the Planck satellite measurements and could be at the origin of other large scale anomalies.

GAIA: A WINDOW TO LARGE-SCALE MOTIONS

Energy Technology Data Exchange (ETDEWEB)

Nusser, Adi [Physics Department and the Asher Space Science Institute-Technion, Haifa 32000 (Israel); Branchini, Enzo [Department of Physics, Universita Roma Tre, Via della Vasca Navale 84, 00146 Rome (Italy); Davis, Marc, E-mail: adi@physics.technion.ac.il, E-mail: branchin@fis.uniroma3.it, E-mail: mdavis@berkeley.edu [Departments of Astronomy and Physics, University of California, Berkeley, CA 94720 (United States)

2012-08-10

Using redshifts as a proxy for galaxy distances, estimates of the two-dimensional (2D) transverse peculiar velocities of distant galaxies could be obtained from future measurements of proper motions. We provide the mathematical framework for analyzing 2D transverse motions and show that they offer several advantages over traditional probes of large-scale motions. They are completely independent of any intrinsic relations between galaxy properties; hence, they are essentially free of selection biases. They are free from homogeneous and inhomogeneous Malmquist biases that typically plague distance indicator catalogs. They provide additional information to traditional probes that yield line-of-sight peculiar velocities only. Further, because of their 2D nature, fundamental questions regarding vorticity of large-scale flows can be addressed. Gaia, for example, is expected to provide proper motions of at least bright galaxies with high central surface brightness, making proper motions a likely contender for traditional probes based on current and future distance indicator measurements.

Large-scale grid management

International Nuclear Information System (INIS)

Langdal, Bjoern Inge; Eggen, Arnt Ove

2003-01-01

The network companies in the Norwegian electricity industry now have to establish a large-scale network management, a concept essentially characterized by (1) broader focus (Broad Band, Multi Utility,...) and (2) bigger units with large networks and more customers. Research done by SINTEF Energy Research shows so far that the approaches within large-scale network management may be structured according to three main challenges: centralization, decentralization and out sourcing. The article is part of a planned series

Occurrence Probabilities of Wet and Dry Periods in Southern Italy through the SPI Evaluated on Synthetic Monthly Precipitation Series

Directory of Open Access Journals (Sweden)

Tommaso Caloiero

2018-03-01

Full Text Available The present article investigates dry and wet periods in a large area of the Mediterranean basin. First, a stochastic model was applied to a homogeneous database of monthly precipitation values of 46 rain gauges in five regions of southern Italy. In particular, after estimating the model parameters, a set of 104 years of monthly precipitation for each rain gauge was generated by means of a Monte Carlo technique. Then, dry and wet periods were analyzed through the application of the standardized precipitation index (SPI over 3-month and 6-month timespan (short-term and 12-month and 24-month period (long-term. As a result of the SPI application on the generated monthly precipitation series, higher occurrence probabilities of dry conditions than wet conditions have been detected, especially when long-term precipitation scales are considered.

Magma viscosity estimation based on analysis of erupted products. Potential assessment for large-scale pyroclastic eruptions

International Nuclear Information System (INIS)

Takeuchi, Shingo

2010-01-01

After the formulation of guidelines for volcanic hazards in site evaluation for nuclear installations (e.g. JEAG4625-2009), it is required to establish appropriate methods to assess potential of large-scale pyroclastic eruptions at long-dormant volcanoes, which is one of the most hazardous volcanic phenomena on the safety of the installations. In considering the volcanic dormancy, magma eruptability is an important concept. The magma eruptability is dominantly controlled by magma viscosity, which can be estimated from petrological analysis of erupted materials. Therefore, viscosity estimation of magmas erupted in past eruptions should provide important information to assess future activities at hazardous volcanoes. In order to show the importance of magma viscosity in the concept of magma eruptability, this report overviews dike propagation processes from a magma chamber and nature of magma viscosity. Magma viscosity at pre-eruptive conditions of magma chambers were compiled based on previous petrological studies on past eruptions in Japan. There are only 16 examples of eruptions at 9 volcanoes satisfying data requirement for magma viscosity estimation. Estimated magma viscosities range from 10 2 to 10 7 Pa·s for basaltic to rhyolitic magmas. Most of examples fall below dike propagation limit of magma viscosity (ca. 10 6 Pa·s) estimated based on a dike propagation model. Highly viscous magmas (ca. 10 7 Pa·s) than the dike propagation limit are considered to lose eruptability which is the ability to form dikes and initiate eruptions. However, in some cases, small precursory eruptions of less viscous magmas commonly occurred just before climactic eruptions of the highly viscous magmas, suggesting that the precursory dike propagation by the less viscous magmas induced the following eruptions of highly viscous magmas (ca. 10 7 Pa·s). (author)

Mapping Precipitation in the Lower Mekong River Basin and the U.S. Affiliated Pacific Islands

Science.gov (United States)

Lakshmi, V.; Sutton, J. R. P.; Bolten, J. D.

2017-12-01

Mapping and quantifying precipitation across varying temporal and spatial scales is of utmost importance in understanding, monitoring, and predicting flooding and drought. While there exists many in-situ precipitation gages that can accurately estimate precipitation in a given location, there are still many areas that lack in-situ gages. Many of these locations do not have precipitation gages because they are rural and/or topographically complex. The purpose of our research was to compare different remotely sensed satellite precipitation estimates with in-situ estimates across topographically complex and rural terrain within the United States Affiliated Pacific Islands (USAPI) and the Lower Mekong River Basin (LMRB). We utilize the publicly available Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Climate Data Record (CDR) from NOAA and two remotely sensed precipitation products from NASA; the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM). These precipitation estimates were compared with each other and to the available in-situ precipitation estimates from station gages. We also utilize NASA Landsat data to determine the land cover types of these study areas. Using the precipitation estimates, topography, and the land cover of the study areas, we were able to show areas experiencing differing amounts of rainfall and their agreement with in-situ estimates. Additionally, we study the seasonal and spatial trends in precipitation. These analyses can be used to help understand areas that are experience frequent flood or drought.

Using a weather generator to downscale spatio-temporal precipitation at urban scale

DEFF Research Database (Denmark)

Sørup, Hjalte Jomo Danielsen; Christensen, Ole Bøssing; Arnbjerg-Nielsen, Karsten

In recent years, urban flooding has occurred in Denmark due to very local extreme precipitation events with very short lifetime. Several of these floods have been among the most severe ever experienced. The current study demonstrates the applicability of the Spatio-Temporal Neyman-Scott Rectangular...... the observed spatio-temporal differences at very fine scale for all measured parameters. For downscaling, perturbation with a climate change signal, precipitation from four different regional climate model simulations has been analysed. The analysed models are two runs from the ENSEMBLES (RACMO...

Evaluating the applicability of four recent satellite–gauge combined precipitation estimates for extreme precipitation and streamflow predictions over the upper Yellow river basin in China

Science.gov (United States)

This study aimed to statistically and hydrologically assess the performance of four latest and widely used satellite–gauge combined precipitation estimates (SGPEs), namely CRT, BLD, 3B42CDR, and 3B42 for the extreme precipitation and stream'ow scenarios over the upper Yellow river basin (UYRB) in ch...

Precipitation estimates and comparison of satellite rainfall data to in situ rain gauge observations to further develop the watershed-modeling capabilities for the Lower Mekong River Basin

Science.gov (United States)

Dandridge, C.; Lakshmi, V.; Sutton, J. R. P.; Bolten, J. D.

2017-12-01

This study focuses on the lower region of the Mekong River Basin (MRB), an area including Burma, Cambodia, Vietnam, Laos, and Thailand. This region is home to expansive agriculture that relies heavily on annual precipitation over the basin for its prosperity. Annual precipitation amounts are regulated by the global monsoon system and therefore vary throughout the year. This research will lead to improved prediction of floods and management of floodwaters for the MRB. We compare different satellite estimates of precipitation to each other and to in-situ precipitation estimates for the Mekong River Basin. These comparisons will help us determine which satellite precipitation estimates are better at predicting precipitation in the MRB and will help further our understanding of watershed-modeling capabilities for the basin. In this study we use: 1) NOAA's PERSIANN daily 0.25° precipitation estimate Climate Data Record (CDR), 2) NASA's Tropical Rainfall Measuring Mission (TRMM) daily 0.25° estimate, and 3) NASA's Global Precipitation Measurement (GPM) daily 0.1 estimate and 4) 488 in-situ stations located in the lower MRB provide daily precipitation estimates. The PERSIANN CDR precipitation estimate was able to provide the longest data record because it is available from 1983 to present. The TRMM precipitation estimate is available from 2000 to present and the GPM precipitation estimates are available from 2015 to present. It is for this reason that we provide several comparisons between our precipitation estimates. Comparisons were done between each satellite product and the in-situ precipitation estimates based on geographical location and date using the entire available data record for each satellite product for daily, monthly, and yearly precipitation estimates. We found that monthly PERSIANN precipitation estimates were able to explain up to 90% of the variability in station precipitation depending on station location.

Towards a Quantitative Use of Satellite Remote Sensing in Crop Growth Models for Large Scale Agricultural Production Estimate (Invited)

Science.gov (United States)

Defourny, P.

2013-12-01

The development of better agricultural monitoring capabilities is clearly considered as a critical step for strengthening food production information and market transparency thanks to timely information about crop status, crop area and yield forecasts. The documentation of global production will contribute to tackle price volatility by allowing local, national and international operators to make decisions and anticipate market trends with reduced uncertainty. Several operational agricultural monitoring systems are currently operating at national and international scales. Most are based on the methods derived from the pioneering experiences completed some decades ago, and use remote sensing to qualitatively compare one year to the others to estimate the risks of deviation from a normal year. The GEO Agricultural Monitoring Community of Practice described the current monitoring capabilities at the national and global levels. An overall diagram summarized the diverse relationships between satellite EO and agriculture information. There is now a large gap between the current operational large scale systems and the scientific state of the art in crop remote sensing, probably because the latter mainly focused on local studies. The poor availability of suitable in-situ and satellite data over extended areas hampers large scale demonstrations preventing the much needed up scaling research effort. For the cropland extent, this paper reports a recent research achievement using the full ENVISAT MERIS 300 m archive in the context of the ESA Climate Change Initiative. A flexible combination of classification methods depending to the region of the world allows mapping the land cover as well as the global croplands at 300 m for the period 2008 2012. This wall to wall product is then compared with regards to the FP 7-Geoland 2 results obtained using as Landsat-based sampling strategy over the IGADD countries. On the other hand, the vegetation indices and the biophysical variables

Global Precipitation Analyses at Time Scales of Monthly to 3-Hourly

Science.gov (United States)

Adler, Robert F.; Huffman, George; Curtis, Scott; Bolvin, David; Nelkin, Eric; Einaudi, Franco (Technical Monitor)

2002-01-01

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM (Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the Goodyear data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the Goodyear period. Monthly anomalies of precipitation are related to ENRON variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 degree latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is described. Finally, a TRMM-based Based analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous OR observations and merges the various calibrated observations into a final, Baehr resolution map. This TRMM standard product will be available for the entire TRMM period (January Represent). A real-time version of this merged product is being produced and is available at 0.25 degree latitude-longitude resolution over the latitude range from 50 deg. N -50 deg. S. Examples will be shown, including its use in monitoring flood conditions.

