WorldWideScience

Sample records for near-term climate prediction

  1. Near term climate projections for invasive species distributions

    Science.gov (United States)

    Jarnevich, C.S.; Stohlgren, T.J.

    2009-01-01

    Climate change and invasive species pose important conservation issues separately, and should be examined together. We used existing long term climate datasets for the US to project potential climate change into the future at a finer spatial and temporal resolution than the climate change scenarios generally available. These fine scale projections, along with new species distribution modeling techniques to forecast the potential extent of invasive species, can provide useful information to aide conservation and invasive species management efforts. We created habitat suitability maps for Pueraria montana (kudzu) under current climatic conditions and potential average conditions up to 30 years in the future. We examined how the potential distribution of this species will be affected by changing climate, and the management implications associated with these changes. Our models indicated that P. montana may increase its distribution particularly in the Northeast with climate change and may decrease in other areas. ?? 2008 Springer Science+Business Media B.V.

  2. Upgrades, Current Capabilities and Near-Term Plans of the NASA ARC Mars Climate

    Science.gov (United States)

    Hollingsworth, J. L.; Kahre, Melinda April; Haberle, Robert M.; Schaeffer, James R.

    2012-01-01

    We describe and review recent upgrades to the ARC Mars climate modeling framework, in particular, with regards to physical parameterizations (i.e., testing, implementation, modularization and documentation); the current climate modeling capabilities; selected research topics regarding current/past climates; and then, our near-term plans related to the NASA ARC Mars general circulation modeling (GCM) project.

  3. Evaluating Modeled Impact Metrics for Human Health, Agriculture Growth, and Near-Term Climate

    Science.gov (United States)

    Seltzer, K. M.; Shindell, D. T.; Faluvegi, G.; Murray, L. T.

    2017-12-01

    Simulated metrics that assess impacts on human health, agriculture growth, and near-term climate were evaluated using ground-based and satellite observations. The NASA GISS ModelE2 and GEOS-Chem models were used to simulate the near-present chemistry of the atmosphere. A suite of simulations that varied by model, meteorology, horizontal resolution, emissions inventory, and emissions year were performed, enabling an analysis of metric sensitivities to various model components. All simulations utilized consistent anthropogenic global emissions inventories (ECLIPSE V5a or CEDS), and an evaluation of simulated results were carried out for 2004-2006 and 2009-2011 over the United States and 2014-2015 over China. Results for O3- and PM2.5-based metrics featured minor differences due to the model resolutions considered here (2.0° × 2.5° and 0.5° × 0.666°) and model, meteorology, and emissions inventory each played larger roles in variances. Surface metrics related to O3 were consistently high biased, though to varying degrees, demonstrating the need to evaluate particular modeling frameworks before O3 impacts are quantified. Surface metrics related to PM2.5 were diverse, indicating that a multimodel mean with robust results are valuable tools in predicting PM2.5-related impacts. Oftentimes, the configuration that captured the change of a metric best over time differed from the configuration that captured the magnitude of the same metric best, demonstrating the challenge in skillfully simulating impacts. These results highlight the strengths and weaknesses of these models in simulating impact metrics related to air quality and near-term climate. With such information, the reliability of historical and future simulations can be better understood.

  4. Near-Term Actions to Address Long-Term Climate Risk

    Science.gov (United States)

    Lempert, R. J.

    2014-12-01

    Addressing climate change requires effective long-term policy making, which occurs when reflecting on potential events decades or more in the future causes policy makers to choose near-term actions different than those they would otherwise pursue. Contrary to some expectations, policy makers do sometimes make such long-term decisions, but not as commonly and successfully as climate change may require. In recent years however, the new capabilities of analytic decision support tools, combined with improved understanding of cognitive and organizational behaviors, has significantly improved the methods available for organizations to manage longer-term climate risks. In particular, these tools allow decision makers to understand what near-term actions consistently contribute to achieving both short- and long-term societal goals, even in the face of deep uncertainty regarding the long-term future. This talk will describe applications of these approaches for infrastructure, water, and flood risk management planning, as well as studies of how near-term choices about policy architectures can affect long-term greenhouse gas emission reduction pathways.

  5. Assessing the near-term risk of climate uncertainty : interdependencies among the U.S. states.

    Energy Technology Data Exchange (ETDEWEB)

    Loose, Verne W.; Lowry, Thomas Stephen; Malczynski, Leonard A.; Tidwell, Vincent Carroll; Stamber, Kevin Louis; Reinert, Rhonda K.; Backus, George A.; Warren, Drake E.; Zagonel, Aldo A.; Ehlen, Mark Andrew; Klise, Geoffrey T.; Vargas, Vanessa N.

    2010-04-01

    Policy makers will most likely need to make decisions about climate policy before climate scientists have resolved all relevant uncertainties about the impacts of climate change. This study demonstrates a risk-assessment methodology for evaluating uncertain future climatic conditions. We estimate the impacts of climate change on U.S. state- and national-level economic activity from 2010 to 2050. To understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions to mitigate the course of climate change, we focus on precipitation, one of the most uncertain aspects of future climate change. We use results of the climate-model ensemble from the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) as a proxy for representing climate uncertainty over the next 40 years, map the simulated weather from the climate models hydrologically to the county level to determine the physical consequences on economic activity at the state level, and perform a detailed 70-industry analysis of economic impacts among the interacting lower-48 states. We determine the industry-level contribution to the gross domestic product and employment impacts at the state level, as well as interstate population migration, effects on personal income, and consequences for the U.S. trade balance. We show that the mean or average risk of damage to the U.S. economy from climate change, at the national level, is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs.

  6. Predicting Near-Term Water Quality from Satellite Observations of Watershed Conditions

    Science.gov (United States)

    Weiss, W. J.; Wang, L.; Hoffman, K.; West, D.; Mehta, A. V.; Lee, C.

    2017-12-01

    Despite the strong influence of watershed conditions on source water quality, most water utilities and water resource agencies do not currently have the capability to monitor watershed sources of contamination with great temporal or spatial detail. Typically, knowledge of source water quality is limited to periodic grab sampling; automated monitoring of a limited number of parameters at a few select locations; and/or monitoring relevant constituents at a treatment plant intake. While important, such observations are not sufficient to inform proactive watershed or source water management at a monthly or seasonal scale. Satellite remote sensing data on the other hand can provide a snapshot of an entire watershed at regular, sub-monthly intervals, helping analysts characterize watershed conditions and identify trends that could signal changes in source water quality. Accordingly, the authors are investigating correlations between satellite remote sensing observations of watersheds and source water quality, at a variety of spatial and temporal scales and lags. While correlations between remote sensing observations and direct in situ measurements of water quality have been well described in the literature, there are few studies that link remote sensing observations across a watershed with near-term predictions of water quality. In this presentation, the authors will describe results of statistical analyses and discuss how these results are being used to inform development of a desktop decision support tool to support predictive application of remote sensing data. Predictor variables under evaluation include parameters that describe vegetative conditions; parameters that describe climate/weather conditions; and non-remote sensing, in situ measurements. Water quality parameters under investigation include nitrogen, phosphorus, organic carbon, chlorophyll-a, and turbidity.

  7. "Near-term" Natural Catastrophe Risk Management and Risk Hedging in a Changing Climate

    Science.gov (United States)

    Michel, Gero; Tiampo, Kristy

    2014-05-01

    Competing with analytics - Can the insurance market take advantage of seasonal or "near-term" forecasting and temporal changes in risk? Natural perils (re)insurance has been based on models following climatology i.e. the long-term "historical" average. This is opposed to considering the "near-term" and forecasting hazard and risk for the seasons or years to come. Variability and short-term changes in risk are deemed abundant for almost all perils. In addition to hydrometeorological perils whose changes are vastly discussed, earthquake activity might also change over various time-scales affected by earlier local (or even global) events, regional changes in the distribution of stresses and strains and more. Only recently has insurance risk modeling of (stochastic) hurricane-years or extratropical-storm-years started considering our ability to forecast climate variability herewith taking advantage of apparent correlations between climate indicators and the activity of storm events. Once some of these "near-term measures" were in the market, rating agencies and regulators swiftly adopted these concepts demanding companies to deploy a selection of more conservative "time-dependent" models. This was despite the fact that the ultimate effect of some of these measures on insurance risk was not well understood. Apparent short-term success over the last years in near-term seasonal hurricane forecasting was brought to a halt in 2013 when these models failed to forecast the exceptional shortage of hurricanes herewith contradicting an active-year forecast. The focus of earthquake forecasting has in addition been mostly on high rather than low temporal and regional activity despite the fact that avoiding losses does not by itself create a product. This presentation sheds light on new risk management concepts for over-regional and global (re)insurance portfolios that take advantage of forecasting changes in risk. The presentation focuses on the "upside" and on new opportunities

  8. Modeling the Near-Term Risk of Climate Uncertainty: Interdependencies among the U.S. States

    Science.gov (United States)

    Lowry, T. S.; Backus, G.; Warren, D.

    2010-12-01

    Decisions made to address climate change must start with an understanding of the risk of an uncertain future to human systems, which in turn means understanding both the consequence as well as the probability of a climate induced impact occurring. In other words, addressing climate change is an exercise in risk-informed policy making, which implies that there is no single correct answer or even a way to be certain about a single answer; the uncertainty in future climate conditions will always be present and must be taken as a working-condition for decision making. In order to better understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions, this study estimates the impacts from responses to climate change on U.S. state- and national-level economic activity by employing a risk-assessment methodology for evaluating uncertain future climatic conditions. Using the results from the Intergovernmental Panel on Climate Change’s (IPCC) Fourth Assessment Report (AR4) as a proxy for climate uncertainty, changes in hydrology over the next 40 years were mapped and then modeled to determine the physical consequences on economic activity and to perform a detailed 70-industry analysis of the economic impacts among the interacting lower-48 states. The analysis determines industry-level effects, employment impacts at the state level, interstate population migration, consequences to personal income, and ramifications for the U.S. trade balance. The conclusions show that the average risk of damage to the U.S. economy from climate change is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs. Further analysis shows that an increase in uncertainty raises this risk. This paper will present the methodology behind the approach, a summary of the underlying models, as well as the path forward for improving the approach.

  9. Impacts of Near-Term Climate Change on Irrigation Demands and Crop Yields in the Columbia River Basin

    Science.gov (United States)

    Rajagopalan, K.; Chinnayakanahalli, K. J.; Stockle, C. O.; Nelson, R. L.; Kruger, C. E.; Brady, M. P.; Malek, K.; Dinesh, S. T.; Barber, M. E.; Hamlet, A. F.; Yorgey, G. G.; Adam, J. C.

    2018-03-01

    Adaptation to a changing climate is critical to address future global food and water security challenges. While these challenges are global, successful adaptation strategies are often generated at regional scales; therefore, regional-scale studies are critical to inform adaptation decision making. While climate change affects both water supply and demand, water demand is relatively understudied, especially at regional scales. The goal of this work is to address this gap, and characterize the direct impacts of near-term (for the 2030s) climate change and elevated CO2 levels on regional-scale crop yields and irrigation demands for the Columbia River basin (CRB). This question is addressed through a coupled crop-hydrology model that accounts for site-specific and crop-specific characteristics that control regional-scale response to climate change. The overall near-term outlook for agricultural production in the CRB is largely positive, with yield increases for most crops and small overall increases in irrigation demand. However, there are crop-specific and location-specific negative impacts as well, and the aggregate regional response of irrigation demands to climate change is highly sensitive to the spatial crop mix. Low-value pasture/hay varieties of crops—typically not considered in climate change assessments—play a significant role in determining the regional response of irrigation demands to climate change, and thus cannot be overlooked. While, the overall near-term outlook for agriculture in the region is largely positive, there may be potential for a negative outlook further into the future, and it is important to consider this in long-term planning.

  10. Do differences in future sulfate emission pathways matter for near-term climate? A case study for the Asian monsoon

    Science.gov (United States)

    Bartlett, Rachel E.; Bollasina, Massimo A.; Booth, Ben B. B.; Dunstone, Nick J.; Marenco, Franco; Messori, Gabriele; Bernie, Dan J.

    2018-03-01

    Anthropogenic aerosols could dominate over greenhouse gases in driving near-term hydroclimate change, especially in regions with high present-day aerosol loading such as Asia. Uncertainties in near-future aerosol emissions represent a potentially large, yet unexplored, source of ambiguity in climate projections for the coming decades. We investigated the near-term sensitivity of the Asian summer monsoon to aerosols by means of transient modelling experiments using HadGEM2-ES under two existing climate change mitigation scenarios selected to have similar greenhouse gas forcing, but to span a wide range of plausible global sulfur dioxide emissions. Increased sulfate aerosols, predominantly from East Asian sources, lead to large regional dimming through aerosol-radiation and aerosol-cloud interactions. This results in surface cooling and anomalous anticyclonic flow over land, while abating the western Pacific subtropical high. The East Asian monsoon circulation weakens and precipitation stagnates over Indochina, resembling the observed southern-flood-northern-drought pattern over China. Large-scale circulation adjustments drive suppression of the South Asian monsoon and a westward extension of the Maritime Continent convective region. Remote impacts across the Northern Hemisphere are also generated, including a northwestward shift of West African monsoon rainfall induced by the westward displacement of the Indian Ocean Walker cell, and temperature anomalies in northern midlatitudes linked to propagation of Rossby waves from East Asia. These results indicate that aerosol emissions are a key source of uncertainty in near-term projection of regional and global climate; a careful examination of the uncertainties associated with aerosol pathways in future climate assessments must be highly prioritised.

  11. Interactions among Amazon land use, forests and climate: prospects for a near-term forest tipping point

    OpenAIRE

    Nepstad, Daniel C; Stickler, Claudia M; Filho, Britaldo Soares-; Merry, Frank

    2008-01-01

    Some model experiments predict a large-scale substitution of Amazon forest by savannah-like vegetation by the end of the twenty-first century. Expanding global demands for biofuels and grains, positive feedbacks in the Amazon forest fire regime and drought may drive a faster process of forest degradation that could lead to a near-term forest dieback. Rising worldwide demands for biofuel and meat are creating powerful new incentives for agro-industrial expansion into Amazon forest regions. For...

  12. Near-term technology policies for long-term climate targets--economy wide versus technology specific approaches

    International Nuclear Information System (INIS)

    Sanden, B.A.; Azar, Christian

    2005-01-01

    The aim of this paper is to offer suggestions when it comes to near-term technology policies for long-term climate targets based on some insights into the nature of technical change. We make a distinction between economy wide and technology specific policy instruments and put forward two key hypotheses: (i) Near-term carbon targets such as the Kyoto protocol can be met by economy wide price instruments (carbon taxes, or a cap-and-trade system) changing the technologies we pick from the shelf (higher energy efficiency in cars, buildings and industry, wind, biomass for heat and electricity, natural gas instead of coal, solar thermal, etc.). (ii) Technology specific policies are needed to bring new technologies to the shelf. Without these new technologies, stricter emission reduction targets may be considered impossible to meet by the government, industry and the general public, and therefore not adopted. The policies required to bring these more advanced technologies to the shelf are more complex and include increased public research and development, demonstration, niche market creation, support for networks within the new industries, standard settings and infrastructure policies (e.g., when it comes to hydrogen distribution). There is a risk that the society in its quest for cost-efficiency in meeting near-term emissions targets, becomes blindfolded when it comes to the more difficult, but equally important issue of bringing more advanced technologies to the shelf. The paper presents mechanisms that cause technology look in, how these very mechanisms can be used to get out of the current 'carbon lock-in' and the risk with premature lock-ins into new technologies that do not deliver what they currently promise. We then review certain climate policy proposals with regards to their expected technology impact, and finally we present a let-a-hundred-flowers-bloom strategy for the next couple of decades

  13. Simultaneously Mitigating Near-Term Climate Change and Improving Human Health and Food Security

    Science.gov (United States)

    Shindell, Drew; Kuylenstierna, Johan C. I.; Vignati, Elisabetta; van Dingenen, Rita; Amann, Markus; Klimont, Zbigniew; Anenberg, Susan C.; Muller, Nicholas; Janssens-Maenhout, Greet; Raes, Frank; Schwartz, Joel; Faluvegi, Greg; Pozzoli, Luca; Kupiainen, Kaarle; Höglund-Isaksson, Lena; Emberson, Lisa; Streets, David; Ramanathan, V.; Hicks, Kevin; Oanh, N. T. Kim; Milly, George; Williams, Martin; Demkine, Volodymyr; Fowler, David

    2012-01-01

    Tropospheric ozone and black carbon (BC) contribute to both degraded air quality and global warming. We considered ~400 emission control measures to reduce these pollutants by using current technology and experience. We identified 14 measures targeting methane and BC emissions that reduce projected global mean warming ~0.5°C by 2050. This strategy avoids 0.7 to 4.7 million annual premature deaths from outdoor air pollution and increases annual crop yields by 30 to 135 million metric tons due to ozone reductions in 2030 and beyond. Benefits of methane emissions reductions are valued at $700 to $5000 per metric ton, which is well above typical marginal abatement costs (less than $250). The selected controls target different sources and influence climate on shorter time scales than those of carbon dioxide-reduction measures. Implementing both substantially reduces the risks of crossing the 2°C threshold.

  14. Simultaneously mitigating near-term climate change and improving human health and food security.

    Science.gov (United States)

    Shindell, Drew; Kuylenstierna, Johan C I; Vignati, Elisabetta; van Dingenen, Rita; Amann, Markus; Klimont, Zbigniew; Anenberg, Susan C; Muller, Nicholas; Janssens-Maenhout, Greet; Raes, Frank; Schwartz, Joel; Faluvegi, Greg; Pozzoli, Luca; Kupiainen, Kaarle; Höglund-Isaksson, Lena; Emberson, Lisa; Streets, David; Ramanathan, V; Hicks, Kevin; Oanh, N T Kim; Milly, George; Williams, Martin; Demkine, Volodymyr; Fowler, David

    2012-01-13

    Tropospheric ozone and black carbon (BC) contribute to both degraded air quality and global warming. We considered ~400 emission control measures to reduce these pollutants by using current technology and experience. We identified 14 measures targeting methane and BC emissions that reduce projected global mean warming ~0.5°C by 2050. This strategy avoids 0.7 to 4.7 million annual premature deaths from outdoor air pollution and increases annual crop yields by 30 to 135 million metric tons due to ozone reductions in 2030 and beyond. Benefits of methane emissions reductions are valued at $700 to $5000 per metric ton, which is well above typical marginal abatement costs (less than $250). The selected controls target different sources and influence climate on shorter time scales than those of carbon dioxide-reduction measures. Implementing both substantially reduces the risks of crossing the 2°C threshold.

  15. Interactions among Amazon land use, forests and climate: prospects for a near-term forest tipping point.

    Science.gov (United States)

    Nepstad, Daniel C; Stickler, Claudia M; Filho, Britaldo Soares-; Merry, Frank

    2008-05-27

    Some model experiments predict a large-scale substitution of Amazon forest by savannah-like vegetation by the end of the twenty-first century. Expanding global demands for biofuels and grains, positive feedbacks in the Amazon forest fire regime and drought may drive a faster process of forest degradation that could lead to a near-term forest dieback. Rising worldwide demands for biofuel and meat are creating powerful new incentives for agro-industrial expansion into Amazon forest regions. Forest fires, drought and logging increase susceptibility to further burning while deforestation and smoke can inhibit rainfall, exacerbating fire risk. If sea surface temperature anomalies (such as El Niño episodes) and associated Amazon droughts of the last decade continue into the future, approximately 55% of the forests of the Amazon will be cleared, logged, damaged by drought or burned over the next 20 years, emitting 15-26Pg of carbon to the atmosphere. Several important trends could prevent a near-term dieback. As fire-sensitive investments accumulate in the landscape, property holders use less fire and invest more in fire control. Commodity markets are demanding higher environmental performance from farmers and cattle ranchers. Protected areas have been established in the pathway of expanding agricultural frontiers. Finally, emerging carbon market incentives for reductions in deforestation could support these trends.

  16. Climate Prediction Center - Outlooks

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Outreach > Publications > Climate Diagnostics Bulletin Climate Diagnostics Bulletin - Tropics Climate Diagnostics Bulletin - Forecast Climate Diagnostics

  17. Climate prediction and predictability

    Science.gov (United States)

    Allen, Myles

    2010-05-01

    Climate prediction is generally accepted to be one of the grand challenges of the Geophysical Sciences. What is less widely acknowledged is that fundamental issues have yet to be resolved concerning the nature of the challenge, even after decades of research in this area. How do we verify or falsify a probabilistic forecast of a singular event such as anthropogenic warming over the 21st century? How do we determine the information content of a climate forecast? What does it mean for a modelling system to be "good enough" to forecast a particular variable? How will we know when models and forecasting systems are "good enough" to provide detailed forecasts of weather at specific locations or, for example, the risks associated with global geo-engineering schemes. This talk will provide an overview of these questions in the light of recent developments in multi-decade climate forecasting, drawing on concepts from information theory, machine learning and statistics. I will draw extensively but not exclusively from the experience of the climateprediction.net project, running multiple versions of climate models on personal computers.

  18. Assessing climate change impacts on the near-term stability of the wind energy resource over the United States.

    Science.gov (United States)

    Pryor, S C; Barthelmie, R J

    2011-05-17

    The energy sector comprises approximately two-thirds of global total greenhouse gas emissions. For this and other reasons, renewable energy resources including wind power are being increasingly harnessed to provide electricity generation potential with negligible emissions of carbon dioxide. The wind energy resource is naturally a function of the climate system because the "fuel" is the incident wind speed and thus is determined by the atmospheric circulation. Some recent articles have reported historical declines in measured near-surface wind speeds, leading some to question the continued viability of the wind energy industry. Here we briefly articulate the challenges inherent in accurately quantifying and attributing historical tendencies and making robust projections of likely future wind resources. We then analyze simulations from the current generation of regional climate models and show, at least for the next 50 years, the wind resource in the regions of greatest wind energy penetration will not move beyond the historical envelope of variability. Thus this work suggests that the wind energy industry can, and will, continue to make a contribution to electricity provision in these regions for at least the next several decades.