Near-real-time Estimation and Forecast of Total Precipitable Water in Europe

Science.gov (United States)

Bartholy, J.; Kern, A.; Barcza, Z.; Pongracz, R.; Ihasz, I.; Kovacs, R.; Ferencz, C.

2013-12-01

Information about the amount and spatial distribution of atmospheric water vapor (or total precipitable water) is essential for understanding weather and the environment including the greenhouse effect, the climate system with its feedbacks and the hydrological cycle. Numerical weather prediction (NWP) models need accurate estimations of water vapor content to provide realistic forecasts including representation of clouds and precipitation. In the present study we introduce our research activity for the estimation and forecast of atmospheric water vapor in Central Europe using both observations and models. The Eötvös Loránd University (Hungary) operates a polar orbiting satellite receiving station in Budapest since 2002. This station receives Earth observation data from polar orbiting satellites including MODerate resolution Imaging Spectroradiometer (MODIS) Direct Broadcast (DB) data stream from satellites Terra and Aqua. The received DB MODIS data are automatically processed using freely distributed software packages. Using the IMAPP Level2 software total precipitable water is calculated operationally using two different methods. Quality of the TPW estimations is a crucial question for further application of the results, thus validation of the remotely sensed total precipitable water fields is presented using radiosonde data. In a current research project in Hungary we aim to compare different estimations of atmospheric water vapor content. Within the frame of the project we use a NWP model (DBCRAS; Direct Broadcast CIMSS Regional Assimilation System numerical weather prediction software developed by the University of Wisconsin, Madison) to forecast TPW. DBCRAS uses near real time Level2 products from the MODIS data processing chain. From the wide range of the derived Level2 products the MODIS TPW parameter found within the so-called mod07 results (Atmospheric Profiles Product) and the cloud top pressure and cloud effective emissivity parameters from the so

Improvement of Hydrological Simulations by Applying Daily Precipitation Interpolation Schemes in Meso-Scale Catchments

Directory of Open Access Journals (Sweden)

Mateusz Szcześniak

2015-02-01

Full Text Available Ground-based precipitation data are still the dominant input type for hydrological models. Spatial variability in precipitation can be represented by spatially interpolating gauge data using various techniques. In this study, the effect of daily precipitation interpolation methods on discharge simulations using the semi-distributed SWAT (Soil and Water Assessment Tool model over a 30-year period is examined. The study was carried out in 11 meso-scale (119–3935 km2 sub-catchments lying in the Sulejów reservoir catchment in central Poland. Four methods were tested: the default SWAT method (Def based on the Nearest Neighbour technique, Thiessen Polygons (TP, Inverse Distance Weighted (IDW and Ordinary Kriging (OK. =The evaluation of methods was performed using a semi-automated calibration program SUFI-2 (Sequential Uncertainty Fitting Procedure Version 2 with two objective functions: Nash-Sutcliffe Efficiency (NSE and the adjusted R2 coefficient (bR2. The results show that: (1 the most complex OK method outperformed other methods in terms of NSE; and (2 OK, IDW, and TP outperformed Def in terms of bR2. The median difference in daily/monthly NSE between OK and Def/TP/IDW calculated across all catchments ranged between 0.05 and 0.15, while the median difference between TP/IDW/OK and Def ranged between 0.05 and 0.07. The differences between pairs of interpolation methods were, however, spatially variable and a part of this variability was attributed to catchment properties: catchments characterised by low station density and low coefficient of variation of daily flows experienced more pronounced improvement resulting from using interpolation methods. Methods providing higher precipitation estimates often resulted in a better model performance. The implication from this study is that appropriate consideration of spatial precipitation variability (often neglected by model users that can be achieved using relatively simple interpolation methods can

Strengthening effect of nano-scale precipitates in a die-cast Mg–4Al–5.6Sm–0.3Mn alloy

Energy Technology Data Exchange (ETDEWEB)

Yang, Qiang [State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022 (China); Bu, Fanqiang [State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Qiu, Xin [State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022 (China); Yangzhou Hongfu Aluminium Co. Ltd, Yangzhou 100049 (China); Li, Yangde; Li, Weirong [E-ande Scientific & Technology Co. Ltd, Dongguan 523000 (China); Sun, Wei [State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022 (China); Liu, Xiaojuan, E-mail: lxjuan@ciac.ac.cn [State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022 (China); Meng, Jian, E-mail: jmeng@ciac.jl.cn [State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022 (China)

2016-04-25

In this paper we report a quantitative study of the age-hardening in the high-pressure die-cast Mg–4Al−5.6Sm−0.3Mn alloy. The results indicate that a number of nano-scale spherical precipitates identified as Al{sub 3}Sm using high-angle annular dark-field scanning transmission electron microscopy, precipitated in Mg matrix after aging at 150–225 °C, with no obvious changes on grain sizes, intermetallic phases formed during solidification, and dislocation densities. From the existing strengthening theory equations in which some lacking parameters were taken from the first-principles density functional theory (DFT) calculations, a quantitative insight into the strengthening mechanisms of the nano-scale precipitate was formulated. The results are in reasonable agreement with the experimental values, and the operative mechanism of precipitation strengthening was revealed as Orowan dislocation bypassing. - Highlights: • The yield strength of Mg–Al–Sm alloy was improved by aging treatment. • A number of nano-scale precipitates formed in matrix after aging treatments. • The nanoscale precipitate was confirmed as Al{sub 3}Sm based on the data of HAADF-STEM study. • The strengthening mechanisms of the nano-scale precipitate were quantitatively formulated. • The operative mechanism of precipitate strengthening is Orowan dislocation bypassing.

Ethics of large-scale change

OpenAIRE

Arler, Finn

2006-01-01

  The subject of this paper is long-term large-scale changes in human society. Some very significant examples of large-scale change are presented: human population growth, human appropriation of land and primary production, the human use of fossil fuels, and climate change. The question is posed, which kind of attitude is appropriate when dealing with large-scale changes like these from an ethical point of view. Three kinds of approaches are discussed: Aldo Leopold's mountain thinking, th...

Statistical characterisation of COSMO Sky-Med X-SAR retrieved precipitation fields by scale-invariance analysis

Science.gov (United States)

Deidda, Roberto; Mascaro, Giuseppe; Hellies, Matteo; Baldini, Luca; Roberto, Nicoletta

2013-04-01

COSMO Sky-Med (CSK) is an important programme of the Italian Space Agency aiming at supporting environmental monitoring and management of exogenous, endogenous and anthropogenic risks through X-band Synthetic Aperture Radar (X-SAR) on board of 4 satellites forming a constellation. Most of typical SAR applications are focused on land or ocean observation. However, X-band SAR can be detect precipitation that results in a specific signature caused by the combination of attenuation of surface returns induced by precipitation and enhancement of backscattering determined by the hydrometeors in the SAR resolution volume. Within CSK programme, we conducted an intercomparison between the statistical properties of precipitation fields derived by CSK SARs and those derived by the CNR Polar 55C (C-band) ground based weather radar located in Rome (Italy). This contribution presents main results of this research which was aimed at the robust characterisation of rainfall statistical properties across different scales by means of scale-invariance analysis and multifractal theory. The analysis was performed on a dataset of more two years of precipitation observations collected by the CNR Polar 55C radar and rainfall fields derived from available images collected by the CSK satellites during intense rainfall events. Scale-invariance laws and multifractal properties were detected on the most intense rainfall events derived from the CNR Polar 55C radar for spatial scales from 4 km to 64 km. The analysis on X-SAR retrieved rainfall fields, although based on few images, leaded to similar results and confirmed the existence of scale-invariance and multifractal properties for scales larger than 4 km. These outcomes encourage investigating SAR methodologies for future development of meteo-hydrological forecasting models based on multifractal theory.

Scaling precipitation input to spatially distributed hydrological models by measured snow distribution

Directory of Open Access Journals (Sweden)

Christian Vögeli

2016-12-01

Full Text Available Accurate knowledge on snow distribution in alpine terrain is crucial for various applicationssuch as flood risk assessment, avalanche warning or managing water supply and hydro-power.To simulate the seasonal snow cover development in alpine terrain, the spatially distributed,physics-based model Alpine3D is suitable. The model is typically driven by spatial interpolationsof observations from automatic weather stations (AWS, leading to errors in the spatial distributionof atmospheric forcing. With recent advances in remote sensing techniques, maps of snowdepth can be acquired with high spatial resolution and accuracy. In this work, maps of the snowdepth distribution, calculated from summer and winter digital surface models based on AirborneDigital Sensors (ADS, are used to scale precipitation input data, with the aim to improve theaccuracy of simulation of the spatial distribution of snow with Alpine3D. A simple method toscale and redistribute precipitation is presented and the performance is analysed. The scalingmethod is only applied if it is snowing. For rainfall the precipitation is distributed by interpolation,with a simple air temperature threshold used for the determination of the precipitation phase.It was found that the accuracy of spatial snow distribution could be improved significantly forthe simulated domain. The standard deviation of absolute snow depth error is reduced up toa factor 3.4 to less than 20 cm. The mean absolute error in snow distribution was reducedwhen using representative input sources for the simulation domain. For inter-annual scaling, themodel performance could also be improved, even when using a remote sensing dataset from adifferent winter. In conclusion, using remote sensing data to process precipitation input, complexprocesses such as preferential snow deposition and snow relocation due to wind or avalanches,can be substituted and modelling performance of spatial snow distribution is improved.

Statistical evaluation of the performance of gridded monthly precipitation products from reanalysis data, satellite estimates, and merged analyses over China

Science.gov (United States)

Deng, Xueliang; Nie, Suping; Deng, Weitao; Cao, Weihua

2018-04-01

In this study, we compared the following four different gridded monthly precipitation products: the National Centers for Environmental Prediction version 2 (NCEP-2) reanalysis data, the satellite-based Climate Prediction Center Morphing technique (CMORPH) data, the merged satellite-gauge Global Precipitation Climatology Project (GPCP) data, and the merged satellite-gauge-model data from the Beijing Climate Center Merged Estimation of Precipitation (BMEP). We evaluated the performances of these products using monthly precipitation observations spanning the period of January 2003 to December 2013 from a dense, national, rain gauge network in China. Our assessment involved several statistical techniques, including spatial pattern, temporal variation, bias, root-mean-square error (RMSE), and correlation coefficient (CC) analysis. The results show that NCEP-2, GPCP, and BMEP generally overestimate monthly precipitation at the national scale and CMORPH underestimates it. However, all of the datasets successfully characterized the northwest to southeast increase in the monthly precipitation over China. Because they include precipitation gauge information from the Global Telecommunication System (GTS) network, GPCP and BMEP have much smaller biases, lower RMSEs, and higher CCs than NCEP-2 and CMORPH. When the seasonal and regional variations are considered, NCEP-2 has a larger error over southern China during the summer. CMORPH poorly reproduces the magnitude of the precipitation over southeastern China and the temporal correlation over western and northwestern China during all seasons. BMEP has a lower RMSE and higher CC than GPCP over eastern and southern China, where the station network is dense. In contrast, BMEP has a lower CC than GPCP over western and northwestern China, where the gauge network is relatively sparse.

Estimation of the impact of climate change-induced extreme precipitation events on floods

Science.gov (United States)

Hlavčová, Kamila; Lapin, Milan; Valent, Peter; Szolgay, Ján; Kohnová, Silvia; Rončák, Peter

2015-09-01

In order to estimate possible changes in the flood regime in the mountainous regions of Slovakia, a simple physically-based concept for climate change-induced changes in extreme 5-day precipitation totals is proposed in the paper. It utilizes regionally downscaled scenarios of the long-term monthly means of the air temperature, specific air humidity and precipitation projected for Central Slovakia by two regional (RCM) and two global circulation models (GCM). A simplified physically-based model for the calculation of short-term precipitation totals over the course of changing air temperatures, which is used to drive a conceptual rainfall-runoff model, was proposed. In the paper a case study of this approach in the upper Hron river basin in Central Slovakia is presented. From the 1981-2010 period, 20 events of the basin's most extreme average of 5-day precipitation totals were selected. Only events with continual precipitation during 5 days were considered. These 5-day precipitation totals were modified according to the RCM and GCM-based scenarios for the future time horizons of 2025, 2050 and 2075. For modelling runoff under changed 5-day precipitation totals, a conceptual rainfall-runoff model developed at the Slovak University of Technology was used. Changes in extreme mean daily discharges due to climate change were compared with the original flood events and discussed.

Seasonal Cycle in German Daily Precipitation Extremes

Directory of Open Access Journals (Sweden)

Madlen Fischer

2018-01-01

Full Text Available The seasonal cycle of extreme precipitation in Germany is investigated by fitting statistical models to monthly maxima of daily precipitation sums for 2,865 rain gauges. The basis is a non-stationary generalized extreme value (GEV distribution variation of location and scale parameters. The negative log-likelihood serves as the forecast error for a cross validation to select adequate orders of the harmonic functions for each station. For nearly all gauges considered, the seasonal model is more appropriate to estimate return levels on a monthly scale than a stationary GEV used for individual months. The 100-year return-levels show the influence of cyclones in the western, and convective events in the eastern part of Germany. In addition to resolving the seasonality, we use a simulation study to show that annual return levels can be estimated more precisely from a monthly-resolved seasonal model than from a stationary model based on annual maxima.

The spatial extent of rainfall events and its relation to precipitation scaling

NARCIS (Netherlands)

Lochbihler, K.U.; Lenderink, Geert; Siebesma, A.P.

2017-01-01

Observations show that subdaily precipitation extremes increase with dew point temperature at a rate exceeding the Clausius-Clapeyron (CC) relation. The understanding of this so-called super CC scaling is still incomplete, and observations of convective cell properties could provide important

Global estimate of lichen and bryophyte contributions to forest precipitation interception

Science.gov (United States)

Van Stan, John; Porada, Philipp; Kleidon, Axel

2017-04-01

Interception of precipitation by forest canopies plays an important role in its partitioning to evaporation, transpiration and runoff. Field observations show arboreal lichens and bryophytes can substantially enhance forests' precipitation storage and evaporation. However, representations of canopy interception in global land surface models currently ignore arboreal lichen and bryophyte contributions. This study uses the lichen and bryophyte model (LiBry) to provide the first process-based modelling approach estimating these organisms' contributions to canopy water storage and evaporation. The global mean value of forest water storage capacity increased significantly from 0.87 mm to 1.33 mm by the inclusion of arboreal poikilohydric organisms. Global forest canopy evaporation of intercepted precipitation was also greatly enhanced by 44%. Ratio of total versus bare canopy global evaporation exceeded 2 in many forested regions. This altered global patterns in canopy water storage, evaporation, and ultimately the proportion of rainfall evaporated. A sensitivity analysis was also performed. Results indicate rainfall interception is of larger magnitude than previously reported by global land surface modelling work because of the important role of lichen and bryophytes in rainfall interception.

Large-scale sequential quadratic programming algorithms

Energy Technology Data Exchange (ETDEWEB)

Eldersveld, S.K.

1992-09-01

The problem addressed is the general nonlinear programming problem: finding a local minimizer for a nonlinear function subject to a mixture of nonlinear equality and inequality constraints. The methods studied are in the class of sequential quadratic programming (SQP) algorithms, which have previously proved successful for problems of moderate size. Our goal is to devise an SQP algorithm that is applicable to large-scale optimization problems, using sparse data structures and storing less curvature information but maintaining the property of superlinear convergence. The main features are: 1. The use of a quasi-Newton approximation to the reduced Hessian of the Lagrangian function. Only an estimate of the reduced Hessian matrix is required by our algorithm. The impact of not having available the full Hessian approximation is studied and alternative estimates are constructed. 2. The use of a transformation matrix Q. This allows the QP gradient to be computed easily when only the reduced Hessian approximation is maintained. 3. The use of a reduced-gradient form of the basis for the null space of the working set. This choice of basis is more practical than an orthogonal null-space basis for large-scale problems. The continuity condition for this choice is proven. 4. The use of incomplete solutions of quadratic programming subproblems. Certain iterates generated by an active-set method for the QP subproblem are used in place of the QP minimizer to define the search direction for the nonlinear problem. An implementation of the new algorithm has been obtained by modifying the code MINOS. Results and comparisons with MINOS and NPSOL are given for the new algorithm on a set of 92 test problems.

Fan-out Estimation in Spin-based Quantum Computer Scale-up.

Science.gov (United States)

Nguyen, Thien; Hill, Charles D; Hollenberg, Lloyd C L; James, Matthew R

2017-10-17

Solid-state spin-based qubits offer good prospects for scaling based on their long coherence times and nexus to large-scale electronic scale-up technologies. However, high-threshold quantum error correction requires a two-dimensional qubit array operating in parallel, posing significant challenges in fabrication and control. While architectures incorporating distributed quantum control meet this challenge head-on, most designs rely on individual control and readout of all qubits with high gate densities. We analysed the fan-out routing overhead of a dedicated control line architecture, basing the analysis on a generalised solid-state spin qubit platform parameterised to encompass Coulomb confined (e.g. donor based spin qubits) or electrostatically confined (e.g. quantum dot based spin qubits) implementations. The spatial scalability under this model is estimated using standard electronic routing methods and present-day fabrication constraints. Based on reasonable assumptions for qubit control and readout we estimate 10 2 -10 5 physical qubits, depending on the quantum interconnect implementation, can be integrated and fanned-out independently. Assuming relatively long control-free interconnects the scalability can be extended. Ultimately, the universal quantum computation may necessitate a much higher number of integrated qubits, indicating that higher dimensional electronics fabrication and/or multiplexed distributed control and readout schemes may be the preferredstrategy for large-scale implementation.

Large-scale nuclear energy from the thorium cycle

International Nuclear Information System (INIS)

Lewis, W.B.; Duret, M.F.; Craig, D.S.; Veeder, J.I.; Bain, A.S.

1973-02-01

The thorium fuel cycle in CANDU (Canada Deuterium Uranium) reactors challenges breeders and fusion as the simplest means of meeting the world's large-scale demands for energy for centuries. Thorium oxide fuel allows high power density with excellent neutron economy. The combination of thorium fuel with organic caloporteur promises easy maintenance and high availability of the whole plant. The total fuelling cost including charges on the inventory is estimated to be attractively low. (author) [fr

Assessing the uncertainty of soil moisture impacts on convective precipitation using a new ensemble approach

Directory of Open Access Journals (Sweden)

O. Henneberg

2018-05-01

Full Text Available Soil moisture amount and distribution control evapotranspiration and thus impact the occurrence of convective precipitation. Many recent model studies demonstrate that changes in initial soil moisture content result in modified convective precipitation. However, to quantify the resulting precipitation changes, the chaotic behavior of the atmospheric system needs to be considered. Slight changes in the simulation setup, such as the chosen model domain, also result in modifications to the simulated precipitation field. This causes an uncertainty due to stochastic variability, which can be large compared to effects caused by soil moisture variations. By shifting the model domain, we estimate the uncertainty of the model results. Our novel uncertainty estimate includes 10 simulations with shifted model boundaries and is compared to the effects on precipitation caused by variations in soil moisture amount and local distribution. With this approach, the influence of soil moisture amount and distribution on convective precipitation is quantified. Deviations in simulated precipitation can only be attributed to soil moisture impacts if the systematic effects of soil moisture modifications are larger than the inherent simulation uncertainty at the convection-resolving scale.We performed seven experiments with modified soil moisture amount or distribution to address the effect of soil moisture on precipitation. Each of the experiments consists of 10 ensemble members using the deep convection-resolving COSMO model with a grid spacing of 2.8 km. Only in experiments with very strong modification in soil moisture do precipitation changes exceed the model spread in amplitude, location or structure. These changes are caused by a 50 % soil moisture increase in either the whole or part of the model domain or by drying the whole model domain. Increasing or decreasing soil moisture both predominantly results in reduced precipitation rates. Replacing the soil

Long range transport of air pollutants in Europe and acid precipitation in Norway

Science.gov (United States)

Jack Nordo

1976-01-01

Observations show that pollutants from large emission sources may cause significant air concentrations 500 to 1000 miles away. Very acid precipitation occurs in such periods. The scavenging is often intensified by the topography. Case studies will be presented, with special emphasis on acid precipitation in Scandinavia. Large scale dispersion models have been developed...