  19. Hazards of decreasing marine oxygen: the near-term and millennial-scale benefits of meeting the Paris climate targets

    Science.gov (United States)

    Battaglia, Gianna; Joos, Fortunat

    2018-06-01

    Ocean deoxygenation is recognized as key ecosystem stressor of the future ocean and associated climate-related ocean risks are relevant for current policy decisions. In particular, benefits of reaching the ambitious 1.5 °C warming target mentioned by the Paris Agreement compared to higher temperature targets are of high interest. Here, we model oceanic oxygen, warming and their compound hazard in terms of metabolic conditions on multi-millennial timescales for a range of equilibrium temperature targets. Scenarios where radiative forcing is stabilized by 2300 are used in ensemble simulations with the Bern3D Earth System Model of Intermediate Complexity. Transiently, the global mean ocean oxygen concentration decreases by a few percent under low forcing and by 40 % under high forcing. Deoxygenation peaks about a thousand years after stabilization of radiative forcing and new steady-state conditions are established after AD 8000 in our model. Hypoxic waters expand over the next millennium and recovery is slow and remains incomplete under high forcing. Largest transient decreases in oxygen are projected for the deep sea. Distinct and near-linear relationships between the equilibrium temperature response and marine O2 loss emerge. These point to the effectiveness of the Paris climate target in reducing marine hazards and risks. Mitigation measures are projected to reduce peak decreases in oceanic oxygen inventory by 4.4 % °C-1 of avoided equilibrium warming. In the upper ocean, the decline of a metabolic index, quantified by the ratio of O2 supply to an organism's O2 demand, is reduced by 6.2 % °C-1 of avoided equilibrium warming. Definitions of peak hypoxia demonstrate strong sensitivity to additional warming. Volumes of water with less than 50 mmol O2 m-3, for instance, increase between 36 % and 76 % °C-1 of equilibrium temperature response. Our results show that millennial-scale responses should be considered in assessments of ocean deoxygenation and associated

  20. The near-term prediction of drought and flooding conditions in the northeastern United States based on extreme phases of AMO and NAO

    Science.gov (United States)

    Berton, Rouzbeh; Driscoll, Charles T.; Adamowski, Jan F.

    2017-10-01

    A series of hydroclimatic teleconnection patterns were identified between variations in either Atlantic or Pacific oceanic indices with precipitation and discharge anomalies in the northeastern United States. We hypothesized that temporal annual or seasonal changes in discharge could be explained by variations in extreme phases of the Atlantic Multi-decadal Oscillation (AMO index, SST: Sea Surface Temperature anomalies) and the North Atlantic Oscillation (NAO index, SLP: Sea-Level Pressure anomalies) up to three seasons in advance. The Merrimack River watershed, the fourth largest basin in New England, with a drainage area of 13,000 km2, is a compelling study site because it not only provides an opportunity to investigate the teleconnection between hydrologic variables and large-scale climate circulation patterns, but also how those patterns may become obscured by anthropogenic disturbances such as river regulation or urban development. We considered precipitation and discharge data of 21 gauging stations within the Merrimack River watershed, including the Hubbard Brook Experimental Forest (HBEF), NH, with a median record length of 55 years beginning as early as 1904. The discharge anomalies were statistically significant (p-value ≤ 0.2) between extreme positive and negative phases of AMO (1857-2011) and NAO (1900-2011) and revealed the potential teleconnectivity of climate circulation patterns with discharge. Annual and seasonal correlations of discharge were examined with the extreme phases of AMO and NAO at zero-, one-, or two- year/season lags (total of 30 scenarios). When AMO was greater than 0.2, the strongest correlations of AMO and NAO with discharge were observed at headwater catchments. This correlation weakened downstream towards larger regulated and/or developed sub-basins. We introduced a simple approach for near-term prediction of drought and flooding events. An exponential decay function was regressed through the historic occurrence of the relative

  1. Prediction of cognitive and motor development in preterm children using exhaustive feature selection and cross-validation of near-term white matter microstructure.

    Science.gov (United States)

    Schadl, Kornél; Vassar, Rachel; Cahill-Rowley, Katelyn; Yeom, Kristin W; Stevenson, David K; Rose, Jessica

    2018-01-01

    Advanced neuroimaging and computational methods offer opportunities for more accurate prognosis. We hypothesized that near-term regional white matter (WM) microstructure, assessed on diffusion tensor imaging (DTI), using exhaustive feature selection with cross-validation would predict neurodevelopment in preterm children. Near-term MRI and DTI obtained at 36.6 ± 1.8 weeks postmenstrual age in 66 very-low-birth-weight preterm neonates were assessed. 60/66 had follow-up neurodevelopmental evaluation with Bayley Scales of Infant-Toddler Development, 3rd-edition (BSID-III) at 18-22 months. Linear models with exhaustive feature selection and leave-one-out cross-validation computed based on DTI identified sets of three brain regions most predictive of cognitive and motor function; logistic regression models were computed to classify high-risk infants scoring one standard deviation below mean. Cognitive impairment was predicted (100% sensitivity, 100% specificity; AUC = 1) by near-term right middle-temporal gyrus MD, right cingulate-cingulum MD, left caudate MD. Motor impairment was predicted (90% sensitivity, 86% specificity; AUC = 0.912) by left precuneus FA, right superior occipital gyrus MD, right hippocampus FA. Cognitive score variance was explained (29.6%, cross-validated Rˆ2 = 0.296) by left posterior-limb-of-internal-capsule MD, Genu RD, right fusiform gyrus AD. Motor score variance was explained (31.7%, cross-validated Rˆ2 = 0.317) by left posterior-limb-of-internal-capsule MD, right parahippocampal gyrus AD, right middle-temporal gyrus AD. Search in large DTI feature space more accurately identified neonatal neuroimaging correlates of neurodevelopment.

  2. Prediction of near-term increases in suicidal ideation in recently depressed patients with bipolar II disorder using intensive longitudinal data.

    Science.gov (United States)

    Depp, Colin A; Thompson, Wesley K; Frank, Ellen; Swartz, Holly A

    2017-01-15

    There are substantial gaps in understanding near-term precursors of suicidal ideation in bipolar II disorder. We evaluated whether repeated patient-reported mood and energy ratings predicted subsequent near-term increases in suicide ideation. Secondary data were used from 86 depressed adults with bipolar II disorder enrolled in one of 3 clinical trials evaluating Interpersonal and Social Rhythm Therapy and/or pharmacotherapy as treatments for depression. Twenty weeks of daily mood and energy ratings and weekly Hamilton Depression Rating Scale (HDRS) were obtained. Penalized regression was used to model trajectories of daily mood and energy ratings in the 3 week window prior to HDRS Suicide Item ratings. Participants completed an average of 68.6 (sd=52) days of mood and energy ratings. Aggregated across the sample, 22% of the 1675 HDRS Suicide Item ratings were non-zero, indicating presence of at least some suicidal thoughts. A cross-validated model with longitudinal ratings of energy and depressed mood within the three weeks prior to HDRS ratings resulted in an AUC of 0.91 for HDRS Suicide item >2, accounting for twice the variation when compared to baseline HDRS ratings. Energy, both at low and high levels, was an earlier predictor than mood. Data derived from a heterogeneous treated sample may not generalize to naturalistic samples. Identified suicidal behavior was absent from the sample so it could not be predicted. Prediction models coupled with intensively gathered longitudinal data may shed light on the dynamic course of near-term risk factors for suicidal ideation in bipolar II disorder. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Climate Prediction Center

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Organization Enter Search Term(s): Search Search the CPC Go NCEP Quarterly Newsletter Climate Highlights U.S Climate-Weather El Niño/La Niña MJO Blocking AAO, AO, NAO, PNA Climatology Global Monsoons Expert

  4. Iterative near-term ecological forecasting: Needs, opportunities, and challenges.

    Science.gov (United States)

    Dietze, Michael C; Fox, Andrew; Beck-Johnson, Lindsay M; Betancourt, Julio L; Hooten, Mevin B; Jarnevich, Catherine S; Keitt, Timothy H; Kenney, Melissa A; Laney, Christine M; Larsen, Laurel G; Loescher, Henry W; Lunch, Claire K; Pijanowski, Bryan C; Randerson, James T; Read, Emily K; Tredennick, Andrew T; Vargas, Rodrigo; Weathers, Kathleen C; White, Ethan P

    2018-02-13

    Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

  5. Iterative near-term ecological forecasting: Needs, opportunities, and challenges

    Science.gov (United States)

    Dietze, Michael C.; Fox, Andrew; Beck-Johnson, Lindsay; Betancourt, Julio L.; Hooten, Mevin B.; Jarnevich, Catherine S.; Keitt, Timothy H.; Kenney, Melissa A.; Laney, Christine M.; Larsen, Laurel G.; Loescher, Henry W.; Lunch, Claire K.; Pijanowski, Bryan; Randerson, James T.; Read, Emily; Tredennick, Andrew T.; Vargas, Rodrigo; Weathers, Kathleen C.; White, Ethan P.

    2018-01-01

    Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

  6. Climate Prediction Center - Seasonal Outlook

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Forecast Discussion PROGNOSTIC DISCUSSION FOR MONTHLY OUTLOOK NWS CLIMATE PREDICTION CENTER COLLEGE PARK MD INFLUENCE ON THE MONTHLY-AVERAGED CLIMATE. OUR MID-MONTH ASSESSMENT OF LOW-FREQUENCY CLIMATE VARIABILITY IS

  7. Climate Prediction Center - Site Index

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Means Bulletins Annual Winter Stratospheric Ozone Climate Diagnostics Bulletin (Most Recent) Climate (Hazards Outlook) Climate Assessment: Dec. 1999-Feb. 2000 (Seasonal) Climate Assessment: Mar-May 2000

  8. Mexico’s Transition to a Net-Zero Emissions Energy System: Near Term Implications of Long Term Stringent Climate Targets

    DEFF Research Database (Denmark)

    Solano-Rodríguez, Baltazar; Pizarro Alonso, Amalia Rosa; Vaillancourt, Kathleen

    2018-01-01

    Mexico has positioned itself as a leader among emerging countries for its efforts to mitigate climate change through ambitious climate policies aimed at reducing greenhouse gas (GHG) emissions. However, the Energy Reform bill approved in 2014 promotes the production of hydrocarbons to develop...... the economy of this sector, as well as the use of natural gas for electricity generation in order to reduce electricity prices in the short term. In 2016, nearly 80% of Mexico’s total electricity was generated by thermal power plants. While natural gas prices stay low, there might be a limited role...... for natural gas to act as a fuel bridge in this sector if the government is to pursue deep decarbonisation targets to 2050. There is a risk that over-investing in gas infrastructure may delay a transition to lower carbon sources, potentially leading to less cost-efficient pathways towards decarbonisation...

  9. Global Air Quality and Health Co-benefits of Mitigating Near-term Climate Change Through Methane and Black Carbon Emission Controls

    Science.gov (United States)

    Anenberg, Susan C.; Schwartz, Joel; Shindell, Drew Todd; Amann, Markus; Faluvegi, Gregory S.; Klimont, Zbigniew; Janssens-Maenhout, Greet; Pozzoli, Luca; Dingenen, Rita Van; Vignati, Elisabetta; hide

    2012-01-01

    Tropospheric ozone and black carbon (BC), a component of fine particulate matter (PM health benefits of 14 specific emission control measures targeting BC and methane, an ozone precursor, that were selected because of their potential to reduce the rate of climate change over the next 20-40 years. Methods: We simulated the impacts of mitigation measures on outdoor concentrations of PM2.5 and ozone using two composition-climate models, and calculated associated changes in premature PM2.5- and ozone-related deaths using epidemiologically derived concentration-response functions. Results: We estimated that, for PM2.5 and ozone, respectively, fully implementing these measures could reduce global population-weighted average surface concentrations by 23-34% and 7-17% and avoid 0.6-4.4 and 0.04-0.52 million annual premature deaths globally in 2030. More than 80% of the health benefits are estimated to occur in Asia. We estimated that BC mitigation measures would achieve approximately 98% of the deaths that would be avoided if all BC and methane mitigation measures were implemented, due to reduced BC and associated reductions of nonmethane ozone precursor and organic carbon emissions as well as stronger mortality relationships for PM2.5 relative to ozone. Although subject to large uncertainty, these estimates and conclusions are not strongly dependent on assumptions for the concentration-response function. Conclusions: In addition to climate benefits, our findings indicate that the methane and BC emission control measures would have substantial co-benefits for air quality and public health worldwide, potentially reversing trends of increasing air pollution concentrations and mortality in Africa and South, West, and Central Asia. These projected benefits are independent of carbon dioxide mitigation measures. Benefits of BC measures are underestimated because we did not account for benefits from reduced indoor exposures and because outdoor exposure estimates were limited by

  10. Climate Prediction Center - monthly Outlook

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Outlooks monthly Climate Outlooks Banner OFFICIAL Forecasts June 2018 [UPDATED MONTHLY FORECASTS SERVICE ) Canonical Correlation Analysis ECCA - Ensemble Canonical Correlation Analysis Optimal Climate Normals

  11. Climate Prediction - NOAA's National Weather Service

    Science.gov (United States)

    Statistical Models... MOS Prod GFS-LAMP Prod Climate Past Weather Predictions Weather Safety Weather Radio National Weather Service on FaceBook NWS on Facebook NWS Director Home > Climate > Predictions Climate Prediction Long range forecasts across the U.S. Climate Prediction Web Sites Climate Prediction

  12. Climate Prediction Center - Outreach: 41st Annual Climate Diagnostics &

    Science.gov (United States)

    home page National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Annual Climate Diagnostics & Prediction Workshop NOAA's 41st Climate Diagnostics and Prediction Climate Diagnostics Prediction Workshop (CDPW) news, visit the CDPW list server Abstract Submission Has

  13. Decadal climate prediction (project GCEP).

    Science.gov (United States)

    Haines, Keith; Hermanson, Leon; Liu, Chunlei; Putt, Debbie; Sutton, Rowan; Iwi, Alan; Smith, Doug

    2009-03-13

    Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.

  14. Climate Prediction Center - Monitoring & Data Index

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Oceanic & Atmospheric Monitoring and Data Monitoring Weather & Climate in Realtime Climate Diagnostics Bulletin Preliminary Climate Diagnostics Bulletin Figures Monthly Atmospheric & Sea Surface

  15. Predicting space climate change

    Science.gov (United States)

    Balcerak, Ernie

    2011-10-01

    Galactic cosmic rays and solar energetic particles can be hazardous to humans in space, damage spacecraft and satellites, pose threats to aircraft electronics, and expose aircrew and passengers to radiation. A new study shows that these threats are likely to increase in coming years as the Sun approaches the end of the period of high solar activity known as “grand solar maximum,” which has persisted through the past several decades. High solar activity can help protect the Earth by repelling incoming galactic cosmic rays. Understanding the past record can help scientists predict future conditions. Barnard et al. analyzed a 9300-year record of galactic cosmic ray and solar activity based on cosmogenic isotopes in ice cores as well as on neutron monitor data. They used this to predict future variations in galactic cosmic ray flux, near-Earth interplanetary magnetic field, sunspot number, and probability of large solar energetic particle events. The researchers found that the risk of space weather radiation events will likely increase noticeably over the next century compared with recent decades and that lower solar activity will lead to increased galactic cosmic ray levels. (Geophysical Research Letters, doi:10.1029/2011GL048489, 2011)

  16. Near-term oil prices

    International Nuclear Information System (INIS)

    Lynch, M.C.

    2001-01-01

    This PowerPoint presentation included 36 slides that described the state of oil prices and how to predict them. Prices are random, stochastic, chaotic, mean-reverting and driven by speculators, oil companies and OPEC. The many factors that enable price forecasting are economic growth, weather, industry behaviour, speculators, OPEC policy choices, Mexico/Russia production policy, non-OPEC supply and the interpretation of the above factors by OPEC, speculators, traders and the petroleum industry. Several graphs were included depicting such things as WTI price forecasts, differentials, oil market change in 2001, inventory levels, and WTI backwardation. The presentation provided some explanations for price uncertainties, price surges and collapses. U.S. GDP growth and the volatility of Iraq's production was also depicted. The author predicted that economic growth will occur and that oil demand will go up. Oil prices will fluctuate as the Middle East will be politically unstable and weather will be a major factor that will influence oil prices. The prices are likely to be more volatile than in the 1986 to 1995 period. 2 tabs., 22 figs

  17. Climate Prediction Center - The ENSO Cycle

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > El Niño/La Niña > The ENSO Cycle ENSO Cycle Banner Climate for Weather and Climate Prediction Climate Prediction Center 5830 University Research Court College

  18. Predictability of weather and climate

    National Research Council Canada - National Science Library

    Palmer, Tim; Hagedorn, Renate

    2006-01-01

    ... and anthropogenic climate change are among those included. Ensemble systems for forecasting predictability are discussed extensively. Ed Lorenz, father of chaos theory, makes a contribution to theoretical analysis with a previously unpublished paper. This well-balanced volume will be a valuable resource for many years. High-quality chapter autho...

  19. Detecting failure of climate predictions

    Science.gov (United States)

    Runge, Michael C.; Stroeve, Julienne C.; Barrett, Andrew P.; McDonald-Madden, Eve

    2016-01-01

    The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty1, 2. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies3. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.

  20. Are abrupt climate changes predictable?

    Science.gov (United States)

    Ditlevsen, Peter

    2013-04-01

    It is taken for granted that the limited predictability in the initial value problem, the weather prediction, and the predictability of the statistics are two distinct problems. Lorenz (1975) dubbed this predictability of the first and the second kind respectively. Predictability of the first kind in a chaotic dynamical system is limited due to the well-known critical dependence on initial conditions. Predictability of the second kind is possible in an ergodic system, where either the dynamics is known and the phase space attractor can be characterized by simulation or the system can be observed for such long times that the statistics can be obtained from temporal averaging, assuming that the attractor does not change in time. For the climate system the distinction between predictability of the first and the second kind is fuzzy. This difficulty in distinction between predictability of the first and of the second kind is related to the lack of scale separation between fast and slow components of the climate system. The non-linear nature of the problem furthermore opens the possibility of multiple attractors, or multiple quasi-steady states. As the ice-core records show, the climate has been jumping between different quasi-stationary climates, stadials and interstadials through the Dansgaard-Oechger events. Such a jump happens very fast when a critical tipping point has been reached. The question is: Can such a tipping point be predicted? This is a new kind of predictability: the third kind. If the tipping point is reached through a bifurcation, where the stability of the system is governed by some control parameter, changing in a predictable way to a critical value, the tipping is predictable. If the sudden jump occurs because internal chaotic fluctuations, noise, push the system across a barrier, the tipping is as unpredictable as the triggering noise. In order to hint at an answer to this question, a careful analysis of the high temporal resolution NGRIP isotope

  1. Ocean eddies and climate predictability.

    Science.gov (United States)

    Kirtman, Ben P; Perlin, Natalie; Siqueira, Leo

    2017-12-01

    A suite of coupled climate model simulations and experiments are used to examine how resolved mesoscale ocean features affect aspects of climate variability, air-sea interactions, and predictability. In combination with control simulations, experiments with the interactive ensemble coupling strategy are used to further amplify the role of the oceanic mesoscale field and the associated air-sea feedbacks and predictability. The basic intent of the interactive ensemble coupling strategy is to reduce the atmospheric noise at the air-sea interface, allowing an assessment of how noise affects the variability, and in this case, it is also used to diagnose predictability from the perspective of signal-to-noise ratios. The climate variability is assessed from the perspective of sea surface temperature (SST) variance ratios, and it is shown that, unsurprisingly, mesoscale variability significantly increases SST variance. Perhaps surprising is the fact that the presence of mesoscale ocean features even further enhances the SST variance in the interactive ensemble simulation beyond what would be expected from simple linear arguments. Changes in the air-sea coupling between simulations are assessed using pointwise convective rainfall-SST and convective rainfall-SST tendency correlations and again emphasize how the oceanic mesoscale alters the local association between convective rainfall and SST. Understanding the possible relationships between the SST-forced signal and the weather noise is critically important in climate predictability. We use the interactive ensemble simulations to diagnose this relationship, and we find that the presence of mesoscale ocean features significantly enhances this link particularly in ocean eddy rich regions. Finally, we use signal-to-noise ratios to show that the ocean mesoscale activity increases model estimated predictability in terms of convective precipitation and atmospheric upper tropospheric circulation.

  2. Prediction of interannual climate variations

    International Nuclear Information System (INIS)

    Shukla, J.

    1993-01-01

    It has been known for some time that the behavior of the short-term fluctuations of the earth's atmosphere resembles that of a chaotic non-linear dynamical system, and that the day-to-day weather cannot be predicted beyond a few weeks. However, it has also been found that the interactions of the atmosphere with the underlying oceans and the land surfaces can produce fluctuations whose time scales are much longer than the limits of deterministic prediction of weather. It is, therefore, natural to ask whether it is possible that the seasonal and longer time averages of climate fluctuations can be predicted with sufficient skill to be beneficial for social and economic applications, even though the details of day-to-day weather cannot be predicted beyond a few weeks. The main objective of the workshop was to address this question by assessing the current state of knowledge on predictability of seasonal and interannual climate variability and to investigate various possibilities for its prediction. (orig./KW)

  3. Climate Prediction Center - Outlooks: CFS Forecast of Seasonal Climate

    Science.gov (United States)

    National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site government Web resources and services. CFS Seasonal Climate Forecasts CFS Forecast of Seasonal Climate discontinued after October 2012. This page displays seasonal climate anomalies from the NCEP coupled forecast

  4. Climate Prediction Center - Expert Assessments Index

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Monitoring and Data > Global Climate Data & Maps > ; Global Regional Climate Maps Regional Climate Maps Banner The Monthly regional analyses products are

  5. Climate Prediction Center - Global Tropical Hazards Assessment

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Organization Search Go Search the CPC Go Climate Outlooks Climate & Weather Link El Niño/La Niña MJO Teleconnections AO NAO PNA AAO Blocking Storm Tracks Climate Glossary Outreach About Us Our Mission Who We Are

  6. Climate Prediction Center - Monitoring and Data Index

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News ; Atmospheric Monitoring and Data Monitoring Weather & Climate in Realtime Climate Diagnostics Bulletin Preliminary Climate Diagnostics Bulletin Figures Monthly Atmospheric & Sea Surface Temperature Indices

  7. Climate Prediction Center - Atlantic Hurricane Outlook

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News ; Seasonal Climate Summary Archive The 2018 Atlantic hurricane season outlook is an official product of the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC). The outlook is

  8. Climate Prediction Center - Monitoring and Data - Regional Climate Maps:

    Science.gov (United States)

    National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site government Web resources and services. HOME > Monitoring and Data > U.S. Climate Data > ; Precipitation & Temperature > Regional Climate Maps: USA Menu Weekly 1-Month 3-Month 12-Month Weekly

  9. Decadel climate prediction: challenges and opportunities

    International Nuclear Information System (INIS)

    Hurrell, J W

    2008-01-01

    The scientific understanding of climate change is now sufficiently clear to show that climate change from global warming is already upon us, and the rate of change as projected exceeds anything seen in nature in the past 10,000 years. Uncertainties remain, however, especially regarding how climate will change at regional and local scales where the signal of natural variability is large. Addressing many of these uncertainties will require a movement toward high resolution climate system predictions, with a blurring of the distinction between shorter-term predictions and longer-term climate projections. The key is the realization that climate system predictions, regardless of timescale, will require initialization of coupled general circulation models with best estimates of the current observed state of the atmosphere, oceans, cryosphere, and land surface. Formidable challenges exist: for instance, what is the best method of initialization given imperfect observations and systematic errors in models? What effect does initialization have on climate predictions? What predictions should be attempted, and how would they be verified? Despite such challenges, the unrealized predictability that resides in slowly evolving phenomena, such as ocean current systems, is of paramount importance for society to plan and adapt for the next few decades. Moreover, initialized climate predictions will require stronger collaboration with shared knowledge, infrastructure and technical capabilities among those in the weather and climate prediction communities. The potential benefits include improved understanding and predictions on all time scales

  10. Climate Prediction Center - Monitoring and Data

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News monthly data, time series, and maps for various climate parameters, such as precipitation, temperature Oscillations (ENSO) and other climate patterns such as the North Atlantic and Pacific Decadal Oscillations, and

  11. Seasonal climate prediction for North Eurasia

    International Nuclear Information System (INIS)

    Kryjov, Vladimir N

    2012-01-01

    An overview of the current status of the operational seasonal climate prediction for North Eurasia is presented. It is shown that the performance of existing climate models is rather poor in seasonal prediction for North Eurasia. Multi-model ensemble forecasts are more reliable than single-model ones; however, for North Eurasia they tend to be close to climatological ones. Application of downscaling methods may improve predictions for some locations (or regions). However, general improvement of the reliability of seasonal forecasts for North Eurasia requires improvement of the climate prediction models. (letter)

  12. Development of a Climate Prediction Market

    Science.gov (United States)

    Roulston, M. S.