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

Science.gov (United States)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is

Regional-scale relationships between aerosol and summer monsoon circulation, and precipitation over northeast Asia

Science.gov (United States)

Yoon, Soon-Chang; Kim, Sang-Woo; Choi, Suk-Jin; Choi, In-Jin

2010-08-01

We investigated the regional-scale relationships between columnar aerosol loads and summer monsoon circulation, and also the precipitation over northeast Asia using aerosol optical depth (AOD) data obtained from the 8-year MODIS, AERONET Sun/sky radiometer, and precipitation data acquired under the Global Precipitation Climatology Project (GPCP). These high-quality data revealed the regional-scale link between AOD and summer monsoon circulation, precipitation in July over northeast Asian countries, and their distinct spatial and annual variabilities. Compared to the mean AOD for the entire period of 2001-2008, the increase of almost 40-50% in the AOD value in July 2005 and July 2007 was found over the downwind regions of China (Yellow Sea, Korean peninsula, and East Sea), with negative precipitation anomalies. This can be attributable to the strong westerly confluent flows, between cyclone flows by continental thermal low centered over the northern China and anticyclonic flows by the western North Pacific High, which transport anthropogenic pollution aerosols emitted from east China to aforementioned downwind high AOD regions along the rim of the Pacific marine airmass. In July 2002, however, the easterly flows transported anthropogenic aerosols from east China to the southwestern part of China in July 2002. As a result, the AOD off the coast of China was dramatically reduced in spite of decreasing rainfall. From the calculation of the cross-correlation coefficient between MODIS-derived AOD anomalies and GPCP precipitation anomalies in July over the period 2001-2008, we found negative correlations over the areas encompassed by 105-115°E and 30-35°N and by 120-140°E and 35-40°N (Yellow Sea, Korean peninsula, and East Sea). This suggests that aerosol loads over these regions are easily influenced by the Asian monsoon flow system and associated precipitation.

Development of a methodology for probable maximum precipitation estimation over the American River watershed using the WRF model

Science.gov (United States)

Tan, Elcin

A new physically-based methodology for probable maximum precipitation (PMP) estimation is developed over the American River Watershed (ARW) using the Weather Research and Forecast (WRF-ARW) model. A persistent moisture flux convergence pattern, called Pineapple Express, is analyzed for 42 historical extreme precipitation events, and it is found that Pineapple Express causes extreme precipitation over the basin of interest. An average correlation between moisture flux convergence and maximum precipitation is estimated as 0.71 for 42 events. The performance of the WRF model is verified for precipitation by means of calibration and independent validation of the model. The calibration procedure is performed only for the first ranked flood event 1997 case, whereas the WRF model is validated for 42 historical cases. Three nested model domains are set up with horizontal resolutions of 27 km, 9 km, and 3 km over the basin of interest. As a result of Chi-square goodness-of-fit tests, the hypothesis that "the WRF model can be used in the determination of PMP over the ARW for both areal average and point estimates" is accepted at the 5% level of significance. The sensitivities of model physics options on precipitation are determined using 28 microphysics, atmospheric boundary layer, and cumulus parameterization schemes combinations. It is concluded that the best triplet option is Thompson microphysics, Grell 3D ensemble cumulus, and YSU boundary layer (TGY), based on 42 historical cases, and this TGY triplet is used for all analyses of this research. Four techniques are proposed to evaluate physically possible maximum precipitation using the WRF: 1. Perturbations of atmospheric conditions; 2. Shift in atmospheric conditions; 3. Replacement of atmospheric conditions among historical events; and 4. Thermodynamically possible worst-case scenario creation. Moreover, climate change effect on precipitation is discussed by emphasizing temperature increase in order to determine the

Political consultation and large-scale research

International Nuclear Information System (INIS)

Bechmann, G.; Folkers, H.

1977-01-01

Large-scale research and policy consulting have an intermediary position between sociological sub-systems. While large-scale research coordinates science, policy, and production, policy consulting coordinates science, policy and political spheres. In this very position, large-scale research and policy consulting lack of institutional guarantees and rational back-ground guarantee which are characteristic for their sociological environment. This large-scale research can neither deal with the production of innovative goods under consideration of rentability, nor can it hope for full recognition by the basis-oriented scientific community. Policy consulting knows neither the competence assignment of the political system to make decisions nor can it judge succesfully by the critical standards of the established social science, at least as far as the present situation is concerned. This intermediary position of large-scale research and policy consulting has, in three points, a consequence supporting the thesis which states that this is a new form of institutionalization of science: These are: 1) external control, 2) the organization form, 3) the theoretical conception of large-scale research and policy consulting. (orig.) [de

On identifying relationships between the flood scaling exponent and basin attributes.

Science.gov (United States)

Medhi, Hemanta; Tripathi, Shivam

2015-07-01

Floods are known to exhibit self-similarity and follow scaling laws that form the basis of regional flood frequency analysis. However, the relationship between basin attributes and the scaling behavior of floods is still not fully understood. Identifying these relationships is essential for drawing connections between hydrological processes in a basin and the flood response of the basin. The existing studies mostly rely on simulation models to draw these connections. This paper proposes a new methodology that draws connections between basin attributes and the flood scaling exponents by using observed data. In the proposed methodology, region-of-influence approach is used to delineate homogeneous regions for each gaging station. Ordinary least squares regression is then applied to estimate flood scaling exponents for each homogeneous region, and finally stepwise regression is used to identify basin attributes that affect flood scaling exponents. The effectiveness of the proposed methodology is tested by applying it to data from river basins in the United States. The results suggest that flood scaling exponent is small for regions having (i) large abstractions from precipitation in the form of large soil moisture storages and high evapotranspiration losses, and (ii) large fractions of overland flow compared to base flow, i.e., regions having fast-responding basins. Analysis of simple scaling and multiscaling of floods showed evidence of simple scaling for regions in which the snowfall dominates the total precipitation.

Doubly stochastic Poisson process models for precipitation at fine time-scales

Science.gov (United States)

Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao

2012-09-01

This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.

Robust Visual Tracking Using the Bidirectional Scale Estimation

Directory of Open Access Journals (Sweden)

An Zhiyong

2017-01-01

Full Text Available Object tracking with robust scale estimation is a challenging task in computer vision. This paper presents a novel tracking algorithm that learns the translation and scale filters with a complementary scheme. The translation filter is constructed using the ridge regression and multidimensional features. A robust scale filter is constructed by the bidirectional scale estimation, including the forward scale and backward scale. Firstly, we learn the scale filter using the forward tracking information. Then the forward scale and backward scale can be estimated using the respective scale filter. Secondly, a conservative strategy is adopted to compromise the forward and backward scales. Finally, the scale filter is updated based on the final scale estimation. It is effective to update scale filter since the stable scale estimation can improve the performance of scale filter. To reveal the effectiveness of our tracker, experiments are performed on 32 sequences with significant scale variation and on the benchmark dataset with 50 challenging videos. Our results show that the proposed tracker outperforms several state-of-the-art trackers in terms of robustness and accuracy.

Large-scale multimedia modeling applications

International Nuclear Information System (INIS)

Droppo, J.G. Jr.; Buck, J.W.; Whelan, G.; Strenge, D.L.; Castleton, K.J.; Gelston, G.M.

1995-08-01

Over the past decade, the US Department of Energy (DOE) and other agencies have faced increasing scrutiny for a wide range of environmental issues related to past and current practices. A number of large-scale applications have been undertaken that required analysis of large numbers of potential environmental issues over a wide range of environmental conditions and contaminants. Several of these applications, referred to here as large-scale applications, have addressed long-term public health risks using a holistic approach for assessing impacts from potential waterborne and airborne transport pathways. Multimedia models such as the Multimedia Environmental Pollutant Assessment System (MEPAS) were designed for use in such applications. MEPAS integrates radioactive and hazardous contaminants impact computations for major exposure routes via air, surface water, ground water, and overland flow transport. A number of large-scale applications of MEPAS have been conducted to assess various endpoints for environmental and human health impacts. These applications are described in terms of lessons learned in the development of an effective approach for large-scale applications

Recent advances in precipitation-bias correction and application

Institute of Scientific and Technical Information of China (English)

无

2009-01-01

Significant progresses have been made in recent years in precipitation data analyses at regional to global scales. This paper re-views and synthesizes recent advances in precipitation-bias corrections and applications in many countries and over the cold re-gions. The main objective of this review is to identify and examine gaps in regional and national precipitation-error analyses. This paper also discusses and recommends future research needs and directions. More effort and coordination are necessary in the determinations of precipitation biases on large regions across national borders. It is important to emphasize that bias cor-rections of precipitation measurements affect both water budget and energy balance calculations, particularly over the cold regions.

Assimilating Non-linear Effects of Customized Large-Scale Climate Predictors on Downscaled Precipitation over the Tropical Andes

Science.gov (United States)

Molina, J. M.; Zaitchik, B. F.

2016-12-01

Recent findings considering high CO2 emission scenarios (RCP8.5) suggest that the tropical Andes may experience a massive warming and a significant precipitation increase (decrease) during the wet (dry) seasons by the end of the 21st century. Variations on rainfall-streamflow relationships and seasonal crop yields significantly affect human development in this region and make local communities highly vulnerable to climate change and variability. We developed an expert-informed empirical statistical downscaling (ESD) algorithm to explore and construct robust global climate predictors to perform skillful RCP8.5 projections of in-situ March-May (MAM) precipitation required for impact modeling and adaptation studies. We applied our framework to a topographically-complex region of the Colombian Andes where a number of previous studies have reported El Niño-Southern Oscillation (ENSO) as the main driver of climate variability. Supervised machine learning algorithms were trained with customized and bias-corrected predictors from NCEP reanalysis, and a cross-validation approach was implemented to assess both predictive skill and model selection. We found weak and not significant teleconnections between precipitation and lagged seasonal surface temperatures over El Niño3.4 domain, which suggests that ENSO fails to explain MAM rainfall variability in the study region. In contrast, series of Sea Level Pressure (SLP) over American Samoa -likely associated with the South Pacific Convergence Zone (SPCZ)- explains more than 65% of the precipitation variance. The best prediction skill was obtained with Selected Generalized Additive Models (SGAM) given their ability to capture linear/nonlinear relationships present in the data. While SPCZ-related series exhibited a positive linear effect in the rainfall response, SLP predictors in the north Atlantic and central equatorial Pacific showed nonlinear effects. A multimodel (MIROC, CanESM2 and CCSM) ensemble of ESD projections revealed

Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

Science.gov (United States)

Hong, Yang; Adler, Robert F.; Huffman, George J.; Pierce, Harold

2008-01-01

Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

Synoptic Disturbances Found in Precipitable Water Fields North of Equatorial Africa

National Research Council Canada - National Science Library

Patla, Jason

1999-01-01

The origin and structure of tropical synoptic scale precipitable water (PW) anomalies estimated from TOVS satellite observations are analyzed as they propagate eastward across northern Africa during MAM 1988...

Impact of large-scale tides on cosmological distortions via redshift-space power spectrum

Science.gov (United States)

Akitsu, Kazuyuki; Takada, Masahiro

2018-03-01

Although large-scale perturbations beyond a finite-volume survey region are not direct observables, these affect measurements of clustering statistics of small-scale (subsurvey) perturbations in large-scale structure, compared with the ensemble average, via the mode-coupling effect. In this paper we show that a large-scale tide induced by scalar perturbations causes apparent anisotropic distortions in the redshift-space power spectrum of galaxies in a way depending on an alignment between the tide, wave vector of small-scale modes and line-of-sight direction. Using the perturbation theory of structure formation, we derive a response function of the redshift-space power spectrum to large-scale tide. We then investigate the impact of large-scale tide on estimation of cosmological distances and the redshift-space distortion parameter via the measured redshift-space power spectrum for a hypothetical large-volume survey, based on the Fisher matrix formalism. To do this, we treat the large-scale tide as a signal, rather than an additional source of the statistical errors, and show that a degradation in the parameter is restored if we can employ the prior on the rms amplitude expected for the standard cold dark matter (CDM) model. We also discuss whether the large-scale tide can be constrained at an accuracy better than the CDM prediction, if the effects up to a larger wave number in the nonlinear regime can be included.

Biofuel Development and Large-Scale Land Deals in Sub-Saharan Africa

OpenAIRE

Giorgia Giovannetti; Elisa Ticci

2013-01-01

Africa's biofuel potential over the last ten years has increasingly attracted foreign investors’ attention. We estimate the determinants of foreign investors land demand for biofuel production in SSA, using Poisson specifications of the gravity model. Our estimates suggest that land availability, abundance of water resources and weak land governance are significant determinants of large-scale land acquisitions for biofuel production. This in turn suggests that this type of investment is mainl...

Global and exponential attractors of the three dimensional viscous primitive equations of large-scale moist atmosphere

OpenAIRE

You, Bo; Li, Fang

2016-01-01

This paper is concerned with the long-time behavior of solutions for the three dimensional viscous primitive equations of large-scale moist atmosphere. We prove the existence of a global attractor for the three dimensional viscous primitive equations of large-scale moist atmosphere by asymptotic a priori estimate and construct an exponential attractor by using the smoothing property of the semigroup generated by the three dimensional viscous primitive equations of large-scale moist atmosphere...

Optimized Large-scale CMB Likelihood and Quadratic Maximum Likelihood Power Spectrum Estimation

Science.gov (United States)

Gjerløw, E.; Colombo, L. P. L.; Eriksen, H. K.; Górski, K. M.; Gruppuso, A.; Jewell, J. B.; Plaszczynski, S.; Wehus, I. K.

2015-11-01

We revisit the problem of exact cosmic microwave background (CMB) likelihood and power spectrum estimation with the goal of minimizing computational costs through linear compression. This idea was originally proposed for CMB purposes by Tegmark et al., and here we develop it into a fully functioning computational framework for large-scale polarization analysis, adopting WMAP as a working example. We compare five different linear bases (pixel space, harmonic space, noise covariance eigenvectors, signal-to-noise covariance eigenvectors, and signal-plus-noise covariance eigenvectors) in terms of compression efficiency, and find that the computationally most efficient basis is the signal-to-noise eigenvector basis, which is closely related to the Karhunen-Loeve and Principal Component transforms, in agreement with previous suggestions. For this basis, the information in 6836 unmasked WMAP sky map pixels can be compressed into a smaller set of 3102 modes, with a maximum error increase of any single multipole of 3.8% at ℓ ≤ 32 and a maximum shift in the mean values of a joint distribution of an amplitude-tilt model of 0.006σ. This compression reduces the computational cost of a single likelihood evaluation by a factor of 5, from 38 to 7.5 CPU seconds, and it also results in a more robust likelihood by implicitly regularizing nearly degenerate modes. Finally, we use the same compression framework to formulate a numerically stable and computationally efficient variation of the Quadratic Maximum Likelihood implementation, which requires less than 3 GB of memory and 2 CPU minutes per iteration for ℓ ≤ 32, rendering low-ℓ QML CMB power spectrum analysis fully tractable on a standard laptop.

Decentralized Large-Scale Power Balancing

DEFF Research Database (Denmark)

Halvgaard, Rasmus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad

2013-01-01

problem is formulated as a centralized large-scale optimization problem but is then decomposed into smaller subproblems that are solved locally by each unit connected to an aggregator. For large-scale systems the method is faster than solving the full problem and can be distributed to include an arbitrary...

A Simple Sampling Method for Estimating the Accuracy of Large Scale Record Linkage Projects.

Science.gov (United States)

Boyd, James H; Guiver, Tenniel; Randall, Sean M; Ferrante, Anna M; Semmens, James B; Anderson, Phil; Dickinson, Teresa

2016-05-17

Record linkage techniques allow different data collections to be brought together to provide a wider picture of the health status of individuals. Ensuring high linkage quality is important to guarantee the quality and integrity of research. Current methods for measuring linkage quality typically focus on precision (the proportion of incorrect links), given the difficulty of measuring the proportion of false negatives. The aim of this work is to introduce and evaluate a sampling based method to estimate both precision and recall following record linkage. In the sampling based method, record-pairs from each threshold (including those below the identified cut-off for acceptance) are sampled and clerically reviewed. These results are then applied to the entire set of record-pairs, providing estimates of false positives and false negatives. This method was evaluated on a synthetically generated dataset, where the true match status (which records belonged to the same person) was known. The sampled estimates of linkage quality were relatively close to actual linkage quality metrics calculated for the whole synthetic dataset. The precision and recall measures for seven reviewers were very consistent with little variation in the clerical assessment results (overall agreement using the Fleiss Kappa statistics was 0.601). This method presents as a possible means of accurately estimating matching quality and refining linkages in population level linkage studies. The sampling approach is especially important for large project linkages where the number of record pairs produced may be very large often running into millions.

Steps toward a CONUS-wide reanalysis with archived NEXRAD data using National Mosaic and Multisensor Quantitative Precipitation Estimation (NMQ/Q2) algorithms

Science.gov (United States)

Stevens, S. E.; Nelson, B. R.; Langston, C.; Qi, Y.

2012-12-01

The National Mosaic and Multisensor QPE (NMQ/Q2) software suite, developed at NOAA's National Severe Storms Laboratory (NSSL) in Norman, OK, addresses a large deficiency in the resolution of currently archived precipitation datasets. Current standards, both radar- and satellite-based, provide for nationwide precipitation data with a spatial resolution of up to 4-5 km, with a temporal resolution as fine as one hour. Efforts are ongoing to process archived NEXRAD data for the period of record (1996 - present), producing a continuous dataset providing precipitation data at a spatial resolution of 1 km, on a timescale of only five minutes. In addition, radar-derived precipitation data are adjusted hourly using a wide variety of automated gauge networks spanning the United States. Applications for such a product range widely, from emergency management and flash flood guidance, to hydrological studies and drought monitoring. Results are presented from a subset of the NEXRAD dataset, providing basic statistics on the distribution of rainrates, relative frequency of precipitation types, and several other variables which demonstrate the variety of output provided by the software. Precipitation data from select case studies are also presented to highlight the increased resolution provided by this reanalysis and the possibilities that arise from the availability of data on such fine scales. A previously completed pilot project and steps toward a nationwide implementation are presented along with proposed strategies for managing and processing such a large dataset. Reprocessing efforts span several institutions in both North Carolina and Oklahoma, and data/software coordination are key in producing a homogeneous record of precipitation to be archived alongside NOAA's other Climate Data Records. Methods are presented for utilizing supercomputing capability in expediting processing, to allow for the iterative nature of a reanalysis effort.

Improving snow water equivalent simulations in an alpine basin using blended gage precipitation and snow pillow measurements

Science.gov (United States)

Sohrabi, M.; Safeeq, M.; Conklin, M. H.

2017-12-01

Snowpack is a critical freshwater reservoir that sustains ecosystem, natural habitat, hydropower, agriculture, and urban water supply in many areas around the world. Accurate estimation of basin scale snow water equivalent (SWE), through both measurement and modeling, has been significantly recognized to improve regional water resource management. Recent advances in remote data acquisition techniques have improved snow measurements but our ability to model snowpack evolution is largely hampered by poor knowledge of inherently variable high-elevation precipitation patterns. For a variety of reasons, majority of the precipitation gages are located in low and mid-elevation range and function as drivers for basin scale hydrologic modeling. Here, we blend observed gage precipitation from low and mid-elevation with point observations of SWE from high-elevation snow pillow into a physically based snow evolution model (SnowModel) to better represent the basin-scale precipitation field and improve snow simulations. To do this, we constructed two scenarios that differed in only precipitation. In WTH scenario, we forced the SnowModel using spatially distributed gage precipitation data. In WTH+SP scenario, the model was forced with spatially distributed precipitation data derived from gage precipitation along with observed precipitation from snow pillows. Since snow pillows do not directly measure precipitation, we uses positive change in SWE as a proxy for precipitation. The SnowModel was implemented at daily time step and 100 m resolution for the Kings River Basin, USA over 2000-2014. Our results show an improvement in snow simulation under WTH+SP as compared to WTH scenario, which can be attributed to better representation in high-elevation precipitation patterns under WTH+SP. The average Nash Sutcliffe efficiency over all snow pillow and course sites was substantially higher for WTH+SP (0.77) than for WTH scenario (0.47). The maximum difference in observed and simulated

Advances in Understanding the Role of Frozen Precipitation in High Latitude Hydrology

Science.gov (United States)

L'Ecuyer, T. S.; Wood, N.; Smalley, M.; McIlhattan, E.; Kulie, M.