    2017-12-01

    Winton, a global investment firm, is planning to establish a prediction market for climate. This prediction market will allow participants to place bets on global climate up to several decades in the future. Winton is pursuing this endeavour as part of its philanthropy that funds scientific research and the communication of scientific ideas. The Winton Climate Prediction Market will be based in the U.K. It will be structured as an online gambling site subject to the regulation of the Gambling Commission. Unlike existing betting sites, the Climate Prediction Market will be subsidized: a central market maker will inject money into the market. This is in contrast to traditional bookmakers or betting exchanges who set odds in their favour or charge commissions to make a profit. The philosophy of a subsidized prediction market is that the party seeking information should fund the market, rather than the participants who provide the information. The initial market will allow bets to be placed on the atmospheric concentration of carbon dioxide and the global mean temperature anomaly. It will thus produce implied forecasts of carbon dioxide concentration as well as global temperatures. If the initial market is successful, additional markets could be added which target other climate variables, such as regional temperatures or sea-level rise. These markets could be sponsored by organizations that are interested in predictions of the specific climate variables. An online platform for the Climate Prediction Market has been developed and has been tested internally at Winton.

  13. Climate Prediction Center - ENSO FAQ

    Science.gov (United States)

    data buoys used to monitor ocean temperatures? What is climate variability? A prominent aspect of our Niño or La Niña? During an El Niño or La Niña, the changes in Pacific Ocean temperatures affect Pacific. Changes in the ocean surface temperatures affect tropical rainfall patterns and atmospheric winds

  14. Short-acting sulfonamides near term and neonatal jaundice

    DEFF Research Database (Denmark)

    Klarskov, Pia; Andersen, Jon Trærup; Jimenez-Solem, Espen

    2013-01-01

    To investigate the association between maternal use of sulfamethizole near term and the risk of neonatal jaundice.......To investigate the association between maternal use of sulfamethizole near term and the risk of neonatal jaundice....

  15. Climate Prediction Center - Outlooks: Current UV Index Forecast Map

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Service NOAA Center for Weather and Climate Prediction Climate Prediction Center 5830 University Research Court College Park, Maryland 20740 Page Author: Climate Prediction Center Internet Team Disclaimer

  16. The predictive validity of safety climate.

    Science.gov (United States)

    Johnson, Stephen E

    2007-01-01

    Safety professionals have increasingly turned their attention to social science for insight into the causation of industrial accidents. One social construct, safety climate, has been examined by several researchers [Cooper, M. D., & Phillips, R. A. (2004). Exploratory analysis of the safety climate and safety behavior relationship. Journal of Safety Research, 35(5), 497-512; Gillen, M., Baltz, D., Gassel, M., Kirsch, L., & Vacarro, D. (2002). Perceived safety climate, job Demands, and coworker support among union and nonunion injured construction workers. Journal of Safety Research, 33(1), 33-51; Neal, A., & Griffin, M. A. (2002). Safety climate and safety behaviour. Australian Journal of Management, 27, 66-76; Zohar, D. (2000). A group-level model of safety climate: Testing the effect of group climate on microaccidents in manufacturing jobs. Journal of Applied Psychology, 85(4), 587-596; Zohar, D., & Luria, G. (2005). A multilevel model of safety climate: Cross-level relationships between organization and group-level climates. Journal of Applied Psychology, 90(4), 616-628] who have documented its importance as a factor explaining the variation of safety-related outcomes (e.g., behavior, accidents). Researchers have developed instruments for measuring safety climate and have established some degree of psychometric reliability and validity. The problem, however, is that predictive validity has not been firmly established, which reduces the credibility of safety climate as a meaningful social construct. The research described in this article addresses this problem and provides additional support for safety climate as a viable construct and as a predictive indicator of safety-related outcomes. This study used 292 employees at three locations of a heavy manufacturing organization to complete the 16 item Zohar Safety Climate Questionnaire (ZSCQ) [Zohar, D., & Luria, G. (2005). A multilevel model of safety climate: Cross-level relationships between organization and group

  17. Climate Change as a Predictable Surprise

    International Nuclear Information System (INIS)

    Bazerman, M.H.

    2006-01-01

    In this article, I analyze climate change as a 'predictable surprise', an event that leads an organization or nation to react with surprise, despite the fact that the information necessary to anticipate the event and its consequences was available (Bazerman and Watkins, 2004). I then assess the cognitive, organizational, and political reasons why society fails to implement wise strategies to prevent predictable surprises generally and climate change specifically. Finally, I conclude with an outline of a set of response strategies to overcome barriers to change

  18. An analytical model for climatic predictions

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-12-01

    A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day -1 . We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs

  19. US Climate Variability and Predictability Project

    Energy Technology Data Exchange (ETDEWEB)

    Patterson, Mike [University Corporation for Atmospheric Research (UCAR), Boulder, CO (United States)

    2017-11-14

    The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year support of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.

  20. Climate Prediction Center - Forecasts & Outlook Maps, Graphs and Tables

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News list below The Climate Prediction Center (CPC) is responsible for issuing seasonal climate outlook maps , and National Centers for Environmental Prediction). These weather and climate products comprise the

  1. Climate Prediction Center - Monitoring & Data: Seasonal ENSO Impacts on

    Science.gov (United States)

    page National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center , state and local government Web resources and services. HOME > Monitoring and Data > U.S. Climate and Climate Prediction Climate Prediction Center 5830 University Research Court College Park, Maryland

  2. A federal partnership to pursue operational prediction at the weather-climate interface

    Science.gov (United States)

    Sandgathe, Scott A.; Eleuterio, Daniel; Warren, Steven

    2012-10-01

    Earth System Prediction Capability Workshop Washington, D. C., 21-23 March 2012 A meeting to advance a federal partnership toward operational prediction of the physical environment at subseasonal to decadal time scales was held in Washington, D. C. Scientists, headquarters representatives, and program managers from the Department of Energy, NASA, the National Oceanic and Atmospheric Administration (NOAA), the National Science Foundation, the U.S. Air Force, and the U.S. Navy met to discuss pressing agency requirements for extended-range environmental prediction to inform economic, energy, agricultural, national security, and infrastructure decisions. After significant review and discussion, participants agreed that the highest potential for progress was at the interseasonal to interannual (ISI) time scales (Advancing the Science of Climate Change (2010), Board on Atmospheric Sciences and Climate (BASC), http://www.nap.edu/openbook.php?record_id=12782). They agreed to pursue a joint effort, identifying five areas for near-term demonstrations of predictability and establishing volunteer coordinators to organize the demonstration efforts. The demonstrations will establish operational extended-range predictive skill, inform further research, enhance interagency collaboration, and push forward environmental prediction technical and computational capabilities.

  3. Climate Prediction Center (CPC) Palmer Drought and Crop Moisture Indices

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Climate Prediction Center (CPC) Palmer Drought Severity and Crop Moisture Indices are computed for the 344 U.S. Climate Divisions on a weekly basis based on a...

  4. On climate prediction: how much can we expect from climate memory?

    Science.gov (United States)

    Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

    2018-03-01

    Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

  5. An prediction and explanation of 'climatic swing

    Science.gov (United States)

    Barkin, Yury

    2010-05-01

    Introduction. In works of the author [1, 2] the mechanism has been offered and the scenario of formation of congelations and warming of the Earth and their inversion and asymmetric displays in opposite hemispheres has been described. These planetary thermal processes are connected with gravitational forced oscillations of the core-mantle system of the Earth, controlling and directing submission of heat in the top layers of the mantle and on a surface of the Earth. It is shown, that action of this mechanism should observed in various time scales. In particular significant changes of a climate should occur to the thousand-year periods, with the periods in tens and hundred thousand years. Thus excitation of system the core-mantle is caused by planetary secular orbital perturbations and by perturbations of the Earth rotation which as is known are characterized by significant amplitudes. But also in a short time scale the climate variations with the interannual and decade periods also should be observed, how dynamic consequences of the swing of the core-mantle system of the Earth with the same periods [3]. The fundamental phenomenon of secular polar drift of the core relatively to the viscous-elastic and changeable mantle [4] in last years has obtained convincing confirmations various geosciences. Reliable an attribute of influence of oscillations of the core on a variation of natural processes is their property of inversion when, for example, activity of process accrues in northern hemisphere and decreases in a southern hemisphere. Such contrast secular changes in northern and southern (N/S) hemispheres have been predicted on the base of geodynamic model [1] and revealed according to observations: from gravimetry measurements of a gravity [5]; in determination of a secular trend of a sea level, as global, and in northern and southern hemispheres [6, 7]; in redistribution of air masses [6, 8]; in geodetic measurements of changes of average radiuses of northern and

  6. AREVA HTR concept for near-term deployment

    Energy Technology Data Exchange (ETDEWEB)

    Lommers, L.J., E-mail: lewis.lommers@areva.com [AREVA Inc., 2101 Horn Rapids Road, Richland, WA 99354 (United States); Shahrokhi, F. [AREVA Inc., Lynchburg, VA (United States); Mayer, J.A. [AREVA Inc., Marlborough, MA (United States); Southworth, F.H. [AREVA Inc., Lynchburg, VA (United States)

    2012-10-15

    This paper introduces AREVA's High Temperature Reactor (HTR) steam cycle concept for near-term industrial deployment. Today, nuclear power primarily impacts only electricity generation. The process heat and transportation fuel sectors are completely dependent on fossil fuels. In order to impact this energy sector as rapidly as possible, AREVA has focused its HTR development effort on the steam cycle HTR concept. This reduces near-term development risk and minimizes the delay before a useful contribution to this sector of the energy economy can be realized. It also provides a stepping stone to longer term very high temperature concepts which might serve additional markets. A general description of the current AREVA steam cycle HTR concept is provided. This concept provides a flexible system capable of serving a variety of process heat and cogeneration markets in the near-term.

  7. AREVA HTR concept for near-term deployment

    International Nuclear Information System (INIS)

    Lommers, L.J.; Shahrokhi, F.; Mayer, J.A.; Southworth, F.H.

    2012-01-01

    This paper introduces AREVA's High Temperature Reactor (HTR) steam cycle concept for near-term industrial deployment. Today, nuclear power primarily impacts only electricity generation. The process heat and transportation fuel sectors are completely dependent on fossil fuels. In order to impact this energy sector as rapidly as possible, AREVA has focused its HTR development effort on the steam cycle HTR concept. This reduces near-term development risk and minimizes the delay before a useful contribution to this sector of the energy economy can be realized. It also provides a stepping stone to longer term very high temperature concepts which might serve additional markets. A general description of the current AREVA steam cycle HTR concept is provided. This concept provides a flexible system capable of serving a variety of process heat and cogeneration markets in the near-term.

  8. Impurity control in near-term tokamak reactors

    International Nuclear Information System (INIS)

    Stacey, W.M. Jr.; Smith, D.L.; Brooks, J.N.

    1976-10-01

    Several methods for reducing impurity contamination in near-term tokamak reactors by modifying the first-wall surface with a low-Z or low-sputter material are examined. A review of the sputtering data and an assessment of the technological feasibility of various wall modification schemes are presented. The power performance of a near-term tokamak reactor is simulated for various first-wall surface materials, with and without a divertor, in order to evaluate the likely effect of plasma contamination associated with these surface materials

  9. Near-Term Opportunities for Carbon Dioxide Capture and Storage 2007

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2007-07-01

    This document contains the summary report of the workshop on global assessments for near-term opportunities for carbon dioxide capture and storage (CCS), which took place on 21-22 June 2007 in Oslo, Norway. It provided an opportunity for direct dialogue between concerned stakeholders in the global effort to accelerate the development and commercialisation of CCS technology. This is part of a series of three workshops on near-term opportunities for this important mitigation option that will feed into the G8 Plan of Action on Climate Change, Clean Energy and Sustainable Development. The ultimate goal of this effort is to present a report and policy recommendations to the G8 leaders at their 2008 summit meeting in Japan.

  10. Decadal climate predictions improved by ocean ensemble dispersion filtering

    Science.gov (United States)

    Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

    2017-06-01

    Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two time scales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering toward the ensemble mean.Plain Language SummaryDecadal predictions aim to predict the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. The ocean memory due to its heat capacity holds big potential skill. In recent years, more precise initialization techniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions. Ensembles are another important aspect. Applying slightly perturbed predictions to trigger the famous butterfly effect results in an ensemble. Instead of evaluating one prediction, but the whole ensemble with its

  11. Can We Envision a Bettor's Guide to Climate Prediction Markets?

    Science.gov (United States)

    Trexler, M.

    2017-12-01

    It's one thing to set up a climate prediction market, it's another to find enough informed traders to make the market work. Climate bets could range widely, from purely scientific or atmospheric metrics, to bets that involve the interplay of science, policy, economic, and behavioral outcomes. For a topic as complex and politicized as climate change, a Bettor's Guide to Climate Predictions could substantially expand and diversify the pool of individuals trading in the market, increasing both its liquidity and decision-support value. The Climate Web is an on-line and publically accessible Beta version of such a Bettor's Guide, implementing the knowledge management adage: "if only we knew what we know." The Climate Web not only curates the key literature, news coverage, and websites relating to more than 100 climate topics, from extreme event exceedance curves to climate economics to climate risk scenarios, it extracts and links together thousands of ideas and graphics across all of those topics. The Climate Web integrates the many disciplinary silos that characterize today's often dysfunctional climate policy conversations, allowing rapid cross-silo exploration and understanding. As a Bettor's Guide it would allow prediction market traders to better research and understand their potential bets, and to quickly survey key thinking and uncertainties relating to those bets. The availability of such a Bettor's Guide to Climate Predictions should make traders willing to place more bets than they otherwise would, and should facilitate higher quality betting. The presentation will introduce the knowledge management dimensions and challenges of climate prediction markets, and introduce the Climate Web as one solution to those challenges.

  12. Climate modelling, uncertainty and responses to predictions of change

    International Nuclear Information System (INIS)

    Henderson-Sellers, A.

    1996-01-01

    Article 4.1(F) of the Framework Convention on Climate Change commits all parties to take climate change considerations into account, to the extent feasible, in relevant social, economic and environmental policies and actions and to employ methods such as impact assessments to minimize adverse effects of climate change. This could be achieved by, inter alia, incorporating climate change risk assessment into development planning processes, i.e. relating climatic change to issues of habitability and sustainability. Adaptation is an ubiquitous and beneficial natural and human strategy. Future adaptation (adjustment) to climate is inevitable at the least to decrease the vulnerability to current climatic impacts. An urgent issue is the mismatch between the predictions of global climatic change and the need for information on local to regional change in order to develop adaptation strategies. Mitigation efforts are essential since the more successful mitigation activities are, the less need there will be for adaptation responses. And, mitigation responses can be global (e.g. a uniform percentage reduction in greenhouse gas emissions) while adaptation responses will be local to regional in character and therefore depend upon confident predictions of regional climatic change. The dilemma facing policymakers is that scientists have considerable confidence in likely global climatic changes but virtually zero confidence in regional changes. Mitigation and adaptation strategies relevant to climatic change can most usefully be developed in the context of sound understanding of climate, especially the near-surface continental climate, permitting discussion of societally relevant issues. But, climate models can't yet deliver this type of regionally and locationally specific prediction and some aspects of current research even seem to indicate increased uncertainty. These topics are explored in this paper using the specific example of the prediction of land-surface climate changes

  13. Climate control loads prediction of electric vehicles

    International Nuclear Information System (INIS)

    Zhang, Ziqi; Li, Wanyong; Zhang, Chengquan; Chen, Jiangping

    2017-01-01

    Highlights: • A model of vehicle climate control loads is proposed based on experiments. • Main climate control loads of the modeled vehicle are quantitatively analyzed. • Range reductions of the modeled vehicle under different conditions are simulated. - Abstract: A new model of electric vehicle climate control loads is provided in this paper. The mathematical formulations of the major climate control loads are developed, and the coefficients of the formulations are experimentally determined. Then, the detailed climate control loads are analyzed, and the New European Driving Cycle (NEDC) range reductions due to these loads are calculated under different conditions. It is found that in an electric vehicle, the total climate control loads vary with the vehicle speed, HVAC mode and blower level. The ventilation load is the largest climate control load, followed by the solar radiation load. These two add up to more than 80% of total climate control load in summer. The ventilation load accounts for 70.7–83.9% of total heating load under the winter condition. The climate control loads will cause a 17.2–37.1% reduction of NEDC range in summer, and a 17.1–54.1% reduction in winter, compared to the AC off condition. The heat pump system has an advantage in range extension. A heat pump system with an average heating COP of 1.7 will extend the range by 7.6–21.1% based on the simulation conditions.

  14. Near-term hybrid vehicle program, phase 1

    Science.gov (United States)

    1979-01-01

    The preliminary design of a hybrid vehicle which fully meets or exceeds the requirements set forth in the Near Term Hybrid Vehicle Program is documented. Topics addressed include the general layout and styling, the power train specifications with discussion of each major component, vehicle weight and weight breakdown, vehicle performance, measures of energy consumption, and initial cost and ownership cost. Alternative design options considered and their relationship to the design adopted, computer simulation used, and maintenance and reliability considerations are also discussed.

  15. Predicting phenology by integrating ecology, evolution and climate science

    Science.gov (United States)

    Pau, Stephanie; Wolkovich, Elizabeth M.; Cook, Benjamin I.; Davies, T. Jonathan; Kraft, Nathan J.B.; Bolmgren, Kjell; Betancourt, Julio L.; Cleland, Elsa E.

    2011-01-01

    Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology — the timing of life-history events. Phenology has well-demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species' reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

  16. Validating predictions from climate envelope models.

    Directory of Open Access Journals (Sweden)

    James I Watling

    Full Text Available Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species' distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967-1971 (t1 and evaluated using occurrence data from 1998-2002 (t2. Model sensitivity (the ability to correctly classify species presences was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on

  17. Validating predictions from climate envelope models

    Science.gov (United States)

    Watling, J.; Bucklin, D.; Speroterra, C.; Brandt, L.; Cabal, C.; Romañach, Stephanie S.; Mazzotti, Frank J.

    2013-01-01

    Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.

  18. Ensemble-based Regional Climate Prediction: Political Impacts

    Science.gov (United States)

    Miguel, E.; Dykema, J.; Satyanath, S.; Anderson, J. G.

    2008-12-01

    Accurate forecasts of regional climate, including temperature and precipitation, have significant implications for human activities, not just economically but socially. Sub Saharan Africa is a region that has displayed an exceptional propensity for devastating civil wars. Recent research in political economy has revealed a strong statistical relationship between year to year fluctuations in precipitation and civil conflict in this region in the 1980s and 1990s. To investigate how climate change may modify the regional risk of civil conflict in the future requires a probabilistic regional forecast that explicitly accounts for the community's uncertainty in the evolution of rainfall under anthropogenic forcing. We approach the regional climate prediction aspect of this question through the application of a recently demonstrated method called generalized scalar prediction (Leroy et al. 2009), which predicts arbitrary scalar quantities of the climate system. This prediction method can predict change in any variable or linear combination of variables of the climate system averaged over a wide range spatial scales, from regional to hemispheric to global. Generalized scalar prediction utilizes an ensemble of model predictions to represent the community's uncertainty range in climate modeling in combination with a timeseries of any type of observational data that exhibits sensitivity to the scalar of interest. It is not necessary to prioritize models in deriving with the final prediction. We present the results of the application of generalized scalar prediction for regional forecasts of temperature and precipitation and Sub Saharan Africa. We utilize the climate predictions along with the established statistical relationship between year-to-year rainfall variability in Sub Saharan Africa to investigate the potential impact of climate change on civil conflict within that region.

  19. Evaluation of selected near-term energy-conservation options for the Midwest

    Energy Technology Data Exchange (ETDEWEB)

    Evans, A.R.; Colsher, C.S.; Hamilton, R.W.; Buehring, W.A.

    1978-11-01

    This report evaluates the potential for implementation of near-term energy-conservation practices for the residential, commercial, agricultural, industrial, transportation, and utility sectors of the economy in twelve states: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. The information used to evaluate the magnitude of achievable energy savings includes regional energy use, the regulatory/legislative climate relating to energy conservation, technical characteristics of the measures, and their feasibility of implementation. This work is intended to provide baseline information for an ongoing regional assessment of energy and environmental impacts in the Midwest. 80 references.

  20. Developing hydrogen infrastructure through near-term intermediate technology

    International Nuclear Information System (INIS)

    Arthur, D.M.; Checkel, M.D.; Koch, C.R.

    2003-01-01

    The development of a vehicular hydrogen fuelling infrastructure is a necessary first step towards the widespread use of hydrogen-powered vehicles. This paper proposes the case for using a near-term, intermediate technology to stimulate and support the development of that infrastructure. 'Dynamic Hydrogen Multifuel' (DHM) is an engine control and fuel system technology that uses flexible blending of hydrogen and another fuel to optimize emissions and overall fuel economy in a spark ignition engine. DHM vehicles can enhance emissions and fuel economy using techniques such as cold-starting or idling on pure hydrogen. Blending hydrogen can extend lean operation and exhaust gas recirculation limits while normal engine power and vehicle range can be maintained by the conventional fuel. Essentially DHM vehicles are a near-term intermediate technology which provides significant emissions benefits in a vehicle which is sufficiently economical, practical and familiar to achieve significant production numbers and significant fuel station load. The factors leading to successful implementation of current hydrogen filling stations must also be understood if the infrastructure is to be developed further. The paper discusses important lessons on the development of alternative fuel infrastructure that have been learned from natural gas; why were natural gas vehicle conversions largely successful in Argentina while failing in Canada and New Zealand? What ideas can be distilled from the previous successes and failures of the attempted introduction of a new vehicle fuel? It is proposed that hydrogen infrastructure can be developed by introducing a catalytic, near-term technology to provide fuel station demand and operating experience. However, it is imperative to understand the lessons of historic failures and present successes. (author)

  1. Climate Prediction Center (CPC) U.S. Hazards Outlook

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center releases a US Hazards Outlook daily, Monday through Friday. The product highlights regions of anticipated hazardous weather during the...