2017-12-01

Satellite-based millimeter wavelength radar observations provide a unique perspective on the global character of frozen precipitation that has been difficult to detect using conventional spaceborne precipitation sensors. This presentation will describe the methodology underpinning the ten-year CloudSat global snowfall product and discuss the results of a number of complementary approaches that have been adopted to quantify its uncertainties. These datasets are shedding new light on the distribution, character, and impacts of frozen precipitation on high latitude hydrology. Inferred regional snowfall accumulations, for example, provide valuable constraints on projected changes in precipitation and mass balance on the Antarctic ice sheet in climate models. When placed in the broader context of complementary observations from other A-Train sensors, instantaneous snowfall estimates also hint at the large-scale processes that influence snow formation including air-sea interactions associated with cold-air outbreaks, lake-effect snows, and orographic enhancement. Simultaneous CloudSat and CALIPSO observations further emphasize the important role snowfall plays in the lifetime of super-cooled liquid containing clouds in the Arctic and highlight a model deficiency with important implications for surface energy and mass balance on the Greenland ice sheet.

New method to estimate paleoprecipitation using fossil amphibians and reptiles and the middle and late Miocene precipitation gradients in Europe

Science.gov (United States)

Böhme, M.; Ilg, A.; Ossig, A.; Küchenhoff, H.

2006-06-01

Existing methods for determining paleoprecipitation are subject to large errors (±350 400 mm or more using mammalian proxies), or are restricted to wet climate systems due to their strong facies dependence (paleobotanical proxies). Here we describe a new paleoprecipitation tool based on an indexing of ecophysiological groups within herpetological communities. In recent communities these indices show a highly significant correlation to annual precipitation (r2 = 0.88), and yield paleoprecipitation estimates with average errors of ±250 280 mm. The approach was validated by comparison with published paleoprecipitation estimates from other methods. The method expands the application of paleoprecipitation tools to dry climate systems and in this way contributes to the establishment of a more comprehensive paleoprecipitation database. This method is applied to two high-resolution time intervals from the European Neogene: the early middle Miocene (early Langhian) and the early late Miocene (early Tortonian). The results indicate that both periods show significant meridional precipitation gradients in Europe, these being stronger in the early Langhian (threefold decrease toward the south) than in the early Tortonian (twofold decrease toward the south). This pattern indicates a strengthening of climatic belts during the middle Miocene climatic optimum due to Southern Hemisphere cooling and an increased contribution of Arctic low-pressure cells to the precipitation from the late Miocene onward due to Northern Hemisphere cooling.

The effect of the geomagnetic field on cosmic ray energy estimates and large scale anisotropy searches on data from the Pierre Auger Observatory

Energy Technology Data Exchange (ETDEWEB)

Abreu, P.; /Lisbon, IST; Aglietta, M.; /IFSI, Turin; Ahn, E.J.; /Fermilab; Albuquerque, I.F.M.; /Sao Paulo U.; Allard, D.; /APC, Paris; Allekotte, I.; /Centro Atomico Bariloche; Allen, J.; /New York U.; Allison, P.; /Ohio State U.; Alvarez Castillo, J.; /Mexico U., ICN; Alvarez-Muniz, J.; /Santiago de Compostela U.; Ambrosio, M.; /Naples U. /INFN, Naples /Nijmegen U., IMAPP

2011-11-01

We present a comprehensive study of the influence of the geomagnetic field on the energy estimation of extensive air showers with a zenith angle smaller than 60{sup o}, detected at the Pierre Auger Observatory. The geomagnetic field induces an azimuthal modulation of the estimated energy of cosmic rays up to the {approx} 2% level at large zenith angles. We present a method to account for this modulation of the reconstructed energy. We analyse the effect of the modulation on large scale anisotropy searches in the arrival direction distributions of cosmic rays. At a given energy, the geomagnetic effect is shown to induce a pseudo-dipolar pattern at the percent level in the declination distribution that needs to be accounted for. In this work, we have identified and quantified a systematic uncertainty affecting the energy determination of cosmic rays detected by the surface detector array of the Pierre Auger Observatory. This systematic uncertainty, induced by the influence of the geomagnetic field on the shower development, has a strength which depends on both the zenith and the azimuthal angles. Consequently, we have shown that it induces distortions of the estimated cosmic ray event rate at a given energy at the percent level in both the azimuthal and the declination distributions, the latter of which mimics an almost dipolar pattern. We have also shown that the induced distortions are already at the level of the statistical uncertainties for a number of events N {approx_equal} 32 000 (we note that the full Auger surface detector array collects about 6500 events per year with energies above 3 EeV). Accounting for these effects is thus essential with regard to the correct interpretation of large scale anisotropy measurements taking explicitly profit from the declination distribution.

Automating large-scale reactor systems

International Nuclear Information System (INIS)

Kisner, R.A.

1985-01-01

This paper conveys a philosophy for developing automated large-scale control systems that behave in an integrated, intelligent, flexible manner. Methods for operating large-scale systems under varying degrees of equipment degradation are discussed, and a design approach that separates the effort into phases is suggested. 5 refs., 1 fig

Sustainability Risk Evaluation for Large-Scale Hydropower Projects with Hybrid Uncertainty

Directory of Open Access Journals (Sweden)

Weiyao Tang

2018-01-01

Full Text Available As large-scale hydropower projects are influenced by many factors, risk evaluations are complex. This paper considers a hydropower project as a complex system from the perspective of sustainability risk, and divides it into three subsystems: the natural environment subsystem, the eco-environment subsystem and the socioeconomic subsystem. Risk-related factors and quantitative dimensions of each subsystem are comprehensively analyzed considering uncertainty of some quantitative dimensions solved by hybrid uncertainty methods, including fuzzy (e.g., the national health degree, the national happiness degree, the protection of cultural heritage, random (e.g., underground water levels, river width, and fuzzy random uncertainty (e.g., runoff volumes, precipitation. By calculating the sustainability risk-related degree in each of the risk-related factors, a sustainable risk-evaluation model is built. Based on the calculation results, the critical sustainability risk-related factors are identified and targeted to reduce the losses caused by sustainability risk factors of the hydropower project. A case study at the under-construction Baihetan hydropower station is presented to demonstrate the viability of the risk-evaluation model and to provide a reference for the sustainable risk evaluation of other large-scale hydropower projects.

Estimating Amazonian rainforest stability and the likelihood for large-scale forest dieback

Science.gov (United States)

Rammig, Anja; Thonicke, Kirsten; Jupp, Tim; Ostberg, Sebastian; Heinke, Jens; Lucht, Wolfgang; Cramer, Wolfgang; Cox, Peter

2010-05-01

Annually, tropical forests process approximately 18 Pg of carbon through respiration and photosynthesis - more than twice the rate of anthropogenic fossil fuel emissions. Current climate change may be transforming this carbon sink into a carbon source by changing forest structure and dynamics. Increasing temperatures and potentially decreasing precipitation and thus prolonged drought stress may lead to increasing physiological stress and reduced productivity for trees. Resulting decreases in evapotranspiration and therefore convective precipitation could further accelerate drought conditions and destabilize the tropical ecosystem as a whole and lead to an 'Amazon forest dieback'. The projected direction and intensity of climate change vary widely within the region and between different scenarios from climate models (GCMs). In the scope of a World Bank-funded study, we assessed the 24 General Circulation Models (GCMs) evaluated in the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4) with respect to their capability to reproduce present-day climate in the Amazon basin using a Bayesian approach. With this approach, greater weight is assigned to the models that simulate well the annual cycle of rainfall. We then use the resulting weightings to create probability density functions (PDFs) for future forest biomass changes as simulated by the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJmL) to estimate the risk of potential Amazon rainforest dieback. Our results show contrasting changes in forest biomass throughout five regions of northern South America: If photosynthetic capacity and water use efficiency is enhanced by CO2, biomass increases across all five regions. However, if CO2-fertilisation is assumed to be absent or less important, then substantial dieback occurs in some scenarios and thus, the risk of forest dieback is considerably higher. Particularly affected are regions in the central Amazon basin. The range of

Large-scale ocean connectivity and planktonic body size

KAUST Repository

Villarino, Ernesto; Watson, James R.; Jö nsson, Bror; Gasol, Josep M.; Salazar, Guillem; Acinas, Silvia G.; Estrada, Marta; Massana, Ramó n; Logares, Ramiro; Giner, Caterina R.; Pernice, Massimo C.; Olivar, M. Pilar; Citores, Leire; Corell, Jon; Rodrí guez-Ezpeleta, Naiara; Acuñ a, José Luis; Molina-Ramí rez, Axayacatl; Gonzá lez-Gordillo, J. Ignacio; Có zar, André s; Martí , Elisa; Cuesta, José A.; Agusti, Susana; Fraile-Nuez, Eugenio; Duarte, Carlos M.; Irigoien, Xabier; Chust, Guillem

2018-01-01

Global patterns of planktonic diversity are mainly determined by the dispersal of propagules with ocean currents. However, the role that abundance and body size play in determining spatial patterns of diversity remains unclear. Here we analyse spatial community structure - β-diversity - for several planktonic and nektonic organisms from prokaryotes to small mesopelagic fishes collected during the Malaspina 2010 Expedition. β-diversity was compared to surface ocean transit times derived from a global circulation model, revealing a significant negative relationship that is stronger than environmental differences. Estimated dispersal scales for different groups show a negative correlation with body size, where less abundant large-bodied communities have significantly shorter dispersal scales and larger species spatial turnover rates than more abundant small-bodied plankton. Our results confirm that the dispersal scale of planktonic and micro-nektonic organisms is determined by local abundance, which scales with body size, ultimately setting global spatial patterns of diversity.

Large-scale ocean connectivity and planktonic body size

KAUST Repository

Villarino, Ernesto

2018-01-04

Global patterns of planktonic diversity are mainly determined by the dispersal of propagules with ocean currents. However, the role that abundance and body size play in determining spatial patterns of diversity remains unclear. Here we analyse spatial community structure - β-diversity - for several planktonic and nektonic organisms from prokaryotes to small mesopelagic fishes collected during the Malaspina 2010 Expedition. β-diversity was compared to surface ocean transit times derived from a global circulation model, revealing a significant negative relationship that is stronger than environmental differences. Estimated dispersal scales for different groups show a negative correlation with body size, where less abundant large-bodied communities have significantly shorter dispersal scales and larger species spatial turnover rates than more abundant small-bodied plankton. Our results confirm that the dispersal scale of planktonic and micro-nektonic organisms is determined by local abundance, which scales with body size, ultimately setting global spatial patterns of diversity.

Evaluation of IMERG and TRMM 3B43 Monthly Precipitation Products over Mainland China

Directory of Open Access Journals (Sweden)

Fengrui Chen

2016-06-01

Full Text Available As the successor of the Tropical Rainfall Measuring Mission (TRMM, the Global Precipitation Measurement (GPM mission significantly improves the spatial resolution of precipitation estimates from 0.25° to 0.1°. The present study analyzed the error structures of Integrated Multisatellite Retrievals for GPM (IMERG monthly precipitation products over Mainland China from March 2014 to February 2015 using gauge measurements at multiple spatiotemporal scales. Moreover, IMERG products were also compared with TRMM 3B43 products. The results show that: (1 overall, IMERG can capture the spatial patterns of precipitation over China well. It performs a little better than TRMM 3B43 at seasonal and monthly scales; (2 the performance of IMERG varies greatly spatially and temporally. IMERG performs better at low latitudes than at middle latitudes, and shows worse performance in winter than at other times; (3 compared with TRMM 3B43, IMERG significantly improves the estimation accuracy of precipitation over the Xinjiang region and the Qinghai-Tibetan Plateau, especially over the former where IMERG increases Pearson correlation coefficient by 0.18 and decreases root-mean-square error by 54.47 mm for annual precipitation estimates. However, most IMERG products over these areas are unreliable; and (4 IMERG shows poor performance in winter as TRMM 3B43 even if GPM improved its ability to sense frozen precipitation. Most of them over North China are unreliable during this period.

Length-scale dependent microalloying effects on precipitation behaviors and mechanical properties of Al–Cu alloys with minor Sc addition

International Nuclear Information System (INIS)

Jiang, L.; Li, J.K.; Liu, G.; Wang, R.H.; Chen, B.A.; Zhang, J.Y.; Sun, J.; Yang, M.X.; Yang, G.; Yang, J.; Cao, X.Z.

2015-01-01

Heat-treatable Al alloys containing Al–2.5 wt% Cu (Al–Cu) and Al–2.5 wt% Cu–0.3 wt% Sc (Al–Cu–Sc) with different grain length scales, i.e., average grain size >10 μm ( defined coarse grained, CG), 1–2 μm (fine grained, FG), and <1 μm (ultrafine grained, UFG), were prepared by equal-channel angular pressing (ECAP). The length scale and Sc microalloying effects and their interplay on the precipitation behavior and mechanical properties of the Al–Cu alloys were systematically investigated. In the Al–Cu alloys, intergranular θ-Al 2 Cu precipitation gradually dominated by sacrificing the intragranular θ′-Al 2 Cu precipitation with reducing the length scale. Especially in the UFG regime, only intergranular θ-Al 2 Cu particles were precipitated and intragranular θ′-Al 2 Cu precipitation was completely disappeared. This led to a remarkable reduction in yield strength and ductility due to insufficient dislocation storage capacity. The minor Sc addition resulted in a microalloying effect in the Al–Cu alloy, which, however, is strongly dependent on the length scale. The smaller is the grain size, the more active is the microalloying effect that promotes the intragranular precipitation while reduces the intergranular precipitation. Correspondingly, compared with their Sc-free counterparts, the yield strength of post-aged CG, FG, and UFG Al–Cu alloys with Sc addition increased by ~36 MPa, ~56 MPa, and ~150 MPa, simultaneously in tensile elongation by ~20%, ~30%, and 280%, respectively. The grain size-induced evolutions in vacancy concentration/distribution and number density of vacancy-solute/solute–solute clusters and their influences on precipitation nucleation and kinetics have been comprehensively considered to rationalize the length scale-dependent Sc microalloying mechanisms using positron annihilation lifetime spectrum and three dimension atom probe. The increase in ductility was analyzed in the light of Sc microalloying effect and the

Length-scale dependent microalloying effects on precipitation behaviors and mechanical properties of Al–Cu alloys with minor Sc addition

Energy Technology Data Exchange (ETDEWEB)

Jiang, L.; Li, J.K. [State Key Laboratory for Mechanical Behavior of Materials, Xi' an Jiaotong University, Xi' an 710049 (China); Liu, G., E-mail: lgsammer@mail.xjtu.edu.cn [State Key Laboratory for Mechanical Behavior of Materials, Xi' an Jiaotong University, Xi' an 710049 (China); Wang, R.H. [School of Materials Science and Engineering, Xi' an University of Technology, Xi' an 710048 (China); Chen, B.A.; Zhang, J.Y. [State Key Laboratory for Mechanical Behavior of Materials, Xi' an Jiaotong University, Xi' an 710049 (China); Sun, J., E-mail: junsun@mail.xjtu.edu.cn [State Key Laboratory for Mechanical Behavior of Materials, Xi' an Jiaotong University, Xi' an 710049 (China); Yang, M.X.; Yang, G. [Central Iron and Steel Research Institute, Beijing 100081 (China); Yang, J.; Cao, X.Z. [Key Laboratory of Nuclear Radiation and Nuclear Energy Technology, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China)

2015-06-18

Heat-treatable Al alloys containing Al–2.5 wt% Cu (Al–Cu) and Al–2.5 wt% Cu–0.3 wt% Sc (Al–Cu–Sc) with different grain length scales, i.e., average grain size >10 μm ( defined coarse grained, CG), 1–2 μm (fine grained, FG), and <1 μm (ultrafine grained, UFG), were prepared by equal-channel angular pressing (ECAP). The length scale and Sc microalloying effects and their interplay on the precipitation behavior and mechanical properties of the Al–Cu alloys were systematically investigated. In the Al–Cu alloys, intergranular θ-Al{sub 2}Cu precipitation gradually dominated by sacrificing the intragranular θ′-Al{sub 2}Cu precipitation with reducing the length scale. Especially in the UFG regime, only intergranular θ-Al{sub 2}Cu particles were precipitated and intragranular θ′-Al{sub 2}Cu precipitation was completely disappeared. This led to a remarkable reduction in yield strength and ductility due to insufficient dislocation storage capacity. The minor Sc addition resulted in a microalloying effect in the Al–Cu alloy, which, however, is strongly dependent on the length scale. The smaller is the grain size, the more active is the microalloying effect that promotes the intragranular precipitation while reduces the intergranular precipitation. Correspondingly, compared with their Sc-free counterparts, the yield strength of post-aged CG, FG, and UFG Al–Cu alloys with Sc addition increased by ~36 MPa, ~56 MPa, and ~150 MPa, simultaneously in tensile elongation by ~20%, ~30%, and 280%, respectively. The grain size-induced evolutions in vacancy concentration/distribution and number density of vacancy-solute/solute–solute clusters and their influences on precipitation nucleation and kinetics have been comprehensively considered to rationalize the length scale-dependent Sc microalloying mechanisms using positron annihilation lifetime spectrum and three dimension atom probe. The increase in ductility was analyzed in the light of Sc microalloying

Vibration amplitude rule study for rotor under large time scale

International Nuclear Information System (INIS)

Yang Xuan; Zuo Jianli; Duan Changcheng

2014-01-01

The rotor is an important part of the rotating machinery; its vibration performance is one of the important factors affecting the service life. This paper presents both theoretical analyses and experimental demonstrations of the vibration rule of the rotor under large time scales. The rule can be used for the service life estimation of the rotor. (authors)

Trend analysis of watershed-scale precipitation over Northern California by means of dynamically-downscaled CMIP5 future climate projections.

Science.gov (United States)

Ishida, K; Gorguner, M; Ercan, A; Trinh, T; Kavvas, M L

2017-08-15

The impacts of climate change on watershed-scale precipitation through the 21st century were investigated over eight study watersheds in Northern California based on dynamically downscaled CMIP5 future climate projections from three GCMs (CCSM4, HadGEM2-ES, and MIROC5) under the RCP4.5 and RCP8.5 future climate scenarios. After evaluating the modeling capability of the WRF model, the six future climate projections were dynamically downscaled by means of the WRF model over Northern California at 9km grid resolution and hourly temporal resolution during a 94-year period (2006-2100). The biases in the model simulations were corrected, and basin-average precipitation over the eight study watersheds was calculated from the dynamically downscaled precipitation data. Based on the dynamically downscaled basin-average precipitation, trends in annual depth and annual peaks of basin-average precipitation during the 21st century were analyzed over the eight study watersheds. The analyses in this study indicate that there may be differences between trends of annual depths and annual peaks of watershed-scale precipitation during the 21st century. Furthermore, trends in watershed-scale precipitation under future climate conditions may be different for different watersheds depending on their location and topography even if they are in the same region. Copyright © 2017 Elsevier B.V. All rights reserved.