  2. Climate Prediction Center (CPC) Madden-Julian Oscillation (MJO) Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) Madden Julian Oscillation index (MJO) is a dataset that allows evaluation of the strength and phase of the MJO during the dataset...

  3. Electric power from near-term fusion reactors

    International Nuclear Information System (INIS)

    Longhurst, G.R.; Deis, G.A.; Miller, L.G.

    1981-01-01

    This paper examines requirements and possbilities of electric power production on near-term fusion reactors using low temperature cycle technology similar to that used in some geothermal power systems. Requirements include the need for a working fluid with suitable thermodynamics properties and which is free of oxygen and hydrogen to facilitate tritium management. Thermal storage will also be required due to the short system thermal time constants on near-time reactors. It is possbile to use the FED shield in a binary power cycle, and results are presented of thermodynamic analyses of this system

  4. Practical methods for near-term piloted Mars missions

    Science.gov (United States)

    Zubrin, Robert M.; Weaver, David B.

    1993-01-01

    An evaluation is made of ways of using near-term technologies for direct and semidirect manned Mars missions. A notable feature of the present schemes is the in situ propellant production of CH4/O2 and H2O on the Martian surface in order to reduce surface consumable and return propellant requirements. Medium-energy conjunction class trajectories are shown to be optimal for such missions. Attention is given to the backup plans and abort philosophy of these missions. Either the Russian Energia B or U.S. Saturn VII launch vehicles may be used.

  5. The interactive roles of mastery climate and performance climate in predicting intrinsic motivation.

    Science.gov (United States)

    Buch, R; Nerstad, C G L; Säfvenbom, R

    2017-02-01

    This study examined the interplay between perceived mastery and performance climates in predicting increased intrinsic motivation. The results of a two-wave longitudinal study comprising of 141 individuals from three military academies revealed a positive relationship between a perceived mastery climate and increased intrinsic motivation only for individuals who perceived a low performance climate. This finding suggests a positive relationship between a perceived mastery climate and increased intrinsic motivation only when combined with low perceptions of a performance climate. Hence, introducing a performance climate in addition to a mastery climate can be an undermining motivational strategy, as it attenuates the positive relationship between a mastery climate and increased intrinsic motivation. Implications for future research and practice are discussed. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  6. World oil market fundamentals - Part One: The near term outlook

    International Nuclear Information System (INIS)

    Dwarkin, J.; Morton, K.; Datta, R.

    1998-03-01

    Potential implications of a number of uncertainties currently affecting the world oil market are assessed. The influence of the interplay of geopolitical events on demand and supply, inventories, prices and price trends are reviewed. Reference prices which industry and governments can use for investment and policy evaluations are provided. In this volume, the emphasis is on near term developments, with a review of the uncertainties surrounding these projections. Three different scenarios are postulated for the near term, each one taking into account different levels of Iraqi exports during the period which would effect available inventories, and hence price. Depending on which of the three scenarios actually comes to pass, unless refiners are prepared to build up inventories well beyond seasonal norms, or producers shut in, the prevailing view is that oil prices will be under severe pressure during most of 1998 and 1999. Over the longer term, however, the analysis suggests that an average real value of US$18.00 - $18.50 per barrel remains a reasonable expectation as a sustainable price. 34 refs., tabs., figs

  7. Climate change affects rainmakers' predictions | IDRC - International ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    2010-10-08

    Oct 8, 2010 ... English · Français ... animals, associated with seasonal changes,” Mary O'Neill of Climate Change Adaptation in Africa ( CCAA ) told MediaGlobal. ... and the meteorologists forecast apply on the national and regional level.

  8. Climatic extremes improve predictions of spatial patterns of tree species

    Science.gov (United States)

    Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

    2009-01-01

    Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

  9. Climate Modeling and Causal Identification for Sea Ice Predictability

    Energy Technology Data Exchange (ETDEWEB)

    Hunke, Elizabeth Clare [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urrego Blanco, Jorge Rolando [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urban, Nathan Mark [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-02-12

    This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments in which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.

  10. Near term hybrid passenger vehicle development program, phase 1

    Science.gov (United States)

    1980-01-01

    Missions for hybrid vehicles that promise to yield high petroleum impact were identified and a preliminary design, was developed that satisfies the mission requirements and performance specifications. Technologies that are critical to successful vehicle design, development and fabrication were determined. Trade-off studies to maximize fuel savings were used to develop initial design specifications of the near term hybrid vehicle. Various designs were "driven" through detailed computer simulations which calculate the petroleum consumption in standard driving cycles, the petroleum and electricity consumptions over the specified missions, and the vehicle's life cycle costs over a 10 year vehicle lifetime. Particular attention was given to the selection of the electric motor, heat engine, drivetrain, battery pack and control system. The preliminary design reflects a modified current compact car powered by a currently available turbocharged diesel engine and a 24 kW (peak) compound dc electric motor.

  11. Near-term electric vehicle program: Phase I, final report

    Energy Technology Data Exchange (ETDEWEB)

    Rowlett, B. H.; Murry, R.

    1977-08-01

    A final report is given for an Energy Research and Development Administration effort aimed at a preliminary design of an energy-efficient electric commuter car. An electric-powered passenger vehicle using a regenerative power system was designed to meet the near-term ERDA electric automobile goals. The program objectives were to (1) study the parameters that affect vehicle performance, range, and cost; (2) design an entirely new electric vehicle that meets performance and economic requirements; and (3) define a program to develop this vehicle design for production in the early 1980's. The design and performance features of the preliminary (baseline) electric-powered passenger vehicle design are described, including the baseline power system, system performance, economic analysis, reliability and safety, alternate designs and options, development plan, and conclusions and recommendations. All aspects of the baseline design were defined in sufficient detail to verify performance expectations and system feasibility.

  12. Near-term benefits of the plant life extension program

    International Nuclear Information System (INIS)

    Kaushansky, M.M.

    1987-01-01

    The aging process can be expected to reduce the availability and increase the production costs of nuclear power plants over time. To mitigate this process and recover or enhance plant availability, capacity, thermal efficiency, and maintenance expenditures, the utility must dedicate increased attention and commitment to a comprehensive plant life extension (PLEX) program. Improvements must be justified by balancing the cost of the recommended modifications with the economic value of benefits obtained from its implementation. It is often extremely difficult for utility management to make an optimal selection from among hundreds of proposed projects, most of which are cost-effective. A properly structured PLEX program with an emphasis on near-term benefits should provide the utility with a means of evaluating proposed projects, thus determining the optimum combination for authorization and implementation

  13. The origins of computer weather prediction and climate modeling

    International Nuclear Information System (INIS)

    Lynch, Peter

    2008-01-01

    Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed

  14. The Urgent Need for Improved Climate Models and Predictions

    Science.gov (United States)

    Goddard, Lisa; Baethgen, Walter; Kirtman, Ben; Meehl, Gerald

    2009-09-01

    An investment over the next 10 years of the order of US$2 billion for developing improved climate models was recommended in a report (http://wcrp.wmo.int/documents/WCRP_WorldModellingSummit_Jan2009.pdf) from the May 2008 World Modelling Summit for Climate Prediction, held in Reading, United Kingdom, and presented by the World Climate Research Programme. The report indicated that “climate models will, as in the past, play an important, and perhaps central, role in guiding the trillion dollar decisions that the peoples, governments and industries of the world will be making to cope with the consequences of changing climate.” If trillions of dollars are going to be invested in making decisions related to climate impacts, an investment of $2 billion, which is less than 0.1% of that amount, to provide better climate information seems prudent. One example of investment in adaptation is the World Bank's Climate Investment Fund, which has drawn contributions of more than $6 billion for work on clean technologies and adaptation efforts in nine pilot countries and two pilot regions. This is just the beginning of expenditures on adaptation efforts by the World Bank and other mechanisms, focusing on only a small fraction of the nations of the world and primarily aimed at anticipated anthropogenic climate change. Moreover, decisions are being made now, all around the world—by individuals, companies, and governments—that affect people and their livelihoods today, not just 50 or more years in the future. Climate risk management, whether related to projects of the scope of the World Bank's or to the planning and decisions of municipalities, will be best guided by meaningful climate information derived from observations of the past and model predictions of the future.

  15. Statistical prediction of Late Miocene climate

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A; Gupta, S.M.

    by making certain simplifying assumptions; for example in modelling ocean 4 currents, the geostrophic approximation is made. In case of statistical prediction no such a priori assumption need be made. statistical prediction comprises of using observed data... the number of equations. In this case the equations are overdetermined, and therefore one has to look for a solution that best fits the sample data in a least squares sense. To this end we express the sample .... (2.1)+ ry = y + data as follows: n L c. (x...

  16. A perspective on sustained marine observations for climate modelling and prediction.

    Science.gov (United States)

    Dunstone, Nick J

    2014-09-28

    Here, I examine some of the many varied ways in which sustained global ocean observations are used in numerical modelling activities. In particular, I focus on the use of ocean observations to initialize predictions in ocean and climate models. Examples are also shown of how models can be used to assess the impact of both current ocean observations and to simulate that of potential new ocean observing platforms. The ocean has never been better observed than it is today and similarly ocean models have never been as capable at representing the real ocean as they are now. However, there remain important unanswered questions that can likely only be addressed via future improvements in ocean observations. In particular, ocean observing systems need to respond to the needs of the burgeoning field of near-term climate predictions. Although new ocean observing platforms promise exciting new discoveries, there is a delicate balance to be made between their funding and that of the current ocean observing system. Here, I identify the need to secure long-term funding for ocean observing platforms as they mature, from a mainly research exercise to an operational system for sustained observation over climate change time scales. At the same time, considerable progress continues to be made via ship-based observing campaigns and I highlight some that are dedicated to addressing uncertainties in key ocean model parametrizations. The use of ocean observations to understand the prominent long time scale changes observed in the North Atlantic is another focus of this paper. The exciting first decade of monitoring of the Atlantic meridional overturning circulation by the RAPID-MOCHA array is highlighted. The use of ocean and climate models as tools to further probe the drivers of variability seen in such time series is another exciting development. I also discuss the need for a concerted combined effort from climate models and ocean observations in order to understand the current slow

  17. Status and near-term plans for DIII-D

    International Nuclear Information System (INIS)

    Davis, L.G.; Callis, R.W.; Luxon, J.L.; Stambaugh, R.D.

    1987-10-01

    The DIII-D tokamak at GA Technologies began plasma operation in February of 1986 and is dedicated to the study of highly non-circular plasmas. High beta operation with enhanced energy confinement is paramount among the goals of the DIII-D research program. Commissioning of the device and facility has verified the design capability including coil and vessel loading, volt-second consumption, bakeout temperature, vessel armor, and neutral beamline thermal integrity and control systems performance. Initial experimental results demonstrate the DIII-D is capable of attaining high confinement (H-mode) discharges in a divertor configuration using modest neutral beam heating or ECH. Record values of I/sub p/aB/sub T/ have been achieved with ohmic heating as a first step toward operation at high values of toroidal beta and record values of beta have been achieved using neutral beam heating. This paper summarizes results to date and gives the near term plans for the facility. 13 refs., 6 figs., 1 tab

  18. An analysis of prediction skill of monthly mean climate variability

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Arun; Chen, Mingyue; Wang, Wanqiu [Climate Prediction Center, National Centers for Environmental Prediction (CPC/NCEP), Camp Springs, MD (United States)

    2011-09-15

    In this paper, lead-time and spatial dependence in skill for prediction of monthly mean climate variability is analyzed. The analysis is based on a set of extensive hindcasts from the Climate Forecast System at the National Centers for Environmental Prediction. The skill characteristics of initialized predictions is also compared with the AMIP simulations forced with the observed sea surface temperature (SST) to quantify the role of initial versus boundary conditions in the prediction of monthly means. The analysis is for prediction of monthly mean SST, precipitation, and 200-hPa height. The results show a rapid decay in skill with lead time for the atmospheric variables in the extratropical latitudes. Further, after a lead-time of approximately 30-40 days, the skill of monthly mean prediction is essentially a boundary forced problem, with SST anomalies in the tropical central/eastern Pacific playing a dominant role. Because of the larger contribution from the atmospheric internal variability to monthly time-averages (compared to seasonal averages), skill for monthly mean prediction associated with boundary forcing is also lower. The analysis indicates that the prospects of skillful prediction of monthly means may remain a challenging problem, and may be limited by inherent limits in predictability. (orig.)

  19. The Impact of Ocean Observations in Seasonal Climate Prediction

    Science.gov (United States)

    Rienecker, Michele; Keppenne, Christian; Kovach, Robin; Marshak, Jelena

    2010-01-01

    The ocean provides the most significant memory for the climate system. Hence, a critical element in climate forecasting with coupled models is the initialization of the ocean with states from an ocean data assimilation system. Remotely-sensed ocean surface fields (e.g., sea surface topography, SST, winds) are now available for extensive periods and have been used to constrain ocean models to provide a record of climate variations. Since the ocean is virtually opaque to electromagnetic radiation, the assimilation of these satellite data is essential to extracting the maximum information content. More recently, the Argo drifters have provided unprecedented sampling of the subsurface temperature and salinity. Although the duration of this observation set has been too short to provide solid statistical evidence of its impact, there are indications that Argo improves the forecast skill of coupled systems. This presentation will address the impact these different observations have had on seasonal climate predictions with the GMAO's coupled model.

  20. Predicting vulnerabilities of North American shorebirds to climate change.

    Directory of Open Access Journals (Sweden)

    Hector Galbraith

    Full Text Available Despite an increase in conservation efforts for shorebirds, there are widespread declines of many species of North American shorebirds. We wanted to know whether these declines would be exacerbated by climate change, and whether relatively secure species might become at-risk species. Virtually all of the shorebird species breeding in the USA and Canada are migratory, which means climate change could affect extinction risk via changes on the breeding, wintering, and/or migratory refueling grounds, and that ecological synchronicities could be disrupted at multiple sites. To predict the effects of climate change on shorebird extinction risks, we created a categorical risk model complementary to that used by Partners-in-Flight and the U.S. Shorebird Conservation Plan. The model is based on anticipated changes in breeding, migration, and wintering habitat, degree of dependence on ecological synchronicities, migration distance, and degree of specialization on breeding, migration, or wintering habitat. We evaluated 49 species, and for 3 species we evaluated 2 distinct populations each, and found that 47 (90% taxa are predicted to experience an increase in risk of extinction. No species was reclassified into a lower-risk category, although 6 species had at least one risk factor decrease in association with climate change. The number of species that changed risk categories in our assessment is sensitive to how much of an effect of climate change is required to cause the shift, but even at its least sensitive, 20 species were at the highest risk category for extinction. Based on our results it appears that shorebirds are likely to be highly vulnerable to climate change. Finally, we discuss both how our approach can be integrated with existing risk assessments and potential future directions for predicting change in extinction risk due to climate change.

  1. Climate Prediction Center (CPC) Rainfall Estimator (RFE) for Africa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — As of January 1, 2001, RFE version 2.0 has been implemented by NOAA?s Climate Prediction Center. Created by Ping-Ping Xie, this replaces RFE 1.0 the previous...

  2. Predicting Climate Change Impacts to the Canadian Boreal Forest

    Directory of Open Access Journals (Sweden)

    Trisalyn A. Nelson

    2014-03-01

    Full Text Available Climate change is expected to alter temperature, precipitation, and seasonality with potentially acute impacts on Canada’s boreal. In this research we predicted future spatial distributions of biodiversity in Canada’s boreal for 2020, 2050, and 2080 using indirect indicators derived from remote sensing and based on vegetation productivity. Vegetation productivity indices, representing annual amounts and variability of greenness, have been shown to relate to tree and wildlife richness in Canada’s boreal. Relationships between historical satellite-derived productivity and climate data were applied to modelled scenarios of future climate to predict and map potential future vegetation productivity for 592 regions across Canada. Results indicated that the pattern of vegetation productivity will become more homogenous, particularly west of Hudson Bay. We expect climate change to impact biodiversity along north/south gradients and by 2080 vegetation distributions will be dominated by processes of seasonality in the north and a combination of cumulative greenness and minimum cover in the south. The Hudson Plains, which host the world’s largest and most contiguous wetland, are predicted to experience less seasonality and more greenness. The spatial distribution of predicted trends in vegetation productivity was emphasized over absolute values, in order to support regional biodiversity assessments and conservation planning.

  3. Antimatter Production for Near-Term Propulsion Applications

    Science.gov (United States)

    Gerrish, Harold P.; Schmidt, George R.

    1999-01-01

    This presentation discusses the use and potential of power generated from Proton-Antiproton Annihilation. The problem is that there is not enough production of anti-protons, and that the production methods are inefficient. The cost for 1 gram of antiprotons is estimated at 62.5 trillion dollars. Applications which require large quantities (i.e., about 1 kg) will require dramatic improvements in the efficiency of the production of the antiprotons. However, applications which involve small quantities (i.e., 1 to 10 micrograms may be practical with a relative expansion of capacities. There are four "conventional" antimatter propulsion concepts which are: (1) the solid core, (2) the gas core, (3) the plasma core, and the (4) beam core. These are compared in terms of specific impulse, propulsive energy utilization and vehicle structure/propellant mass ratio. Antimatter-catalyzed fusion propulsion is also evaluated. The improvements outlined in the presentation to the Fermilab production, and other sites. capability would result in worldwide capacity of several micrograms per year, by the middle of the next decade. The conclusions drawn are: (1) the Conventional antimatter propulsion IS not practical due to large p-bar requirement; (2) Antimatter-catalyzed systems can be reasonably considered this "solves" energy cost problem by employing substantially smaller quantities; (3) With current infrastructure, cost for 1 microgram of p-bars is $62.5 million, but with near-term improvements cost should drop; (4) Milligram-scale facility would require a $15 billion investment, but could produce 1 mg, at $0.1/kW-hr, for $6.25 million.

  4. Computational data sciences for assessment and prediction of climate extremes

    Science.gov (United States)

    Ganguly, A. R.

    2011-12-01

    Climate extremes may be defined inclusively as severe weather events or large shifts in global or regional weather patterns which may be caused or exacerbated by natural climate variability or climate change. This area of research arguably represents one of the largest knowledge-gaps in climate science which is relevant for informing resource managers and policy makers. While physics-based climate models are essential in view of non-stationary and nonlinear dynamical processes, their current pace of uncertainty reduction may not be adequate for urgent stakeholder needs. The structure of the models may in some cases preclude reduction of uncertainty for critical processes at scales or for the extremes of interest. On the other hand, methods based on complex networks, extreme value statistics, machine learning, and space-time data mining, have demonstrated significant promise to improve scientific understanding and generate enhanced predictions. When combined with conceptual process understanding at multiple spatiotemporal scales and designed to handle massive data, interdisciplinary data science methods and algorithms may complement or supplement physics-based models. Specific examples from the prior literature and our ongoing work suggests how data-guided improvements may be possible, for example, in the context of ocean meteorology, climate oscillators, teleconnections, and atmospheric process understanding, which in turn can improve projections of regional climate, precipitation extremes and tropical cyclones in an useful and interpretable fashion. A community-wide effort is motivated to develop and adapt computational data science tools for translating climate model simulations to information relevant for adaptation and policy, as well as for improving our scientific understanding of climate extremes from both observed and model-simulated data.

  5. Near-term Forecasting of Solar Total and Direct Irradiance for Solar Energy Applications

    Science.gov (United States)

    Long, C. N.; Riihimaki, L. D.; Berg, L. K.

    2012-12-01

    Integration of solar renewable energy into the power grid, like wind energy, is hindered by the variable nature of the solar resource. One challenge of the integration problem for shorter time periods is the phenomenon of "ramping events" where the electrical output of the solar power system increases or decreases significantly and rapidly over periods of minutes or less. Advance warning, of even just a few minutes, allows power system operators to compensate for the ramping. However, the ability for short-term prediction on such local "point" scales is beyond the abilities of typical model-based weather forecasting. Use of surface-based solar radiation measurements has been recognized as a likely solution for providing input for near-term (5 to 30 minute) forecasts of solar energy availability and variability. However, it must be noted that while fixed-orientation photovoltaic panel systems use the total (global) downwelling solar radiation, tracking photovoltaic and solar concentrator systems use only the direct normal component of the solar radiation. Thus even accurate near-term forecasts of total solar radiation will under many circumstances include inherent inaccuracies with respect to tracking systems due to lack of information of the direct component of the solar radiation. We will present examples and statistical analyses of solar radiation partitioning showing the differences in the behavior of the total/direct radiation with respect to the near-term forecast issue. We will present an overview of the possibility of using a network of unique new commercially available total/diffuse radiometers in conjunction with a near-real-time adaptation of the Shortwave Radiative Flux Analysis methodology (Long and Ackerman, 2000; Long et al., 2006). The results are used, in conjunction with persistence and tendency forecast techniques, to provide more accurate near-term forecasts of cloudiness, and both total and direct normal solar irradiance availability and

  6. State-of-the-Art Climate Predictions for Energy Climate Services

    Science.gov (United States)

    Torralba-Fernandez, Veronica; Davis, Melanie; Doblas-Reyes, Francisco J.; Gonzalez-Reviriego, Nube

    2015-04-01

    Climate predictions tailored to the energy sector represent the cutting edge in climate sciences to forecast wind power generation. At seasonal time scales, current energy practices use a deterministic approach based on retrospective climatology, but climate predictions have recently been shown to provide additional value. For this reason, probabilistic climate predictions of near surface winds can allow end users to take calculated, precautionary action with a potential cost savings to their operations. As every variable predicted in a coupled model forecast system, the prediction of wind speed is affected by biases. To overcome this, two different techniques for the post-processing of ensemble forecasts are considered: a simple bias correction and a calibration method. The former is based on the assumption that the reference and predicted distributions are well approximated by a normal distribution. The latter is a calibration technique which inflates the model variance, and the inflation of the ensemble is required in order to obtain a reliable outcome. Both methods use the "one-year out" cross-validated mode, and they provide corrected forecasts with improved statistical properties. The impact of these bias corrections on the quality of the ECMWF S4 predictions of near surface wind speed during winter is explored. To offer a comprehensive picture of the post-processing effect on the forecast quality of the system, it is necessary to use several scoring measures: rank histograms, reliability diagrams and skill maps. These tools are essential to assess different aspects of the forecasts, and to observe changes in their properties when the two methods are applied. This study reveals that the different techniques to correct the predictions produce a statistically consistent ensemble. However, the operations performed on the forecasts decrease their skill which correspond to an increase in the uncertainty. Therefore, even though the bias correction is fundamental

  7. Initializing decadal climate predictions over the North Atlantic region

    Science.gov (United States)

    Matei, Daniela Mihaela; Pohlmann, Holger; Jungclaus, Johann; Müller, Wolfgang; Haak, Helmuth; Marotzke, Jochem

    2010-05-01

    Decadal climate prediction aims to predict the internally-generated decadal climate variability in addition to externally-forced climate change signal. In order to achieve this it is necessary to start the predictions from the current climate state. In this study we investigate the forecast skill of the North Atlantic decadal climate predictions using two different ocean initialization strategies. First we apply an assimilation of ocean synthesis data provided by the GECCO project (Köhl and Stammer, 2008) as initial conditions for the coupled model ECHAM5/MPI-OM. Hindcast experiments are then performed over the period 1952-2001. An alternative approach is one in which the subsurface ocean temperature and salinity are diagnosed from an ensemble of ocean model runs forced by the NCEP-NCAR atmospheric reanalyzes for the period 1948-2007, then nudge into the coupled model to produce initial conditions for the hindcast experiments. An anomaly coupling scheme is used in both approaches to avoid the hindcast drift and the associated initial shock. Differences between the two assimilation approaches are discussed by comparing them with the observational data in key regions and processes. We asses the skill of the initialized decadal hindcast experiments against the prediction skill of the non-initialized hindcasts simulation. We obtain an overview of the regions with the highest predictability from the regional distribution of the anomaly correlation coefficients and RMSE for the SAT. For the first year the hindcast skill is increased over almost all ocean regions in the NCEP-forced approach. This increase in the hindcast skill for the 1 year lead time is somewhat reduced in the GECCO approach. At lead time 5yr and 10yr, the skill enhancement is still found over the North Atlantic and North Pacific regions. We also consider the potential predictability of the Atlantic Meridional Overturning Circulation (AMOC) and Nordic Seas Overflow by comparing the predicted values to

  8. Empirically derived climate predictability over the extratropical northern hemisphere

    Directory of Open Access Journals (Sweden)

    J. B. Elsner

    1994-01-01

    Full Text Available A novel application of a technique developed from chaos theory is used in describing seasonal to interannual climate predictability over the Northern Hemisphere (NH. The technique is based on an empirical forecast scheme - local approximation in a reconstructed phase space - for time-series data. Data are monthly 500 hPa heights on a latitude-longitude grid covering the NH from 20° N to the equator. Predictability is estimated based on the linear correlation between actual and predicted heights averaged over a forecast range of one- to twelve.month lead. The method is capable of extracting the major climate signals on this time scale including ENSO and the North Atlantic Oscillation.