Precipitation Estimation Using Combined Radar/Radiometer Measurements Within the GPM Framework

Science.gov (United States)

Hou, Arthur

2012-01-01

satellite of JAXA, (3) the Multi-Frequency Microwave Scanning Radiometer (MADRAS) and the multi-channel microwave humidity sounder (SAPHIR) on the French-Indian Megha- Tropiques satellite, (4) the Microwave Humidity Sounder (MHS) on the National Oceanic and Atmospheric Administration (NOAA)-19, (5) MHS instruments on MetOp satellites launched by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), (6) the Advanced Technology Microwave Sounder (ATMS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), and (7) ATMS instruments on the NOAA-NASA Joint Polar Satellite System (JPSS) satellites. Data from Chinese and Russian microwave radiometers may also become available through international collaboration under the auspices of the Committee on Earth Observation Satellites (CEOS) and Group on Earth Observations (GEO). The current generation of global rainfall products combines observations from a network of uncoordinated satellite missions using a variety of merging techniques. GPM will provide next-generation precipitation products characterized by: (1) more accurate instantaneous precipitation estimate (especially for light rain and cold-season solid precipitation), (2) intercalibrated microwave brightness temperatures from constellation radiometers within a consistent framework, and (3) unified precipitation retrievals from constellation radiometers using a common a priori hydrometeor database constrained by combined radar/radiometer measurements provided by the GPM Core Observatory.

Estimating Probable Maximum Precipitation by Considering Combined Effect of Typhoon and Southwesterly Air Flow

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Cheng-Chin Liu

2016-01-01

Full Text Available Typhoon Morakot hit southern Taiwan in 2009, bringing 48-hr of heavy rainfall [close to the Probable Maximum Precipitation (PMP] to the Tsengwen Reservoir catchment. This extreme rainfall event resulted from the combined (co-movement effect of two climate systems (i.e., typhoon and southwesterly air flow. Based on the traditional PMP estimation method (i.e., the storm transposition method, STM, two PMP estimation approaches, i.e., Amplification Index (AI and Independent System (IS approaches, which consider the combined effect are proposed in this work. The AI approach assumes that the southwesterly air flow precipitation in a typhoon event could reach its maximum value. The IS approach assumes that the typhoon and southwesterly air flow are independent weather systems. Based on these assumptions, calculation procedures for the two approaches were constructed for a case study on the Tsengwen Reservoir catchment. The results show that the PMP estimates for 6- to 60-hr durations using the two approaches are approximately 30% larger than the PMP estimates using the traditional STM without considering the combined effect. This work is a pioneer PMP estimation method that considers the combined effect of a typhoon and southwesterly air flow. Further studies on this issue are essential and encouraged.

Atmospheric forcing in the occurrence of precipitation extremes in Iberia: comparison between the eastern and western sectors

Science.gov (United States)

Santos, J. A.; Mendes, A. R.

2009-09-01

The occurrence of severe precipitation deficits in the Iberian Peninsula has major socio-economic and environmental impacts. Several previous studies emphasized the leading role of the large-scale atmospheric flow in the occurrence of long periods with significant precipitation lacks. However, due to the high complexity of the Iberian orography, the sensitivity of the local rain-generating mechanisms to large-scale anomalies is remarkably different from region to region. A principal component analysis of the annual precipitation amounts recorded at a network of meteorological stations over the entire peninsula for the period 1961-1998 corroborates this heterogeneity. With particular significance is the contrast between the western and eastern sectors of the peninsula. In fact, taking into account earlier studies, precipitation in western Iberia is strongly related to large-scale atmospheric patterns over the North Atlantic. On the contrary, precipitation over eastern Iberia is much less associated with these large-scale forcing patterns, but much more linked to local/regional mechanisms. In order to test these hypotheses, eight meteorological stations, four in the western half (Porto, Bragança, Lisboa and Beja) and four in the eastern half (Barcelona, Valencia, Tortosa and Zaragoza) of Iberia are selected taking into account, firstly, the geographical location, and secondly the quality and homogeneity of the respective time series. A set of extremely wet/dry seasons was subsequently chosen for each weather station separately, taking into account the 90th percentile of the respective empirical distributions. The analysis of the different atmospheric fields (precipitation rates, convective precipitation, precipitable water, specific humidity, relative humidity, surface temperature, sea surface pressure, geopotential heights, wind components and vorticity at different isobaric levels) is undertaken by using data from the National Centers for Environmental Prediction

Disdrometer-based C-Band Radar Quantitative Precipitation Estimation (QPE) in a highly complex terrain region in tropical Colombia.

Science.gov (United States)

Sepúlveda, J.; Hoyos Ortiz, C. D.

2017-12-01

An adequate quantification of precipitation over land is critical for many societal applications including agriculture, hydroelectricity generation, water supply, and risk management associated with extreme events. The use of rain gauges, a traditional method for precipitation estimation, and an excellent one, to estimate the volume of liquid water during a particular precipitation event, does not allow to fully capture the highly spatial variability of the phenomena which is a requirement for almost all practical applications. On the other hand, the weather radar, an active remote sensing sensor, provides a proxy for rainfall with fine spatial resolution and adequate temporary sampling, however, it does not measure surface precipitation. In order to fully exploit the capabilities of the weather radar, it is necessary to develop quantitative precipitation estimation (QPE) techniques combining radar information with in-situ measurements. Different QPE methodologies are explored and adapted to local observations in a highly complex terrain region in tropical Colombia using a C-Band radar and a relatively dense network of rain gauges and disdrometers. One important result is that the expressions reported in the literature for extratropical locations are not representative of the conditions found in the tropical region studied. In addition to reproducing the state-of-the-art techniques, a new multi-stage methodology based on radar-derived variables and disdrometer data is proposed in order to achieve the best QPE possible. The main motivation for this new methodology is based on the fact that most traditional QPE methods do not directly take into account the different uncertainty sources involved in the process. The main advantage of the multi-stage model compared to traditional models is that it allows assessing and quantifying the uncertainty in the surface rain rate estimation. The sub-hourly rainfall estimations using the multi-stage methodology are realistic

Effects of local and large-scale climate patterns on estuarine resident fishes: The example of Pomatoschistus microps and Pomatoschistus minutus

Science.gov (United States)

Nyitrai, Daniel; Martinho, Filipe; Dolbeth, Marina; Rito, João; Pardal, Miguel A.

2013-12-01

Large-scale and local climate patterns are known to influence several aspects of the life cycle of marine fish. In this paper, we used a 9-year database (2003-2011) to analyse the populations of two estuarine resident fishes, Pomatoschistus microps and Pomatoschistus minutus, in order to determine their relationships with varying environmental stressors operating over local and large scales. This study was performed in the Mondego estuary, Portugal. Firstly, the variations in abundance, growth, population structure and secondary production were evaluated. These species appeared in high densities in the beginning of the study period, with subsequent occasional high annual density peaks, while their secondary production was lower in dry years. The relationships between yearly fish abundance and the environmental variables were evaluated separately for both species using Spearman correlation analysis, considering the yearly abundance peaks for the whole population, juveniles and adults. Among the local climate patterns, precipitation, river runoff, salinity and temperature were used in the analyses, and North Atlantic Oscillation (NAO) index and sea surface temperature (SST) were tested as large-scale factors. For P. microps, precipitation and NAO were the significant factors explaining abundance of the whole population, the adults and the juveniles as well. Regarding P. minutus, for the whole population, juveniles and adults river runoff was the significant predictor. The results for both species suggest a differential influence of climate patterns on the various life cycle stages, confirming also the importance of estuarine resident fishes as indicators of changes in local and large-scale climate patterns, related to global climate change.

The Software Reliability of Large Scale Integration Circuit and Very Large Scale Integration Circuit

OpenAIRE

Artem Ganiyev; Jan Vitasek

2010-01-01

This article describes evaluation method of faultless function of large scale integration circuits (LSI) and very large scale integration circuits (VLSI). In the article there is a comparative analysis of factors which determine faultless of integrated circuits, analysis of already existing methods and model of faultless function evaluation of LSI and VLSI. The main part describes a proposed algorithm and program for analysis of fault rate in LSI and VLSI circuits.

Spatially-explicit estimation of geographical representation in large-scale species distribution datasets.

Science.gov (United States)

Kalwij, Jesse M; Robertson, Mark P; Ronk, Argo; Zobel, Martin; Pärtel, Meelis

2014-01-01

Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution

Spatio-Temporal Analysis of the Accuracy of Tropical Multisatellite Precipitation Analysis 3B42 Precipitation Data in Mid-High Latitudes of China

Science.gov (United States)

Cai, Yancong; Jin, Changjie; Wang, Anzhi; Guan, Dexin; Wu, Jiabing; Yuan, Fenghui; Xu, Leilei

2015-01-01

Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38°NS). This study attempts to statistically assess TMPA V7 data over the region beyond 40°NS using data obtained from numerous weather stations in 1998–2012. Comparative analysis at three timescales (daily, monthly and annual scale) indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%). Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these data are

Spatio-temporal analysis of the accuracy of tropical multisatellite precipitation analysis 3B42 precipitation data in mid-high latitudes of China.

Directory of Open Access Journals (Sweden)

Yancong Cai

Full Text Available Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38°NS. This study attempts to statistically assess TMPA V7 data over the region beyond 40°NS using data obtained from numerous weather stations in 1998-2012. Comparative analysis at three timescales (daily, monthly and annual scale indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%. Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these

Calculating Soil Wetness, Evapotranspiration and Carbon Cycle Processes Over Large Grid Areas Using a New Scaling Technique

Science.gov (United States)

Sellers, Piers

2012-01-01

Soil wetness typically shows great spatial variability over the length scales of general circulation model (GCM) grid areas (approx 100 km ), and the functions relating evapotranspiration and photosynthetic rate to local-scale (approx 1 m) soil wetness are highly non-linear. Soil respiration is also highly dependent on very small-scale variations in soil wetness. We therefore expect significant inaccuracies whenever we insert a single grid area-average soil wetness value into a function to calculate any of these rates for the grid area. For the particular case of evapotranspiration., this method - use of a grid-averaged soil wetness value - can also provoke severe oscillations in the evapotranspiration rate and soil wetness under some conditions. A method is presented whereby the probability distribution timction(pdf) for soil wetness within a grid area is represented by binning. and numerical integration of the binned pdf is performed to provide a spatially-integrated wetness stress term for the whole grid area, which then permits calculation of grid area fluxes in a single operation. The method is very accurate when 10 or more bins are used, can deal realistically with spatially variable precipitation, conserves moisture exactly and allows for precise modification of the soil wetness pdf after every time step. The method could also be applied to other ecological problems where small-scale processes must be area-integrated, or upscaled, to estimate fluxes over large areas, for example in treatments of the terrestrial carbon budget or trace gas generation.

Investigating precipitation changes of anthropic origin: data and methodological issues

Science.gov (United States)

de Lima, Isabel; Lovejoy, Shaun