  9. Classical boson sampling algorithms with superior performance to near-term experiments

    Science.gov (United States)

    Neville, Alex; Sparrow, Chris; Clifford, Raphaël; Johnston, Eric; Birchall, Patrick M.; Montanaro, Ashley; Laing, Anthony

    2017-12-01

    It is predicted that quantum computers will dramatically outperform their conventional counterparts. However, large-scale universal quantum computers are yet to be built. Boson sampling is a rudimentary quantum algorithm tailored to the platform of linear optics, which has sparked interest as a rapid way to demonstrate such quantum supremacy. Photon statistics are governed by intractable matrix functions, which suggests that sampling from the distribution obtained by injecting photons into a linear optical network could be solved more quickly by a photonic experiment than by a classical computer. The apparently low resource requirements for large boson sampling experiments have raised expectations of a near-term demonstration of quantum supremacy by boson sampling. Here we present classical boson sampling algorithms and theoretical analyses of prospects for scaling boson sampling experiments, showing that near-term quantum supremacy via boson sampling is unlikely. Our classical algorithm, based on Metropolised independence sampling, allowed the boson sampling problem to be solved for 30 photons with standard computing hardware. Compared to current experiments, a demonstration of quantum supremacy over a successful implementation of these classical methods on a supercomputer would require the number of photons and experimental components to increase by orders of magnitude, while tackling exponentially scaling photon loss.

  10. Decadal climate prediction with a refined anomaly initialisation approach

    Science.gov (United States)

    Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco J.; Hawkins, Ed; Nichols, Nancy K.

    2017-03-01

    In decadal prediction, the objective is to exploit both the sources of predictability from the external radiative forcings and from the internal variability to provide the best possible climate information for the next decade. Predicting the climate system internal variability relies on initialising the climate model from observational estimates. We present a refined method of anomaly initialisation (AI) applied to the ocean and sea ice components of the global climate forecast model EC-Earth, with the following key innovations: (1) the use of a weight applied to the observed anomalies, in order to avoid the risk of introducing anomalies recorded in the observed climate, whose amplitude does not fit in the range of the internal variability generated by the model; (2) the AI of the ocean density, instead of calculating it from the anomaly initialised state of temperature and salinity. An experiment initialised with this refined AI method has been compared with a full field and standard AI experiment. Results show that the use of such refinements enhances the surface temperature skill over part of the North and South Atlantic, part of the South Pacific and the Mediterranean Sea for the first forecast year. However, part of such improvement is lost in the following forecast years. For the tropical Pacific surface temperature, the full field initialised experiment performs the best. The prediction of the Arctic sea-ice volume is improved by the refined AI method for the first three forecast years and the skill of the Atlantic multidecadal oscillation is significantly increased compared to a non-initialised forecast, along the whole forecast time.

  11. Predicting climate change impacts on polar bear litter size.

    Science.gov (United States)

    Molnár, Péter K; Derocher, Andrew E; Klanjscek, Tin; Lewis, Mark A

    2011-02-08

    Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use mechanistic energy budget models and data obtainable under current conditions to predict polar bear litter size under future conditions. In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40-73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55-100% if break-up occurs 2 months earlier. Simultaneously, mean litter size would decrease by 22-67% and 44-100%, respectively. The expected timeline for these declines varies with climate-model-specific sea ice predictions. Similar litter size declines may occur in over one-third of the global polar bear population.

  12. Singular vectors, predictability and ensemble forecasting for weather and climate

    International Nuclear Information System (INIS)

    Palmer, T N; Zanna, Laure

    2013-01-01

    The local instabilities of a nonlinear dynamical system can be characterized by the leading singular vectors of its linearized operator. The leading singular vectors are perturbations with the greatest linear growth and are therefore key in assessing the system’s predictability. In this paper, the analysis of singular vectors for the predictability of weather and climate and ensemble forecasting is discussed. An overview of the role of singular vectors in informing about the error growth rate in numerical models of the atmosphere is given. This is followed by their use in the initialization of ensemble weather forecasts. Singular vectors for the ocean and coupled ocean–atmosphere system in order to understand the predictability of climate phenomena such as ENSO and meridional overturning circulation are reviewed and their potential use to initialize seasonal and decadal forecasts is considered. As stochastic parameterizations are being implemented, some speculations are made about the future of singular vectors for the predictability of weather and climate for theoretical applications and at the operational level. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Lyapunov analysis: from dynamical systems theory to applications’. (review)

  13. Climate-Induced Boreal Forest Change: Predictions versus Current Observations

    Science.gov (United States)

    Soja, Amber J.; Tchebakova, Nadezda M.; French, Nancy H. F.; Flannigan, Michael D.; Shugart, Herman H.; Stocks, Brian J.; Sukhinin, Anatoly I.; Parfenova, E. I.; Chapin, F. Stuart, III; Stackhouse, Paul W., Jr.

    2007-01-01

    For about three decades, there have been many predictions of the potential ecological response in boreal regions to the currently warmer conditions. In essence, a widespread, naturally occurring experiment has been conducted over time. In this paper, we describe previously modeled predictions of ecological change in boreal Alaska, Canada and Russia, and then we investigate potential evidence of current climate-induced change. For instance, ecological models have suggested that warming will induce the northern and upslope migration of the treeline and an alteration in the current mosaic structure of boreal forests. We present evidence of the migration of keystone ecosystems in the upland and lowland treeline of mountainous regions across southern Siberia. Ecological models have also predicted a moisture-stress-related dieback in white spruce trees in Alaska, and current investigations show that as temperatures increase, white spruce tree growth is declining. Additionally, it was suggested that increases in infestation and wildfire disturbance would be catalysts that precipitate the alteration of the current mosaic forest composition. In Siberia, five of the last seven years have resulted in extreme fire seasons, and extreme fire years have also been more frequent in both Alaska and Canada. In addition, Alaska has experienced extreme and geographically expansive multi-year outbreaks of the spruce beetle, which had been previously limited by the cold, moist environment. We suggest that there is substantial evidence throughout the circumboreal region to conclude that the biosphere within the boreal terrestrial environment has already responded to the transient effects of climate change. Additionally, temperature increases and warming-induced change are progressing faster than had been predicted in some regions, suggesting a potential non-linear rapid response to changes in climate, as opposed to the predicted slow linear response to climate change.

  14. Geospatial Analysis of Near-Term Technical Potential of BECCS in the U.S.

    Science.gov (United States)

    Baik, E.; Sanchez, D.; Turner, P. A.; Mach, K. J.; Field, C. B.; Benson, S. M.

    2017-12-01

    Atmospheric carbon dioxide (CO2) removal using bioenergy with carbon capture and storage (BECCS) is crucial for achieving stringent climate change mitigation targets. To date, previous work discussing the feasibility of BECCS has largely focused on land availability and bioenergy potential, while CCS components - including capacity, injectivity, and location of potential storage sites - have not been thoroughly considered in the context of BECCS. A high-resolution geospatial analysis of both biomass production and potential geologic storage sites is conducted to consider the near-term deployment potential of BECCS in the U.S. The analysis quantifies the overlap between the biomass resource and CO2 storage locations within the context of storage capacity and injectivity. This analysis leverages county-level biomass production data from the U.S. Department of Energy's Billion Ton Report alongside potential CO2 geologic storage sites as provided by the USGS Assessment of Geologic Carbon Dioxide Storage Resources. Various types of lignocellulosic biomass (agricultural residues, dedicated energy crops, and woody biomass) result in a potential 370-400 Mt CO2 /yr of negative emissions in 2020. Of that CO2, only 30-31% of the produced biomass (110-120 Mt CO2 /yr) is co-located with a potential storage site. While large potential exists, there would need to be more than 250 50-MW biomass power plants fitted with CCS to capture all the co-located CO2 capacity in 2020. Neither absolute injectivity nor absolute storage capacity is likely to limit BECCS, but the results show regional capacity and injectivity constraints in the U.S. that had not been identified in previous BECCS analysis studies. The state of Illinois, the Gulf region, and western North Dakota emerge as the best locations for near-term deployment of BECCS with abundant biomass, sufficient storage capacity and injectivity, and the co-location of the two resources. Future studies assessing BECCS potential should

  15. Predicting impacts of climate change on Fasciola hepatica risk.

    Science.gov (United States)

    Fox, Naomi J; White, Piran C L; McClean, Colin J; Marion, Glenn; Evans, Andy; Hutchings, Michael R

    2011-01-10

    Fasciola hepatica (liver fluke) is a physically and economically devastating parasitic trematode whose rise in recent years has been attributed to climate change. Climate has an impact on the free-living stages of the parasite and its intermediate host Lymnaea truncatula, with the interactions between rainfall and temperature having the greatest influence on transmission efficacy. There have been a number of short term climate driven forecasts developed to predict the following season's infection risk, with the Ollerenshaw index being the most widely used. Through the synthesis of a modified Ollerenshaw index with the UKCP09 fine scale climate projection data we have developed long term seasonal risk forecasts up to 2070 at a 25 km square resolution. Additionally UKCIP gridded datasets at 5 km square resolution from 1970-2006 were used to highlight the climate-driven increase to date. The maps show unprecedented levels of future fasciolosis risk in parts of the UK, with risk of serious epidemics in Wales by 2050. The seasonal risk maps demonstrate the possible change in the timing of disease outbreaks due to increased risk from overwintering larvae. Despite an overall long term increase in all regions of the UK, spatio-temporal variation in risk levels is expected. Infection risk will reduce in some areas and fluctuate greatly in others with a predicted decrease in summer infection for parts of the UK due to restricted water availability. This forecast is the first approximation of the potential impacts of climate change on fasciolosis risk in the UK. It can be used as a basis for indicating where active disease surveillance should be targeted and where the development of improved mitigation or adaptation measures is likely to bring the greatest benefits.

  16. Predicting impacts of climate change on Fasciola hepatica risk.

    Directory of Open Access Journals (Sweden)

    Naomi J Fox

    2011-01-01

    Full Text Available Fasciola hepatica (liver fluke is a physically and economically devastating parasitic trematode whose rise in recent years has been attributed to climate change. Climate has an impact on the free-living stages of the parasite and its intermediate host Lymnaea truncatula, with the interactions between rainfall and temperature having the greatest influence on transmission efficacy. There have been a number of short term climate driven forecasts developed to predict the following season's infection risk, with the Ollerenshaw index being the most widely used. Through the synthesis of a modified Ollerenshaw index with the UKCP09 fine scale climate projection data we have developed long term seasonal risk forecasts up to 2070 at a 25 km square resolution. Additionally UKCIP gridded datasets at 5 km square resolution from 1970-2006 were used to highlight the climate-driven increase to date. The maps show unprecedented levels of future fasciolosis risk in parts of the UK, with risk of serious epidemics in Wales by 2050. The seasonal risk maps demonstrate the possible change in the timing of disease outbreaks due to increased risk from overwintering larvae. Despite an overall long term increase in all regions of the UK, spatio-temporal variation in risk levels is expected. Infection risk will reduce in some areas and fluctuate greatly in others with a predicted decrease in summer infection for parts of the UK due to restricted water availability. This forecast is the first approximation of the potential impacts of climate change on fasciolosis risk in the UK. It can be used as a basis for indicating where active disease surveillance should be targeted and where the development of improved mitigation or adaptation measures is likely to bring the greatest benefits.

  17. Nuclear Reactor Technology Assessment for Near Term Deployment

    International Nuclear Information System (INIS)

    2013-01-01

    One of the IAEA's statutory objectives is to 'seek to accelerate and enlarge the contribution of atomic energy to peace, health and prosperity throughout the world.' One way this objective is achieved is through the publication of a range of technical series. Two of these are the IAEA Nuclear Energy Series and the IAEA Safety Standards Series. According to Article III.A.6 of the IAEA Statute, the safety standards establish 'standards of safety for protection of health and minimization of danger to life and property'. The safety standards include the Safety Fundamentals, Safety Requirements and Safety Guides. These standards are written primarily in a regulatory style, and are binding on the IAEA for its own programmes. The principal users are the regulatory bodies in Member States and other national authorities. The IAEA Nuclear Energy Series comprises reports designed to encourage and assist R and D on, and application of, nuclear energy for peaceful uses. This includes practical examples to be used by owners and operators of utilities in Member States, implementing organizations, academia, and government officials, among others. This information is presented in guides, reports on technology status and advances, and best practices for peaceful uses of nuclear energy based on inputs from international experts. The IAEA Nuclear Energy Series complements the IAEA Safety Standards Series. Several IAEA Member States have embarked recently on initiatives to establish or reinvigorate nuclear power programmes. In response, the IAEA has developed several guidance and technical publications to identify with Member States the complex tasks associated with such an undertaking and to recommend the processes that can be used in the performance of this work. A major challenge in this undertaking, especially for newcomer Member States, is the process associated with reactor technology assessment (RTA) for near term deployment. RTA permits the evaluation, selection and deployment

  18. Nudging atmosphere and ocean reanalyses for seasonal climate predictions

    Science.gov (United States)

    Piontek, Robert; Baehr, Johanna; Kornblueh, Luis; Müller, Wolfgang Alexander; Haak, Helmuth; Botzet, Michael; Matei, Daniela

    2010-05-01

    Seasonal climate forecasts based on state-of-the-art climate models have been developed recently. Here, we critically discuss the obstacles encountered in the setup of the ECHAM6/MPIOM global coupled climate model to perform climate predictions on seasonal to decadal time scales. We particularly focus on the initialization procedure, especially on the implementation of the nudging scheme, in which different reanalysis products are used in the atmosphere (e.g.ERA40), and the ocean (e.g., GECCO). Nudging in the atmosphere appears to be sensitive to the following choices: limiting the spectral range of nudging, whether or not temperature is nudged, the strength of the nudging coefficient for surface pressure, and the height at which the planetary boundary layer is excluded from nudging. We find that including nudging in both the atmosphere and the ocean gives improved results over nudging only the ocean or the atmosphere. For the implementation of the nudging in the atmosphere, we find the most significant improvements in the solution when either the planetary boundary layer is excluded, or if nudging of temperature is omitted. There are significant improvements in the solution when resolution is increased in both the atmosphere and in the ocean. Our tests form the basis for the prediction system introduced in the abstract of Müller et al., where hindcasts are analysed as well.

  19. Near-term deployment of carbon capture and sequestration from biorefineries in the United States.

    Science.gov (United States)

    Sanchez, Daniel L; Johnson, Nils; McCoy, Sean T; Turner, Peter A; Mach, Katharine J

    2018-05-08

    Capture and permanent geologic sequestration of biogenic CO 2 emissions may provide critical flexibility in ambitious climate change mitigation. However, most bioenergy with carbon capture and sequestration (BECCS) technologies are technically immature or commercially unavailable. Here, we evaluate low-cost, commercially ready CO 2 capture opportunities for existing ethanol biorefineries in the United States. The analysis combines process engineering, spatial optimization, and lifecycle assessment to consider the technical, economic, and institutional feasibility of near-term carbon capture and sequestration (CCS). Our modeling framework evaluates least cost source-sink relationships and aggregation opportunities for pipeline transport, which can cost-effectively transport small CO 2 volumes to suitable sequestration sites; 216 existing US biorefineries emit 45 Mt CO 2 annually from fermentation, of which 60% could be captured and compressed for pipeline transport for under $25/tCO 2 A sequestration credit, analogous to existing CCS tax credits, of $60/tCO 2 could incent 30 Mt of sequestration and 6,900 km of pipeline infrastructure across the United States. Similarly, a carbon abatement credit, analogous to existing tradeable CO 2 credits, of $90/tCO 2 can incent 38 Mt of abatement. Aggregation of CO 2 sources enables cost-effective long-distance pipeline transport to distant sequestration sites. Financial incentives under the low-carbon fuel standard in California and recent revisions to existing federal tax credits suggest a substantial near-term opportunity to permanently sequester biogenic CO 2 This financial opportunity could catalyze the growth of carbon capture, transport, and sequestration; improve the lifecycle impacts of conventional biofuels; support development of carbon-negative fuels; and help fulfill the mandates of low-carbon fuel policies across the United States. Copyright © 2018 the Author(s). Published by PNAS.

  20. Selenium deficiency risk predicted to increase under future climate change.

    Science.gov (United States)

    Jones, Gerrad D; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P; Seneviratne, Sonia I; Smith, Pete; Winkel, Lenny H E

    2017-03-14

    Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980-1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate-soil interactions. Using moderate climate-change scenarios for 2080-2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate-soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change.

  1. A Standardized Evaluation System for Decadal Climate Prediction

    Science.gov (United States)

    Kadow, C.; Cubasch, U.

    2012-12-01

    The evaluation of decadal prediction systems is a scientific challenge as well as a technical challenge in the climate research. The major project MiKlip (www.fona-miklip.de) for medium-term climate prediction funded by the Federal Ministry of Education and Research in Germany (BMBF) has the aim to create a model system that can provide reliable decadal forecasts on climate and weather. The model system to be developed will be novel in several aspects, with great challenges for the methodology development. This concerns especially the determination of the initial conditions, the inclusion into the model of processes relevant to decadal predictions, the increase of the spatial resolution through regionalisation, the improvement or adjustment of statistical post-processing, and finally the synthesis and validation of the entire model system. Therefore, a standardized evaluation system will be part of the MiKlip system to validate it - developed by the project 'Integrated data and evaluation system for decadal scale prediction' (INTEGRATION). The presentation gives an overview of the different linkages of such a project, shows the different development stages and gives an outlook for users and possible end users in climate service. The technical interface combines all projects inside of MiKlip and invites them to participate in a common evaluation system. The system design and the validation strategy from a standalone tool in the beginning to a user friendly web based system using GRID technologies to an integrated part of the operational MiKlip system for industry and society will give the opportunity to enhance the MiKlip strategy. First results of different possibilities of such a system will be shown to present the scientific background through Taylor diagrams, ensemble skill scores and e.g. climatological means to show the usability and possibilities of MiKlip and the INTEGRATION project.

  2. Toward seamless weather-climate and environmental prediction

    Science.gov (United States)

    Brunet, Gilbert

    2016-04-01

    Over the last decade or so, predicting the weather, climate and atmospheric composition has emerged as one of the most important areas of scientific endeavor. This is partly because the remarkable increase in skill of current weather forecasts has made society more and more dependent on them day to day for a whole range of decision making. And it is partly because climate change is now widely accepted and the realization is growing rapidly that it will affect every person in the world profoundly, either directly or indirectly. One of the important endeavors of our societies is to remain at the cutting-edge of modelling and predicting the evolution of the fully coupled environmental system: atmosphere (weather and composition), oceans, land surface (physical and biological), and cryosphere. This effort will provide an increasingly accurate and reliable service across all the socio-economic sectors that are vulnerable to the effects of adverse weather and climatic conditions, whether now or in the future. This emerging challenge was at the center of the World Weather Open Science Conference (Montreal, 2014).The outcomes of the conference are described in the World Meteorological Organization (WMO) book: Seamless Prediction of the Earth System: from Minutes to Months, (G. Brunet, S. Jones, P. Ruti Eds., WMO-No. 1156, 2015). It is freely available on line at the WMO website. We will discuss some of the outcomes of the conference for the WMO World Weather Research Programme (WWRP) and Global Atmospheric Watch (GAW) long term goals and provide examples of seamless modelling and prediction across a range of timescales at convective and sub-kilometer scales for regional coupled forecasting applications at Environment and Climate Change Canada (ECCC).

  3. Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions

    NARCIS (Netherlands)

    Li, T.; Hasegawa, T.; Yin, X.; Zhu, Y.; Boote, K.; Adam, M.; Bregaglio, S.; Buis, S.; Confalonieri, R.; Fumoto, T.; Gaydon, D.; Marcaida III, M.; Nakagawa, H.; Oriol, P.; Ruane, A.C.; Ruget, F.; Singh, B.; Singh, U.; Tang, L.; Yoshida, H.; Zhang, Z.; Bouman, B.

    2015-01-01

    Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We

  4. Space reactor/organic Rankine conversion - A near-term state-of-the-art solution

    Science.gov (United States)

    Niggemann, R. E.; Lacey, D.

    The use of demonstrated reactor technology with organic Rankine cycle (ORC) power conversion can provide a low cost, minimal risk approach to reactor-powered electrical generation systems in the near term. Several reactor technologies, including zirconium hydride, EBR-II and LMFBR, have demonstrated long life and suitability for space application at the operating temperature required by an efficient ORC engine. While this approach would not replace the high temperature space reactor systems presently under development, it could be available in a nearer time frame at a low and predictable cost, allowing some missions requiring high power levels to be flown prior to the availability of advanced systems with lower specific mass. Although this system has relatively high efficiency, the heat rejection temperature is low, requiring a large radiator on the order of 3.4 sq m/kWe. Therefore, a deployable heat pipe radiator configuration will be required.

  5. Climate change and predicting soil loss from rainfall

    Science.gov (United States)

    Kinnell, Peter

    2017-04-01

    Conceptually, rainfall has a certain capacity to cause soil loss from an eroding area while soil surfaces have a certain resistance to being eroded by rainfall. The terms "rainfall erosivity' and "soil erodibility" are frequently used to encapsulate the concept and in the Revised Universal Soil Loss Equation (RUSLE), the most widely used soil loss prediction equation in the world, average annual values of the R "erosivity" factor and the K "erodibility" factor provide a basis for accounting for variation in rainfall erosion associated with geographic variations of climate and soils. In many applications of RUSLE, R and K are considered to be independent but in reality they are not. In RUSLE2, provision has been made to take account of the fact that K values determined using soil physical factors have to be adjusted for variations in climate because runoff is not directly included as a factor in determining R. Also, the USLE event erosivity index EI30 is better related to accounting for event sediment concentration than event soil loss. While the USLE-M, a modification of the USLE which includes runoff as a factor in determining the event erosivity index provides better estimates of event soil loss when event runoff is known, runoff prediction provides a challenge to modelling event soil loss as climate changes

  6. Predicted Changes in Climatic Niche and Climate Refugia of Conservation Priority Salamander Species in the Northeastern United States

    Directory of Open Access Journals (Sweden)

    William B. Sutton

    2014-12-01

    Full Text Available Global climate change represents one of the most extensive and pervasive threats to wildlife populations. Amphibians, specifically salamanders, are particularly susceptible to the effects of changing climates due to their restrictive physiological requirements and low vagility; however, little is known about which landscapes and species are vulnerable to climate change. Our study objectives included, (1 evaluating species-specific predictions (based on 2050 climate projections and vulnerabilities to climate change and (2 using collective species responses to identify areas of climate refugia for conservation priority salamanders in the northeastern United States. All evaluated salamander species were projected to lose a portion of their climatic niche. Averaged projected losses ranged from 3%–100% for individual species, with the Cow Knob Salamander (Plethodon punctatus, Cheat Mountain Salamander (Plethodon nettingi, Shenandoah Mountain Salamander (Plethodon virginia, Mabee’s Salamander (Ambystoma mabeei, and Streamside Salamander (Ambystoma barbouri predicted to lose at least 97% of their landscape-scale climatic niche. The Western Allegheny Plateau was predicted to lose the greatest salamander climate refugia richness (i.e., number of species with a climatically-suitable niche in a landscape patch, whereas the Central Appalachians provided refugia for the greatest number of species during current and projected climate scenarios. Our results can be used to identify species and landscapes that are likely to be further affected by climate change and potentially resilient habitats that will provide consistent climatic conditions in the face of environmental change.

  7. Study of a nuclear energy supplied steelmaking system for near-term application

    International Nuclear Information System (INIS)

    Yan, Xing L.; Kasahara, Seiji; Tachibana, Yukio; Kunitomi, Kazuhiko

    2012-01-01

    Conventional steelmaking processes involve intensive fossil fuel consumption and CO 2 emission. The system resulting from this study ties a steelmaking plant to a nuclear plant. The latter supplies the former all energy and feedstock with the exception of iron ore. The actual design takes on a multi-disciplinary approach: The nuclear plant employs a proven next-generation technology of fission reactor with 950 °C outlet temperature to produce electricity and heat. The plant construction saving and high efficiency keep the cogeneration cost down. The steelmaking plant employs conventional furnaces but substitutes hydrogen and oxygen for hydrocarbons as reactant and fuel. Water decomposition through an experimentally-demonstrated thermochemical process manufactures the feedstock gases required. Through essential safety features, particular a fully-passive nuclear safety, the design achieves physical proximity and yet operational independence of the two plants to facilitate inter-plant energy transmission. Calculated energy and material balance of the integrated system yields slightly over 1000 t steel per 1 MWt yr nuclear thermal energy. The steel cost is estimated competitive. The CO 2 emission amounts to 1% of conventional processes. The sustainable performance, economical potential, robust safety, and use of verified technological bases attract near-term deployment of this nuclear steelmaking system. -- Highlights: ► A steelmaking concept is proposed based on multi-disciplinary approach. ► It ties advanced nuclear fission reactor and energy conversion to thermochemical manufacture and direct iron making. ► Technological strength of each area is exploited to integrate a final process. ► Heat and material balance of the process is made to predict performance and cost. ► The system rules out fossil fuel use and CO 2 emission, and is near-term deployable.

  8. Cod Gadus morhua and climate change: processes, productivity and prediction

    DEFF Research Database (Denmark)

    Brander, Keith

    2010-01-01

    the causes. Investigation of cod Gadus morhua populations across the whole North Atlantic Ocean has shown large-scale patterns of change in productivity due to lower individual growth and condition, caused by large-scale climate forcing. If a population is being heavily exploited then a drop in productivity......Environmental factors act on individual fishes directly and indirectly. The direct effects on rates and behaviour can be studied experimentally and in the field, particularly with the advent of ever smarter tags for tracking fishes and their environment. Indirect effects due to changes in food......, predators, parasites and diseases are much more difficult to estimate and predict. Climate can affect all life-history stages through direct and indirect processes and although the consequences in terms of growth, survival and reproductive output can be monitored, it is often difficult to determine...

  9. Predicting Seagrass Occurrence in a Changing Climate Using Random Forests

    Science.gov (United States)

    Aydin, O.; Butler, K. A.

    2017-12-01

    Seagrasses are marine plants that can quickly sequester vast amounts of carbon (up to 100 times more and 12 times faster than tropical forests). In this work, we present an integrated GIS and machine learning approach to build a data-driven model of seagrass presence-absence. We outline a random forest approach that avoids the prevalence bias in many ecological presence-absence models. One of our goals is to predict global seagrass occurrence from a spatially limited training sample. In addition, we conduct a sensitivity study which investigates the vulnerability of seagrass to changing climate conditions. We integrate multiple data sources including fine-scale seagrass data from MarineCadastre.gov and the recently available globally extensive publicly available Ecological Marine Units (EMU) dataset. These data are used to train a model for seagrass occurrence along the U.S. coast. In situ oceans data are interpolated using Empirical Bayesian Kriging (EBK) to produce globally extensive prediction variables. A neural network is used to estimate probable future values of prediction variables such as ocean temperature to assess the impact of a warming climate on seagrass occurrence. The proposed workflow can be generalized to many presence-absence models.

  10. Probabilistic empirical prediction of seasonal climate: evaluation and potential applications

    Science.gov (United States)

    Dieppois, B.; Eden, J.; van Oldenborgh, G. J.

    2017-12-01

    Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a new evaluation of an established empirical system used to predict seasonal climate across the globe. Forecasts for surface air temperature, precipitation and sea level pressure are produced by the KNMI Probabilistic Empirical Prediction (K-PREP) system every month and disseminated via the KNMI Climate Explorer (climexp.knmi.nl). K-PREP is based on multiple linear regression and built on physical principles to the fullest extent with predictive information taken from the global CO2-equivalent concentration, large-scale modes of variability in the climate system and regional-scale information. K-PREP seasonal forecasts for the period 1981-2016 will be compared with corresponding dynamically generated forecasts produced by operational forecast systems. While there are many regions of the world where empirical forecast skill is extremely limited, several areas are identified where K-PREP offers comparable skill to dynamical systems. We discuss two key points in the future development and application of the K-PREP system: (a) the potential for K-PREP to provide a more useful basis for reference forecasts than those based on persistence or climatology, and (b) the added value of including K-PREP forecast information in multi-model forecast products, at least for known regions of good skill. We also discuss the potential development of

  11. Macroweather Predictions and Climate Projections using Scaling and Historical Observations

    Science.gov (United States)

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

    2017-12-01

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

  12. Near-term nanotechnology: the molecular fabrication of nanostructured materials

    Science.gov (United States)

    Gillett, Stephen L.

    1996-09-01

    The remarkably short timescales commonly predicted for achieving full molecular nanotechnology (MNT) are not realistic, as an enormous investment must be made up-front for a distant and ill-defined payoff. The reason is that technology, per se, is not an economic driver; economics instead drives technology. Hence, markets that could motivate the ongoing, incremental development of MNT must be sought. Such markets exist: they fundamentally consist of the molecular assembly of nano structured materials such as semipermeable membranes, catalysts, perfect crystalline fibres, and others. Although in theory atomically precise, such materials have no molecular moving parts and thus will be both easier to build and more robust. Some of these applications (e.g. catalysis), moreover, have huge, mature markets. Once a demand is established, further incremental development of primitive molecular assemblers, or `molecular looms', might then justify the analogies with the explosive development of computer hardware over the last few decades. Finally, the fact that many such applications are likely to be rendered obsolete by full MNT is irrelevant to their interim value as technology drivers.

  13. New climate on the Earth: understanding, predicting, reacting

    International Nuclear Information System (INIS)

    Le Treut, H.

    2009-01-01

    The objective of the Copenhagen meeting was to recast the Kyoto protocol, to widen it to all countries, to find a global agreement for the aid to vulnerable populations and for the abatement of greenhouse gases both from industrialized and emerging countries, including the USA and China. Scientific research has revealed the huge complexity of the climate machine and the difficulty to predict its evolution. What will be the sea level in 2100, the pressure on coastal areas, the expansion of desertification, the evolution of glaciers? Today no quantification is possible but it is demonstrated that our greenhouse gas emissions are responsible for the climate change, that this change is already irreversible and will affect all natural environments, and that a warming up greater than 2 deg. C will make climate evolution out of control. In this book, the author lists the actions to implement urgently: significantly reducing greenhouse gas emissions, implementing energy saving policies, limiting fossil fuels consumption, developing alternate energies, capturing and sequestering the CO 2 of thermal plants. We just have few decades in front of us to reduce the extent of the changes in progress and to be prepared to face the ensuing new inequalities. (J.S.)

  14. Climate Prediction Center - Monitoring & Data: La Niña Seasonal Maps and

    Science.gov (United States)

    page National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center ±a Case Selection Contact Richard Tinker [rtinker@ncep.noaa.gov], Climate Prediction Center significant climate signals: The La Niña episode, and long-term trends in average temperature and total

  15. Climate Prediction Center - El Niño/La Niña Home

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Information CPC Web Team HOME > El Niño/La Niña Forecasts Current U.S. Climate Outlook SST Forecasts Temperature and Anomalies NOAA/ National Weather Service National Centers for Environmental Prediction Climate

  16. A linear regression model for predicting PNW estuarine temperatures in a changing climate

    Science.gov (United States)

    Pacific Northwest coastal regions, estuaries, and associated ecosystems are vulnerable to the potential effects of climate change, especially to changes in nearshore water temperature. While predictive climate models simulate future air temperatures, no such projections exist for...

  17. prediction of the impacts of climate changes on the stream flow

    African Journals Online (AJOL)

    HOD

    Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on Ajali River watershed ... Climate is the synthesis of atmospheric conditions characteristic of a .... generator available in the SWAT model.

  18. Oil Trade and Climate Policy

    OpenAIRE

    Malik Curuk; Suphi Sen

    2015-01-01

    It has been argued that a depletable resource owner might optimally increase near-term supply in response to environmental policies promoting the development of alternative resources, which might render climate policy ineffective or even counterproductive. This paper empirically confirms this prediction using data on crude oil exports from OPEC to OECD countries between 2001-2010 in a gravity framework. It documents that oil exporters decrease prices and increase quantity of oil exports in re...

  19. Impact of climatic change on alpine ecosystems: inference and prediction

    Directory of Open Access Journals (Sweden)

    Nigel G. Yoccoz

    2011-01-01

    Full Text Available Alpine ecosystems will be greatly impacted by climatic change, but other factors, such as land use and invasive species, are likely to play an important role too. Climate can influence ecosystems at several levels. We describe some of them, stressing methodological approaches and available data. Climate can modify species phenology, such as flowering date of plants and hatching date in insects. It can also change directly population demography (survival, reproduction, dispersal, and therefore species distribution. Finally it can effect interactions among species – snow cover for example can affect the success of some predators. One characteristic of alpine ecosystems is the presence of snow cover, but surprisingly the role played by snow is relatively poorly known, mainly for logistical reasons. Even if we have made important progress regarding the development of predictive models, particularly so for distribution of alpine plants, we still need to set up observational and experimental networks which properly take into account the variability of alpine ecosystems and of their interactions with climate.Les écosystèmes alpins vont être grandement influencés par les changements climatiques à venir, mais d’autres facteurs, tels que l’utilisation des terres ou les espèces invasives, pourront aussi jouer un rôle important. Le climat peut influencer les écosystèmes à différents niveaux, et nous en décrivons certains, en mettant l’accent sur les méthodes utilisées et les données disponibles. Le climat peut d’abord modifier la phénologie des espèces, comme la date de floraison des plantes ou la date d’éclosion des insectes. Il peut ensuite affecter directement la démographie des espèces (survie, reproduction, dispersion et donc à terme leur répartition. Il peut enfin agir sur les interactions entre espèces – le couvert neigeux par exemple modifie le succès de certains prédateurs. Une caractéristique des

  20. Atlas : A library for numerical weather prediction and climate modelling

    Science.gov (United States)

    Deconinck, Willem; Bauer, Peter; Diamantakis, Michail; Hamrud, Mats; Kühnlein, Christian; Maciel, Pedro; Mengaldo, Gianmarco; Quintino, Tiago; Raoult, Baudouin; Smolarkiewicz, Piotr K.; Wedi, Nils P.

    2017-11-01

    The algorithms underlying numerical weather prediction (NWP) and climate models that have been developed in the past few decades face an increasing challenge caused by the paradigm shift imposed by hardware vendors towards more energy-efficient devices. In order to provide a sustainable path to exascale High Performance Computing (HPC), applications become increasingly restricted by energy consumption. As a result, the emerging diverse and complex hardware solutions have a large impact on the programming models traditionally used in NWP software, triggering a rethink of design choices for future massively parallel software frameworks. In this paper, we present Atlas, a new software library that is currently being developed at the European Centre for Medium-Range Weather Forecasts (ECMWF), with the scope of handling data structures required for NWP applications in a flexible and massively parallel way. Atlas provides a versatile framework for the future development of efficient NWP and climate applications on emerging HPC architectures. The applications range from full Earth system models, to specific tools required for post-processing weather forecast products. The Atlas library thus constitutes a step towards affordable exascale high-performance simulations by providing the necessary abstractions that facilitate the application in heterogeneous HPC environments by promoting the co-design of NWP algorithms with the underlying hardware.

  1. Climate Based Predictability of Oil Palm Tree Yield in Malaysia.

    Science.gov (United States)

    Oettli, Pascal; Behera, Swadhin K; Yamagata, Toshio

    2018-02-02

    The influence of local conditions and remote climate modes on the interannual variability of oil palm fresh fruit bunches (FFB) total yields in Malaysia and two major regions (Peninsular Malaysia and Sabah/Sarawak) is explored. On a country scale, the state of sea-surface temperatures (SST) in the tropical Pacific Ocean during the previous boreal winter is found to influence the regional climate. When El Niño occurs in the Pacific Ocean, rainfall in Malaysia reduces but air temperature increases, generating a high level of water stress for palm trees. As a result, the yearly production of FFB becomes lower than that of a normal year since the water stress during the boreal spring has an important impact on the total annual yields of FFB. Conversely, La Niña sets favorable conditions for palm trees to produce more FFB by reducing chances of water stress risk. The region of the Leeuwin current also seems to play a secondary role through the Ningaloo Niño/ Niña in the interannual variability of FFB yields. Based on these findings, a linear model is constructed and its ability to reproduce the interannual signal is assessed. This model has shown some skills in predicting the total FFB yield.

  2. Integrated model for predicting rice yield with climate change

    Science.gov (United States)

    Park, Jin-Ki; Das, Amrita; Park, Jong-Hwa

    2018-04-01

    Rice is the chief agricultural product and one of the primary food source. For this reason, it is of pivotal importance for worldwide economy and development. Therefore, in a decision-support-system both for the farmers and in the planning and management of the country's economy, forecasting yield is vital. However, crop yield, which is a dependent of the soil-bio-atmospheric system, is difficult to represent in statistical language. This paper describes a novel approach for predicting rice yield using artificial neural network, spatial interpolation, remote sensing and GIS methods. Herein, the variation in the yield is attributed to climatic parameters and crop health, and the normalized difference vegetation index from MODIS is used as an indicator of plant health and growth. Due importance was given to scaling up the input parameters using spatial interpolation and GIS and minimising the sources of error in every step of the modelling. The low percentage error (2.91) and high correlation (0.76) signifies the robust performance of the proposed model. This simple but effective approach is then used to estimate the influence of climate change on South Korean rice production. As proposed in the RCP8.5 scenario, an upswing in temperature may increase the rice yield throughout South Korea.

  3. Round and round: Little consensus exists on the near-term future of natural gas

    International Nuclear Information System (INIS)

    Lunan, D.

    2004-01-01

    The various combinations of factors influencing natural gas supply and demand and the future price of natural gas is discussed. Expert opinion is that prices will continue to track higher, demand will grow with the surging American economy, and supplies will remain constrained providing more fuel for another cycle of ever-higher prices. There is also considerable concern about the continuing rise in demand and tight supply situation in the near term, and the uncertainty about when, or even whether, major new sources will become available. The prediction is that the overriding impact of declining domestic supplies will put a premium on natural gas at any given time. Overall, it appears certain that higher prices are here to stay: as a result, industrial gas users will see their competitiveness eroded, and individual consumers will see their heating bills rise. Governments, too, will be affected as the increasing cost of natural gas will slow down the pace of conversion of coal-fired power generating plants to natural gas, reducing anticipated emissions benefits and in the process compromising environmental goals. Current best estimates put prices for the 2004/2005 heating season at about US$5.40 per MMBtu, whereas the longer term price range is estimated to lie in the range of US$4.75 to US$5.25 per MMBtu. 2 figs

  4. Atmospheric Rivers in Europe: impacts, predictability, and future climate scenarios

    Science.gov (United States)

    Ramos, A. M.; Tome, R.; Sousa, P. M.; Liberato, M. L. R.; Lavers, D.; Trigo, R. M.

    2017-12-01

    In recent years a strong relationship has been found between Atmospheric Rivers (ARs) and extreme precipitation and floods across western Europe, with some regions having 8 of their top 10 annual maxima precipitation events related to ARs. In the particular case of the Iberian Peninsula, the association between ARs and extreme precipitation days in the western river basins is noteworthy, while for the eastern and southern basins the impact of ARs is reduced. An automated ARs detection algorithm is used for the North Atlantic Ocean Basin, allowing the identification of major ARs affecting western European coasts in the present climate and under different climate change scenarios. We have used both reanalyzes and six General Circulation models under three climate scenarios (the control simulation, the RCP4.5 and RCP8.5 scenarios). The western coast of Europe was divided into five domains, namely the Iberian Peninsula, France, UK, Southern Scandinavia and the Netherlands, and Northern Scandinavia. It was found that there is an increase in the vertically integrated horizontal water transport which led to an increase in the AR frequency, a result more visible in the high emission scenarios (RCP8.5) for the 2074-2099 period. Since ARs are associated with high impact weather, it is important to study their predictability. This assessment was performed with the ECMWF ensemble forecasts up to 10 days for winters 2013/14, 2014/15 and 2015/16 for events that made landfall in the Iberian Peninsula. We show the model's potential added value to detect upcoming ARs events, which is particularly useful to predict potential hydrometeorological extremes. AcknowledgementsThis work was supported by the project FORLAND - Hydrogeomorphologic risk in Portugal: driving forces and application for land use planning [PTDC / ATPGEO / 1660/2014] funded by the Portuguese Foundation for Science and Technology (FCT), Portugal. A. M. Ramos was also supported by a FCT postdoctoral grant (FCT

  5. AP1000 will meet the challenges of near-term deployment

    International Nuclear Information System (INIS)

    Matzie, Regis A.

    2008-01-01

    The world demand for energy is growing rapidly, particularly in developing countries that are trying to raise the standard of living for billions of people, many of whom do not have access to electricity or clean water. Climate change and the concern for increased emissions of green house gases have brought into question the future primary reliance of fossil fuels. With the projected worldwide increase in energy demand, concern for the environmental impact of carbon emissions, and the recent price volatility of fossil fuels, nuclear energy is undergoing a rapid resurgence. This 'nuclear renaissance' is broad based, reaching across Asia, North America, Europe, as well as selected countries in Africa and South America. Many countries have publicly expressed their intentions to pursue the construction of new nuclear energy plants. Some countries that have previously turned away from commercial nuclear energy are reconsidering the advisability of this decision. This renaissance is facilitated by the availability of more advanced reactor designs than are operating today, with improved safety, economy, and operations. One such design, the Westinghouse AP1000 advanced passive plant, has been a long time in the making! The development of this passive technology started over two decades ago from an embryonic belief that a new approach to design was needed to spawn a nuclear renaissance. The principal challenges were seen as ensuring reactor safety by requiring less reliance on operator actions and overcoming the high plant capital cost of nuclear energy. The AP1000 design is based on the use of innovative passive technology and modular construction, which require significantly less equipment and commodities that facilitate a more rapid construction schedule. Because Westinghouse had the vision and the perseverance to continue the development of this passive technology, the AP1000 design is ready to meet today's challenge of near-term deployment

  6. Development of an integrated method for long-term water quality prediction using seasonal climate forecast

    Directory of Open Access Journals (Sweden)

    J. Cho

    2016-10-01

    Full Text Available The APEC Climate Center (APCC produces climate prediction information utilizing a multi-climate model ensemble (MME technique. In this study, four different downscaling methods, in accordance with the degree of utilizing the seasonal climate prediction information, were developed in order to improve predictability and to refine the spatial scale. These methods include: (1 the Simple Bias Correction (SBC method, which directly uses APCC's dynamic prediction data with a 3 to 6 month lead time; (2 the Moving Window Regression (MWR method, which indirectly utilizes dynamic prediction data; (3 the Climate Index Regression (CIR method, which predominantly uses observation-based climate indices; and (4 the Integrated Time Regression (ITR method, which uses predictors selected from both CIR and MWR. Then, a sampling-based temporal downscaling was conducted using the Mahalanobis distance method in order to create daily weather inputs to the Soil and Water Assessment Tool (SWAT model. Long-term predictability of water quality within the Wecheon watershed of the Nakdong River Basin was evaluated. According to the Korean Ministry of Environment's Provisions of Water Quality Prediction and Response Measures, modeling-based predictability was evaluated by using 3-month lead prediction data issued in February, May, August, and November as model input of SWAT. Finally, an integrated approach, which takes into account various climate information and downscaling methods for water quality prediction, was presented. This integrated approach can be used to prevent potential problems caused by extreme climate in advance.

  7. NASA's Earth Observing System: The Transition from Climate Monitoring to Climate Change Prediction

    Science.gov (United States)

    King, Michael D.; Herring, David D.

    1998-01-01

    Earth's 4.5 billion year history is a study in change. Natural geological forces have been rearranging the surface features and climatic conditions of our planet since its beginning. There is scientific evidence that some of these natural changes have not only led to mass extinctions of species (e.g., dinosaurs), but have also severely impacted human civilizations. For instance, there is evidence that a relatively sudden climate change caused a 300-year drought that contributed to the downfall of Akkadia, one of the most powerful empires in the Middle-East region around 2200 BC. More recently, the "little ice age" from 1200-1400 AD forced the Vikings to abandon Greenland when temperatures there dropped by about 1.5 C, rendering it too difficult to grow enough crops to sustain the population. Today, there is compelling scientific evidence that human activities have attained the magnitude of a geological force and are speeding up the rate of global change. For example, carbon dioxide levels have risen 30 percent since the industrial revolution and about 40 percent of the world's land surface has been transformed by humans. We don't understand the cause-and-effect relationships among Earth's land, ocean, and atmosphere well enough to predict what, if any, impacts these rapid changes will have on future climate conditions. We need to make many measurements all over the world, over a long period of time, in order to assemble the information needed to construct accurate computer models that will enable us to forecast climate change. In 1988, the Earth System Sciences Committee, sponsored by NASA, issued a report calling for an integrated, long-term strategy for measuring the vital signs of Earth's climate system. The report urged that the measurements must all be intimately coupled with focused process studies, they must facilitate development of Earth system models, and they must be stored in an information system that ensures open access to consistent, long-term data

  8. Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.

    Science.gov (United States)

    Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J

    2018-01-01

    Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.

  9. Predicting forest attributes from climate data using a recursive partitioning and regression tree algorithm

    Science.gov (United States)

    Greg C. Liknes; Christopher W. Woodall; Charles H. Perry

    2009-01-01

    Climate information frequently is included in geospatial modeling efforts to improve the predictive capability of other data sources. The selection of an appropriate climate data source requires consideration given the number of choices available. With regard to climate data, there are a variety of parameters (e.g., temperature, humidity, precipitation), time intervals...

  10. An empirical system for probabilistic seasonal climate prediction

    Science.gov (United States)

    Eden, Jonathan; van Oldenborgh, Geert Jan; Hawkins, Ed; Suckling, Emma

    2016-04-01

    Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

  11. A global empirical system for probabilistic seasonal climate prediction

    Science.gov (United States)

    Eden, J. M.; van Oldenborgh, G. J.; Hawkins, E.; Suckling, E. B.

    2015-12-01

    Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

  12. Predicting lodgepole pine site index from climatic parameters in Alberta.

    Science.gov (United States)

    Robert A. Monserud; Shongming Huang; Yuqing. Yang

    2006-01-01

    We sought to evaluate the impact of climatic variables on site productivity of lodgepole pine (Pinus contorta var. latifolia Engelm.) for the province of Alberta. Climatic data were obtained from the Alberta Climate Model, which is based on 30-year normals from the provincial weather station network. Mapping methods were based...

  13. Seasonal Climate Extremes : Mechanism, Predictability and Responses to Global Warming

    NARCIS (Netherlands)

    Shongwe, M.E.

    2010-01-01

    Climate extremes are rarely occurring natural phenomena in the climate system. They often pose one of the greatest environmental threats to human and natural systems. Statistical methods are commonly used to investigate characteristics of climate extremes. The fitted statistical properties are often

  14. Hydrological responses to climatic changes in the Yellow River basin, China: Climatic elasticity and streamflow prediction

    Science.gov (United States)

    Zhang, Qiang; Liu, Jianyu; Singh, Vijay P.; Shi, Peijun; Sun, Peng

    2017-11-01

    Prediction of streamflow of the Yellow River basin was done using downscaled precipitation and temperature based on outputs of 12 GCMs under RCP2.6 and RCP8.5 scenarios. Streamflow changes of 37 tributaries of the Yellow River basin during 2070-2099 were predicted related to different GCMs and climatic scenarios using Budyko framework. The results indicated that: (1) When compared to precipitation and temperature during 1960-1979, increasing precipitation and temperature are dominant during 2070-2099. Particularly, under RCP8.5, increase of 10% and 30% can be detected for precipitation and temperature respectively; (2) Precipitation changes have larger fractional contribution to streamflow changes than temperature changes, being the major driver for spatial and temporal patterns of water resources across the Yellow River basin; (3) 2070-2099 period will witness increased streamflow depth and decreased streamflow can be found mainly in the semi-humid regions and headwater regions of the Yellow River basin, which can be attributed to more significant increase of temperature than precipitation in these regions; (4) Distinctly different picture of streamflow changes can be observed with consideration of different outputs of GCMs which can be attributed to different outputs of GCMs under different scenarios. Even so, under RCP2.6 and RCP8.5 scenarios, 36.8% and 71.1% of the tributaries of the Yellow River basin are dominated by increasing streamflow. The results of this study are of theoretical and practical merits in terms of management of water resources and also irrigated agriculture under influences of changing climate.

  15. Predicting climate change impacts on native and invasive tree species using radial growth and twenty-first century climate scenarios

    NARCIS (Netherlands)

    González-Muñoz, N.; Linares, J.C.; Castro-Díez, P.; Sass-Klaassen, U.G.W.

    2014-01-01

    The climatic conditions predicted for the twenty-first century may aggravate the extent and impacts of plant invasions, by favouring those invaders more adapted to altered conditions or by hampering the native flora. We aim to predict the fate of native and invasive tree species in the oak forests

  16. Integrating environmental and genetic effects to predict responses of tree populations to climate.

    Science.gov (United States)

    Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

    2010-01-01

    Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

  17. Can decadal climate predictions be improved by ocean ensemble dispersion filtering?

    Science.gov (United States)

    Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

    2017-12-01

    Decadal predictions by Earth system models aim to capture the state and phase of the climate several years inadvance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-termweather forecasts represent an initial value problem and long-term climate projections represent a boundarycondition problem, the decadal climate prediction falls in-between these two time scales. The ocean memorydue to its heat capacity holds big potential skill on the decadal scale. In recent years, more precise initializationtechniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions.Ensembles are another important aspect. Applying slightly perturbed predictions results in an ensemble. Insteadof using and evaluating one prediction, but the whole ensemble or its ensemble average, improves a predictionsystem. However, climate models in general start losing the initialized signal and its predictive skill from oneforecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improvedby a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. Wefound that this procedure, called ensemble dispersion filter, results in more accurate results than the standarddecadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions showan increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with largerensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from oceanensemble dispersion filtering toward the ensemble mean. This study is part of MiKlip (fona-miklip.de) - a major project on decadal climate prediction in Germany.We focus on the Max-Planck-Institute Earth System Model using the low-resolution version (MPI-ESM-LR) andMiKlip's basic initialization strategy as in 2017 published decadal climate forecast: http

  18. Risk minimization for near-term deployment of the next generation nuclear plant

    International Nuclear Information System (INIS)

    Lommers, L.; Southworth, F.; Riou, B.; Lecomte, M.

    2008-01-01

    The NGNP program is developing the High Temperature Reactor for high efficiency electricity production and high temperature process heat such as direct hydrogen production. AREVA leads one of three vendor teams supporting the NGNP program. AREVA has developed an NGNP concept based on AREVA's ANTARES indirect cycle HTR concept. The ANTARES-based NGNP concept attempts to manage development risk by using a conservative design philosophy which balances performance and risk. Additional risk mitigation for rapid near-term deployment is also considered. Near-term markets may not require the full capability of the indirect cycle very high temperature concept. A steam cycle concept might better serve near-term markets for high temperature steam with reduced technical and schedule risk. (authors)

  19. Woody plants and the prediction of climate-change impacts on bird diversity

    DEFF Research Database (Denmark)

    Kissling, W. Daniel; Field, R.; Korntheuer, H.

    2010-01-01

    Current methods of assessing climate-induced shifts of species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. Here, we used species-richness data from 1005 breeding bird and 1417 woody plant...... species in Kenya and employed model-averaged coefficients from regression models and median climatic forecasts assembled across 15 climate-change scenarios to predict bird species richness under climate change. Forecasts assuming an instantaneous response of woody plants and birds to climate change...... suggested increases in future bird species richness across most of Kenya whereas forecasts assuming strongly lagged woody plant responses to climate change indicated a reversed trend, i.e. reduced bird species richness. Uncertainties in predictions of future bird species richness were geographically...

  20. Climate fails to predict wood decomposition at regional scales

    Science.gov (United States)

    Mark A. Bradford; Robert J. Warren; Petr Baldrian; Thomas W. Crowther; Daniel S. Maynard; Emily E. Oldfield; William R. Wieder; Stephen A. Wood; Joshua R. King

    2014-01-01

    Decomposition of organic matter strongly influences ecosystem carbon storage1. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter2, 3, 4, 5. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on...

  1. Taxonomies of Higher Educational Institutions Predicted from Organizational Climate.

    Science.gov (United States)

    Lysons, Art

    1990-01-01

    Application of the Perceived Climate Questionnaire involving senior-level staff from Australian institutions used climate factors as the basis for testing hypothesized taxonomies of the institutions. Results reinforce the relevance of contemporary management theories and demonstrate the importance of leadership styles in organizational…

  2. Predicting the Response of Electricity Load to Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Sullivan, Patrick [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Colman, Jesse [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kalendra, Eric [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2015-07-28

    Our purpose is to develop a methodology to quantify the impact of climate change on electric loads in the United States. We perform simple linear regression, assisted by geospatial smoothing, on paired temperature and load time-series to estimate the heating- and coolinginduced sensitivity to temperature across 300 transmission zones and 16 seasonal and diurnal time periods. The estimated load sensitivities can be coupled with climate scenarios to quantify the potential impact of climate change on load, with a primary application being long-term electricity scenarios. The method allows regional and seasonal differences in climate and load response to be reflected in the electricity scenarios. While the immediate product of this analysis was designed to mesh with the spatial and temporal resolution of a specific electricity model to enable climate change scenarios and analysis with that model, we also propose that the process could be applied for other models and purposes.

  3. Photovoltaic (PV) Pricing Trends: Historical, Recent, and Near-Term Projections

    Energy Technology Data Exchange (ETDEWEB)

    Feldman, D.; Barbose, G.; Margolis, R.; Wiser, R.; Darghouth, N.; Goodrich, A.

    2012-11-01

    This report helps to clarify the confusion surrounding different estimates of system pricing by distinguishing between past, current, and near-term projected estimates. It also discusses the different methodologies and factors that impact the estimated price of a PV system, such as system size, location, technology, and reporting methods.These factors, including timing, can have a significant impact on system pricing.

  4. Acute maternal rehydration increases the urine production rate in the near-term human fetus

    NARCIS (Netherlands)

    Haak, MC; Aarnoudse, JG; Oosterhof, H.

    OBJECTIVE: We sought to investigate the effect of a decrease of maternal plasma osmolality produced by hypotonic rehydration on the fetal urine production rate in normal near-term human fetuses. STUDY DESIGN: Twenty-one healthy pregnant women attending the clinic for antenatal care were studied

  5. The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model

    Science.gov (United States)

    Baehr, J.; Fröhlich, K.; Botzet, M.; Domeisen, D. I. V.; Kornblueh, L.; Notz, D.; Piontek, R.; Pohlmann, H.; Tietsche, S.; Müller, W. A.

    2015-05-01

    A seasonal forecast system is presented, based on the global coupled climate model MPI-ESM as used for CMIP5 simulations. We describe the initialisation of the system and analyse its predictive skill for surface temperature. The presented system is initialised in the atmospheric, oceanic, and sea ice component of the model from reanalysis/observations with full field nudging in all three components. For the initialisation of the ensemble, bred vectors with a vertically varying norm are implemented in the ocean component to generate initial perturbations. In a set of ensemble hindcast simulations, starting each May and November between 1982 and 2010, we analyse the predictive skill. Bias-corrected ensemble forecasts for each start date reproduce the observed surface temperature anomalies at 2-4 months lead time, particularly in the tropics. Niño3.4 sea surface temperature anomalies show a small root-mean-square error and predictive skill up to 6 months. Away from the tropics, predictive skill is mostly limited to the ocean, and to regions which are strongly influenced by ENSO teleconnections. In summary, the presented seasonal prediction system based on a coupled climate model shows predictive skill for surface temperature at seasonal time scales comparable to other seasonal prediction systems using different underlying models and initialisation strategies. As the same model underlying our seasonal prediction system—with a different initialisation—is presently also used for decadal predictions, this is an important step towards seamless seasonal-to-decadal climate predictions.

  6. Monitoring Top-of-Atmosphere Radiative Energy Imbalance for Climate Prediction

    Science.gov (United States)

    Lin, Bing; Chambers, Lin H.; Stackhouse, Paul W., Jr.; Minnis, Patrick

    2009-01-01

    Large climate feedback uncertainties limit the prediction accuracy of the Earth s future climate with an increased CO2 atmosphere. One potential to reduce the feedback uncertainties using satellite observations of top-of-atmosphere (TOA) radiative energy imbalance is explored. Instead of solving the initial condition problem in previous energy balance analysis, current study focuses on the boundary condition problem with further considerations on climate system memory and deep ocean heat transport, which is more applicable for the climate. Along with surface temperature measurements of the present climate, the climate feedbacks are obtained based on the constraints of the TOA radiation imbalance. Comparing to the feedback factor of 3.3 W/sq m/K of the neutral climate system, the estimated feedback factor for the current climate system ranges from -1.3 to -1.0 W/sq m/K with an uncertainty of +/-0.26 W/sq m/K. That is, a positive climate feedback is found because of the measured TOA net radiative heating (0.85 W/sq m) to the climate system. The uncertainty is caused by the uncertainties in the climate memory length. The estimated time constant of the climate is large (70 to approx. 120 years), implying that the climate is not in an equilibrium state under the increasing CO2 forcing in the last century.

  7. Using decadal climate prediction to characterize and manage changing drought and flood risks in Colorado

    Science.gov (United States)

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

    2017-12-01

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

  8. Assessing the implementation of bias correction in the climate prediction

    Science.gov (United States)

    Nadrah Aqilah Tukimat, Nurul

    2018-04-01

    An issue of the climate changes nowadays becomes trigger and irregular. The increment of the greenhouse gases (GHGs) emission into the atmospheric system day by day gives huge impact to the fluctuated weather and global warming. It becomes significant to analyse the changes of climate parameters in the long term. However, the accuracy in the climate simulation is always be questioned to control the reliability of the projection results. Thus, the Linear Scaling (LS) as a bias correction method (BC) had been applied to treat the gaps between observed and simulated results. About two rainfall stations were selected in Pahang state there are Station Lubuk Paku and Station Temerloh. Statistical Downscaling Model (SDSM) used to perform the relationship between local weather and atmospheric parameters in projecting the long term rainfall trend. The result revealed the LS was successfully to reduce the error up to 3% and produced better climate simulated results.

  9. Improving the reliability of fishery predictions under climate change

    DEFF Research Database (Denmark)

    Brander, Keith

    2015-01-01

    The increasing number of publications assessing impacts of climate change on marine ecosystems and fisheries attests to rising scientific and public interest. A selection of recent papers, dealing more with biological than social and economic aspects, is reviewed here, with particular attention...... to the reliability of projections of climate impacts on future fishery yields. The 2014 Intergovernmental Panel on Climate Change (IPCC) report expresses high confidence in projections that mid- and high-latitude fish catch potential will increase by 2050 and medium confidence that low-latitude catch potential...... understanding of climate impacts, such as how to improve coupled models from physics to fish and how to strengthen confidence in analysis of time series...

  10. Climate fails to predict wood decomposition at regional scales

    Czech Academy of Sciences Publication Activity Database

    Bradford, M.A.; Warren, R.J.; Baldrian, Petr; Crowther, T. W.; Maynard, D.S.; Oldfield, E.E.; Wieder, W.R.; Wood, S.A.; King, J.R.

    2014-01-01

    Roč. 4, č. 7 (2014), s. 625-630 ISSN 1758-678X Institutional support: RVO:61388971 Keywords : ecosystem * climate changes * wood decomposition * forest Subject RIV: EE - Microbiology, Virology Impact factor: 14.547, year: 2014

  11. model prediction of maize yield responses to climate change

    African Journals Online (AJOL)

    Prof. Adipala Ekwamu

    identified in the Intergovernmental Panel on Climate Change Third Assessment Report (IPCC-TAR) as a major .... carbon dioxide concentration and management ... address conditions where water is a key limiting ... Laboratory, United States.

  12. Regional decadal predictions of coupled climate-human systems

    Science.gov (United States)

    Curchitser, E. N.; Lawrence, P.; Felder, F.; Large, W.; Bacmeister, J. T.; Andrews, C.; Kopp, R. E.

    2016-12-01

    We present results from a project to develop a framework for investigating the interactions between human activity and the climate system using state-of-the-art multi-scale, climate and economic models. The model is applied to the highly industrialized and urbanized coastal region of the northeast US with an emphasis on New Jersey. The framework is developed around the NCAR Community Earth System Model (CESM). The CESM model capabilities are augmented with enhanced resolution of the atmosphere (25 km), land surface (I km) and ocean models (7 km) in our region of interest. To the climate model, we couple human activity models for the utility sector and a 300-equation econometric model with sectorial details of an input-output model for the New Jersey economy. We will present results to date showing the potential impact of climate change on electricity markets on its consequences on economic activity in the region.

  13. Predicting Future Seed Sourcing of Platycladus orientalis (L. for Future Climates Using Climate Niche Models

    Directory of Open Access Journals (Sweden)

    Xian-Ge Hu

    2017-12-01

    Full Text Available Climate niche modeling has been widely used to assess the impact of climate change on forest trees at the species level. However, geographically divergent tree populations are expected to respond differently to climate change. Considering intraspecific local adaptation in modeling species responses to climate change will thus improve the credibility and usefulness of climate niche models, particularly for genetic resources management. In this study, we used five Platycladus orientalis (L. seed zones (Northwestern; Northern; Central; Southern; and Subtropical covering the entire species range in China. A climate niche model was developed and used to project the suitable climatic conditions for each of the five seed zones for current and various future climate scenarios (Representative Concentration Pathways: RCP2.6, RCP4.5, RCP6.0, and RCP8.5. Our results indicated that the Subtropical seed zone would show consistent reduction for all climate change scenarios. The remaining seed zones, however, would experience various degrees of expansion in suitable habitat relative to their current geographic distributions. Most of the seed zones would gain suitable habitats at their northern distribution margins and higher latitudes. Thus, we recommend adjusting the current forest management strategies to mitigate the negative impacts of climate change.

  14. Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Jaroslav Solc

    2009-06-01

    The Energy & Environmental Research Center (EERC) completed a brief evaluation of the existing status of predictive modeling to assess options for integration of our previous paleohydrologic reconstructions and their synthesis with current global climate scenarios. Results of our research indicate that short-term data series available from modern instrumental records are not sufficient to reconstruct past hydrologic events or predict future ones. On the contrary, reconstruction of paleoclimate phenomena provided credible information on past climate cycles and confirmed their integration in the context of regional climate history is possible. Similarly to ice cores and other paleo proxies, acquired data represent an objective, credible tool for model calibration and validation of currently observed trends. It remains a subject of future research whether further refinement of our results and synthesis with regional and global climate observations could contribute to improvement and credibility of climate predictions on a regional and global scale.

  15. Predicting the effects of climate change on marine communities and the consequences for fisheries

    DEFF Research Database (Denmark)

    Jennings, Simon; Brander, Keith

    2010-01-01

    for the community under the same climate scenario. The main weakness of the community approach is that the methods predict abundance and production by size-class rather than taxonomic group, and society would be particularly concerned if climate driven changes had a strong effect on the relative production...... of fishable and non-fishable species in the community. The main strength of the community approach is that it provides widely applicable ‘null’ models for assessing the biological effects of climate change and a baseline for model comparisons.......Climate effects on the structure and function of marine communities have received scant attention. The few existing approaches for predicting climate effects suggest that community responses might be predicted from the responses of component populations. These approaches require a very complex...

  16. The predictive skill of species distribution models for plankton in a changing climate

    DEFF Research Database (Denmark)

    Brun, Philipp Georg; Kiørboe, Thomas; Licandro, Priscilla

    2016-01-01

    Statistical species distribution models (SDMs) are increasingly used to project spatial relocations of marine taxa under future climate change scenarios. However, tests of their predictive skill in the real-world are rare. Here, we use data from the Continuous Plankton Recorder program, one...... null models, is essential to assess the robustness of projections of marine planktonic species under climate change...

  17. Dynamic-landscape metapopulation models predict complex response of wildlife populations to climate and landscape change

    Science.gov (United States)

    Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh

    2017-01-01

    The increasing need to predict how climate change will impact wildlife species has exposed limitations in how well current approaches model important biological processes at scales at which those processes interact with climate. We used a comprehensive approach that combined recent advances in landscape and population modeling into dynamic-landscape metapopulation...

  18. Climate Prediction Center(CPC)Infra-Red (IR) 0.5 degree Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Climate Prediction Center 0.5 degree IR dataset was created from all available individual geostationary satellite data which have been merged to form nearly seamless...

  19. Climate Prediction Center (CPC) One Month Probabilistic Precipitation Outlook for the Contiguous United States and Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) issues a probabilistic one-month precipitation outlook for the United States twice a month. CPC issues an initial monthly outlook...

  20. Climate Prediction Center (CPC)Monthly Precipitation Reconstruction (PREC) Spatial Resolution of 2.5 degree

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This global monthly precipitation analysis is called the Climate Prediction Center (CPC) Precipitation Reconstruction (PREC). This analysis consists of two...

  1. Climate Prediction Center (CPC)Monthly Precipitation Reconstruction (PREC) at Spatial Resolution of 1 degree.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This global monthly precipitation analysis is called the Climate Prediction Center (CPC) Precipitation Reconstruction (PREC). This analysis consists of two...

  2. Climate Prediction Center (CPC) NCEP-Global Forecast System (GFS) Precipitation Forecast Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Forecast System (GFS) forecast precipitation data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near real-time...

  3. Climate Prediction Center (CPC) Three Month Probabilistic Precipitation Outlook for the Contiguous United States and Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) issues a series of thirteen probabilistic three-month precipitation outlooks for the United States. CPC issues the thirteen...

  4. NOAA Climate Prediction Center (CPC) El Nino-Southern Oscillation (ENSO) Diagnostics Discussion

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The ENSO Diagnostics Discussion (EDD) is issued by NOAA Climate Prediction Center each month on the Thursday between the 5th and 11th with few exceptions (major...

  5. Climate Prediction Center (CPC) Three Month Probabilistic Temperature Outlook for the Contiguous United States and Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) issues a series of thirteen probabilistic three-month temperature outlooks for the United States. CPC issues the thirteen...

  6. Climate Prediction Center (CPC) One Month Probabilistic Temperature Outlook for the Contiguous United States and Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) issues a probabilistic one-month temperature outlook for the United States twice a month. CPC issues an initial monthly outlook...

  7. Near-Term Electric Vehicle Program. Phase II: Mid-Term Summary Report.

    Energy Technology Data Exchange (ETDEWEB)

    None

    1978-08-01

    The Near Term Electric Vehicle (NTEV) Program is a constituent elements of the overall national Electric and Hybrid Vehicle Program that is being implemented by the Department of Energy in accordance with the requirements of the Electric and Hybrid Vehicle Research, Development, and Demonstration Act of 1976. Phase II of the NTEV Program is focused on the detailed design and development, of complete electric integrated test vehicles that incorporate current and near-term technology, and meet specified DOE objectives. The activities described in this Mid-Term Summary Report are being carried out by two contractor teams. The prime contractors for these contractor teams are the General Electric Company and the Garrett Corporation. This report is divided into two discrete parts. Part 1 describes the progress of the General Electric team and Part 2 describes the progress of the Garrett team.

  8. Near-Term Nuclear Power Revival? A U.S. and International Perspective

    International Nuclear Information System (INIS)

    Braun, C.

    2004-01-01

    In this paper I review the causes for the renewed interest in the near-term revival of nuclear power in the U.S. and internationally. I comment on the progress already made in the U.S. in restarting a second era of commercial nuclear power plant construction, and on what is required going forwards, from a utilities perspective, to commit to and implement new plant orders. I review the specific nuclear projects discussed and committed to in the U.S. and abroad in terms of utilities, sites, vendor and suppliers teams, and project arrangements. I will then offer some tentative conclusions regarding the prospects for a near-term U.S. and global nuclear power revival

  9. The Near-Term Impacts of Carbon Mitigation Policies on Manufacturing Industries

    OpenAIRE

    Morgenstern, Richard; Shih, Jhih-Shyang; Ho, Mun; Zhang, Xuehua

    2002-01-01

    Who will pay for new policies to reduce carbon dioxide and other greenhouse gas emissions in the United States? This paper considers a slice of the question by examining the near-term impact on domestic manufacturing industries of both upstream (economy-wide) and downstream (electric power industry only) carbon mitigation policies. Detailed Census data on the electricity use of four-digit manufacturing industries is combined with input-output information on interindustry purchases to paint a ...

  10. Mobile robotics for CANDU reactor maintenance: case studies and near-term improvements

    International Nuclear Information System (INIS)

    Lipsett, M. G.; Rody, K.H.

    1995-01-01

    Although robotics researchers have been promising that robotics would soon be performing tasks in hazardous environments, the reality has yet to live up to the hype. The presently available crop of robots suitable for deployment in industrial situations are remotely operated, requiring skilled users. This talk describes cases where mobile robots have been used successfully in CANDU stations, discusses the difficulties in using mobile robots for reactor maintenance, and provides near-term goals for achievable improvements in performance and usefulness. (author)

  11. Photovoltaic System Pricing Trends. Historical, Recent, and Near-Term Projections, 2015 Edition

    Energy Technology Data Exchange (ETDEWEB)

    Feldman, David [National Renewable Energy Lab. (NREL), Golden, CO (United States); Barbose, Galen [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Margolis, Robert [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bolinger, Mark [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chung, Donald [National Renewable Energy Lab. (NREL), Golden, CO (United States); Fu, Ran [National Renewable Energy Lab. (NREL), Golden, CO (United States); Seel, Joachim [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Davidson, Carolyn [National Renewable Energy Lab. (NREL), Golden, CO (United States); Darghouth, Naïm [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wiser, Ryan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-08-25

    This presentation, based on research at Lawrence Berkeley National Laboratory and the National Renewable Energy Laboratory, provides a high-level overview of historical, recent, and projected near-term PV pricing trends in the United States focusing on the installed price of PV systems. It also attempts to provide clarity surrounding the wide variety of potentially conflicting data available about PV system prices. This PowerPoint is the fourth edition from this series.

  12. The role of reduced aerosol precursor emissions in driving near-term warming

    International Nuclear Information System (INIS)

    Gillett, Nathan P; Von Salzen, Knut

    2013-01-01

    The representative concentration pathway (RCP) scenarios all assume stringent emissions controls on aerosols and their precursors, and hence include progressive decreases in aerosol and aerosol precursor emissions through the 21st century. Recent studies have suggested that the resultant decrease in aerosols could drive rapid near-term warming, which could dominate the effects of greenhouse gas (GHG) increases in the coming decades. In CanESM2 simulations, we find that under the RCP 2.6 scenario, which includes the fastest decrease in aerosol and aerosol precursor emissions, the contribution of aerosol reductions to warming between 2000 and 2040 is around 30%. Moreover, the rate of warming in the RCP 2.6 simulations declines gradually from its present-day value as GHG emissions decrease. Thus, while aerosol emission reductions contribute to gradual warming through the 21st century, we find no evidence that aerosol emission reductions drive particularly rapid near-term warming in this scenario. In the near-term, as in the long-term, GHG increases are the dominant driver of warming. (letter)

  13. Predicting Douglas-fir's response to a warming climate

    Science.gov (United States)

    Andrea Watts; Sheel Bansal; Connie Harrington; Brad. St. Clair

    2015-01-01

    Douglas-fir is an iconic tree in the Pacific Northwest. Although individual trees may appear to be identical, genetic differences within each tree have resulted from adaptation to the local environment. These genetic differences over time have resulted in differences among populations that are important to the species' survival and growth in changing climates....

  14. The CCPP-ARM Parameterization Testbed (CAPT): Where Climate Simulation Meets Weather Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, T J; Potter, G L; Williamson, D L; Cederwall, R T; Boyle, J S; Fiorino, M; Hnilo, J J; Olson, J G; Xie, S; Yio, J J

    2003-11-21

    To significantly improve the simulation of climate by general circulation models (GCMs), systematic errors in representations of relevant processes must first be identified, and then reduced. This endeavor demands, in particular, that the GCM parameterizations of unresolved processes should be tested over a wide range of time scales, not just in climate simulations. Thus, a numerical weather prediction (NWP) methodology for evaluating model parameterizations and gaining insights into their behavior may prove useful, provied that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by realistically initialized climate GCM, and the application of six-hourly NWP analyses and observations of parameterized variables to evaluate these forecasts. The behavior of the parameterizations in such a weather-forecasting framework can provide insights on how these schemes might be improved, and modified parameterizations then can be similarly tested. In order to further this method for evaluating and analyzing parameterizations in climate GCMs, the USDOE is funding a joint venture of its Climate Change Prediction Program (CCPP) and Atmospheric Radiation Measurement (ARM) Program: the CCPP-ARM Parameterization Testbed (CAPT). This article elaborates the scientific rationale for CAPT, discusses technical aspects of its methodology, and presents examples of its implementation in a representative climate GCM. Numerical weather prediction methods show promise for improving parameterizations in climate GCMs.

  15. Predicting Pleistocene climate from vegetation in North America

    Directory of Open Access Journals (Sweden)

    C. Loehle

    2007-01-01

    Full Text Available Climates at the Last Glacial Maximum have been inferred from fossil pollen assemblages, but these inferred climates are colder for eastern North America than those produced by climate simulations. It has been suggested that low CO2 levels could account for this discrepancy. In this study biogeographic evidence is used to test the CO2 effect model. The recolonization of glaciated zones in eastern North America following the last ice age produced distinct biogeographic patterns. It has been assumed that a wide zone south of the ice was tundra or boreal parkland (Boreal-Parkland Zone or BPZ, which would have been recolonized from southern refugia as the ice melted, but the patterns in this zone differ from those in the glaciated zone, which creates a major biogeographic anomaly. In the glacial zone, there are few endemics but in the BPZ there are many across multiple taxa. In the glacial zone, there are the expected gradients of genetic diversity with distance from the ice-free zone, but no evidence of this is found in the BPZ. Many races and related species exist in the BPZ which would have merged or hybridized if confined to the same refugia. Evidence for distinct southern refugia for most temperate species is lacking. Extinctions of temperate flora were rare. The interpretation of spruce as a boreal climate indicator may be mistaken over much of the region if the spruce was actually an extinct temperate species. All of these anomalies call into question the concept that climates in the zone south of the ice were extremely cold or that temperate species had to migrate far to the south. An alternate hypothesis is that low CO2 levels gave an advantage to pine and spruce, which are the dominant trees in the BPZ, and to herbaceous species over trees, which also fits the observed pattern. Thus climate reconstruction from pollen data is probably biased and needs to incorporate CO2 effects. Most temperate species could have survived across their current

  16. Potential Distribution Predicted for Rhynchophorus ferrugineus in China under Different Climate Warming Scenarios.

    Directory of Open Access Journals (Sweden)

    Xuezhen Ge

    Full Text Available As the primary pest of palm trees, Rhynchophorus ferrugineus (Olivier (Coleoptera: Curculionidae has caused serious harm to palms since it first invaded China. The present study used CLIMEX 1.1 to predict the potential distribution of R. ferrugineus in China according to both current climate data (1981-2010 and future climate warming estimates based on simulated climate data for the 2020s (2011-2040 provided by the Tyndall Center for Climate Change Research (TYN SC 2.0. Additionally, the Ecoclimatic Index (EI values calculated for different climatic conditions (current and future, as simulated by the B2 scenario were compared. Areas with a suitable climate for R. ferrugineus distribution were located primarily in central China according to the current climate data, with the northern boundary of the distribution reaching to 40.1°N and including Tibet, north Sichuan, central Shaanxi, south Shanxi, and east Hebei. There was little difference in the potential distribution predicted by the four emission scenarios according to future climate warming estimates. The primary prediction under future climate warming models was that, compared with the current climate model, the number of highly favorable habitats would increase significantly and expand into northern China, whereas the number of both favorable and marginally favorable habitats would decrease. Contrast analysis of EI values suggested that climate change and the density of site distribution were the main effectors of the changes in EI values. These results will help to improve control measures, prevent the spread of this pest, and revise the targeted quarantine areas.

  17. Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models

    Science.gov (United States)

    Ramírez-Albores, Jorge E.; Bustamante, Ramiro O.

    2016-01-01

    Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile) nor the origin of individuals (naturally established or man-planted), the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle), a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model). The second model only included occurrence records of naturally established mature individuals (adult niche model), while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model). When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with data of

  18. The predictive state: Science, territory and the future of the Indian climate.

    Science.gov (United States)

    Mahony, Martin

    2014-02-01

    Acts of scientific calculation have long been considered central to the formation of the modern nation state, yet the transnational spaces of knowledge generation and political action associated with climate change seem to challenge territorial modes of political order. This article explores the changing geographies of climate prediction through a study of the ways in which climate change is rendered knowable at the national scale in India. The recent controversy surrounding an erroneous prediction of melting Himalayan glaciers by the Intergovernmental Panel on Climate Change provides a window onto the complex and, at times, antagonistic relationship between the Panel and Indian political and scientific communities. The Indian reaction to the error, made public in 2009, drew upon a national history of contestation around climate change science and corresponded with the establishment of a scientific assessment network, the Indian Network for Climate Change Assessment, which has given the state a new platform on which to bring together knowledge about the future climate. I argue that the Indian Network for Climate Change Assessment is indicative of the growing use of regional climate models within longer traditions of national territorial knowledge-making, allowing a rescaling of climate change according to local norms and practices of linking scientific knowledge to political action. I illustrate the complex co-production of the epistemic and the normative in climate politics, but also seek to show how co-productionist understandings of science and politics can function as strategic resources in the ongoing negotiation of social order. In this case, scientific rationalities and modes of environmental governance contribute to the contested epistemic construction of territory and the evolving spatiality of the modern nation state under a changing climate.

  19. Approaches to predicting potential impacts of climate change on forest disease: An example with Armillaria root disease

    Science.gov (United States)

    Ned B. Klopfenstein; Mee-Sook Kim; John W. Hanna; Bryce A. Richardson; John E. Lundquist

    2011-01-01

    Climate change will likely have dramatic impacts on forest health because many forest trees could become maladapted to climate. Furthermore, climate change will have additional impacts on forest health through changes in the distribution and severity of forest disease. Methods are needed to predict the influence of climate change on forest disease so that appropriate...

  20. Predicting climate-induced range shifts: model differences and model reliability.

    Science.gov (United States)

    Joshua J. Lawler; Denis White; Ronald P. Neilson; Andrew R. Blaustein

    2006-01-01

    Predicted changes in the global climate are likely to cause large shifts in the geographic ranges of many plant and animal species. To date, predictions of future range shifts have relied on a variety of modeling approaches with different levels of model accuracy. Using a common data set, we investigated the potential implications of alternative modeling approaches for...

  1. Joint Applications Pilot of the National Climate Predictions and Projections Platform and the North Central Climate Science Center: Delivering climate projections on regional scales to support adaptation planning

    Science.gov (United States)

    Ray, A. J.; Ojima, D. S.; Morisette, J. T.

    2012-12-01

    The DOI North Central Climate Science Center (NC CSC) and the NOAA/NCAR National Climate Predictions and Projections (NCPP) Platform and have initiated a joint pilot study to collaboratively explore the "best available climate information" to support key land management questions and how to provide this information. NCPP's mission is to support state of the art approaches to develop and deliver comprehensive regional climate information and facilitate its use in decision making and adaptation planning. This presentation will describe the evolving joint pilot as a tangible, real-world demonstration of linkages between climate science, ecosystem science and resource management. Our joint pilot is developing a deliberate, ongoing interaction to prototype how NCPP will work with CSCs to develop and deliver needed climate information products, including translational information to support climate data understanding and use. This pilot also will build capacity in the North Central CSC by working with NCPP to use climate information used as input to ecological modeling. We will discuss lessons to date on developing and delivering needed climate information products based on this strategic partnership. Four projects have been funded to collaborate to incorporate climate information as part of an ecological modeling project, which in turn will address key DOI stakeholder priorities in the region: Riparian Corridors: Projecting climate change effects on cottonwood and willow seed dispersal phenology, flood timing, and seedling recruitment in western riparian forests. Sage Grouse & Habitats: Integrating climate and biological data into land management decision models to assess species and habitat vulnerability Grasslands & Forests: Projecting future effects of land management, natural disturbance, and CO2 on woody encroachment in the Northern Great Plains The value of climate information: Supporting management decisions in the Plains and Prairie Potholes LCC. NCCSC's role in

  2. An effective drift correction for dynamical downscaling of decadal global climate predictions

    Science.gov (United States)

    Paeth, Heiko; Li, Jingmin; Pollinger, Felix; Müller, Wolfgang A.; Pohlmann, Holger; Feldmann, Hendrik; Panitz, Hans-Jürgen

    2018-04-01

    Initialized decadal climate predictions with coupled climate models are often marked by substantial climate drifts that emanate from a mismatch between the climatology of the coupled model system and the data set used for initialization. While such drifts may be easily removed from the prediction system when analyzing individual variables, a major problem prevails for multivariate issues and, especially, when the output of the global prediction system shall be used for dynamical downscaling. In this study, we present a statistical approach to remove climate drifts in a multivariate context and demonstrate the effect of this drift correction on regional climate model simulations over the Euro-Atlantic sector. The statistical approach is based on an empirical orthogonal function (EOF) analysis adapted to a very large data matrix. The climate drift emerges as a dramatic cooling trend in North Atlantic sea surface temperatures (SSTs) and is captured by the leading EOF of the multivariate output from the global prediction system, accounting for 7.7% of total variability. The SST cooling pattern also imposes drifts in various atmospheric variables and levels. The removal of the first EOF effectuates the drift correction while retaining other components of intra-annual, inter-annual and decadal variability. In the regional climate model, the multivariate drift correction of the input data removes the cooling trends in most western European land regions and systematically reduces the discrepancy between the output of the regional climate model and observational data. In contrast, removing the drift only in the SST field from the global model has hardly any positive effect on the regional climate model.

  3. Visualization of uncertainties and forecast skill in user-tailored seasonal climate predictions for agriculture

    Science.gov (United States)

    Sedlmeier, Katrin; Gubler, Stefanie; Spierig, Christoph; Flubacher, Moritz; Maurer, Felix; Quevedo, Karim; Escajadillo, Yury; Avalos, Griña; Liniger, Mark A.; Schwierz, Cornelia

    2017-04-01

    Seasonal climate forecast products potentially have a high value for users of different sectors. During the first phase (2012-2015) of the project CLIMANDES (a pilot project of the Global Framework for Climate Services led by WMO [http://www.wmo.int/gfcs/climandes]), a demand study conducted with Peruvian farmers indicated a large interest in seasonal climate information for agriculture. The study further showed that the required information should by precise, timely, and understandable. In addition to the actual forecast, two complex measures are essential to understand seasonal climate predictions and their limitations correctly: forecast uncertainty and forecast skill. The former can be sampled by using an ensemble of climate simulations, the latter derived by comparing forecasts of past time periods to observations. Including uncertainty and skill information in an understandable way for end-users (who are often not technically educated) poses a great challenge. However, neglecting this information would lead to a false sense of determinism which could prove fatal to the credibility of climate information. Within the second phase (2016-2018) of the project CLIMANDES, one goal is to develop a prototype of a user-tailored seasonal forecast for the agricultural sector in Peru. In this local context, the basic education level of the rural farming community presents a major challenge for the communication of seasonal climate predictions. This contribution proposes different graphical presentations of climate forecasts along with possible approaches to visualize and communicate the associated skill and uncertainties, considering end users with varying levels of technical knowledge.

  4. Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.

    Science.gov (United States)

    Ceglar, Andrej; Toreti, Andrea; Prodhomme, Chloe; Zampieri, Matteo; Turco, Marco; Doblas-Reyes, Francisco J

    2018-01-22

    Seasonal crop yield forecasting represents an important source of information to maintain market stability, minimise socio-economic impacts of crop losses and guarantee humanitarian food assistance, while it fosters the use of climate information favouring adaptation strategies. As climate variability and extremes have significant influence on agricultural production, the early prediction of severe weather events and unfavourable conditions can contribute to the mitigation of adverse effects. Seasonal climate forecasts provide additional value for agricultural applications in several regions of the world. However, they currently play a very limited role in supporting agricultural decisions in Europe, mainly due to the poor skill of relevant surface variables. Here we show how a combined stress index (CSI), considering both drought and heat stress in summer, can predict maize yield in Europe and how land-surface initialised seasonal climate forecasts can be used to predict it. The CSI explains on average nearly 53% of the inter-annual maize yield variability under observed climate conditions and shows how concurrent heat stress and drought events have influenced recent yield anomalies. Seasonal climate forecast initialised with realistic land-surface achieves better (and marginally useful) skill in predicting the CSI than with climatological land-surface initialisation in south-eastern Europe, part of central Europe, France and Italy.

  5. COLLABORATIVE RESEARCH: TOWARDS ADVANCED UNDERSTANDING AND PREDICTIVE CAPABILITY OF CLIMATE CHANGE IN THE ARCTIC USING A HIGH-RESOLUTION REGIONAL ARCTIC CLIMATE SYSTEM MODEL

    Energy Technology Data Exchange (ETDEWEB)

    Gutowski, William J.

    2013-02-07

    The motivation for this project was to advance the science of climate change and prediction in the Arctic region. Its primary goals were to (i) develop a state-of-the-art Regional Arctic Climate system Model (RACM) including high-resolution atmosphere, land, ocean, sea ice and land hydrology components and (ii) to perform extended numerical experiments using high performance computers to minimize uncertainties and fundamentally improve current predictions of climate change in the northern polar regions. These goals were realized first through evaluation studies of climate system components via one-way coupling experiments. Simulations were then used to examine the effects of advancements in climate component systems on their representation of main physics, time-mean fields and to understand variability signals at scales over many years. As such this research directly addressed some of the major science objectives of the BER Climate Change Research Division (CCRD) regarding the advancement of long-term climate prediction.

  6. Trade-off results and preliminary designs of Near-Term Hybrid Vehicles

    Science.gov (United States)

    Sandberg, J. J.

    1980-01-01

    Phase I of the Near-Term Hybrid Vehicle Program involved the development of preliminary designs of electric/heat engine hybrid passenger vehicles. The preliminary designs were developed on the basis of mission analysis, performance specification, and design trade-off studies conducted independently by four contractors. THe resulting designs involve parallel hybrid (heat engine/electric) propulsion systems with significant variation in component selection, power train layout, and control strategy. Each of the four designs is projected by its developer as having the potential to substitute electrical energy for 40% to 70% of the petroleum fuel consumed annually by its conventional counterpart.

  7. Hardware based technology assessment in support of near-term space fission missions

    International Nuclear Information System (INIS)

    Houts, Mike; Van Dyke, Melissa; Godfroy, Tom; Martin, James; Bragg-Sitton, Shannon; Dickens, Ricky; Salvail, Pat; Williams, Eric; Harper, Roger; Hrbud, Ivana; Carter, Robert

    2003-01-01

    Fission technology can enable rapid, affordable access to any point in the solar system. If fission propulsion systems are to be developed to their full potential; however, near-term customers must be identified and initial fission systems successfully developed, launched, and utilized. Successful utilization will most likely occur if frequent, significant hardware-based milestones can be achieved throughout the program. Achieving these milestones will depend on the capability to perform highly realistic non-nuclear testing of nuclear systems. This paper discusses ongoing and potential research that could help achieve these milestones

  8. Hardware Based Technology Assessment in Support of Near-Term Space Fission Missions

    Science.gov (United States)

    Houts, Mike; VanDyke, Melissa; Godfroy, Tom; Martin, James; BraggSitton, Shannon; Carter, Robert; Dickens, Ricky; Salvail, Pat; Williams, Eric; Harper, Roger

    2003-01-01

    Fission technology can enable rapid, affordable access to any point in the solar system. If fission propulsion systems are to be developed to their full potential; however, near-term customers must be identified and initial fission systems successfully developed, launched, and utilized. Successful utilization will most likely occur if frequent, significant hardware-based milestones can be achieved throughout the program. Achieving these milestones will depend on the capability to perform highly realistic non-nuclear testing of nuclear systems. This paper discusses ongoing and potential research that could help achieve these milestones.

  9. Survey of tritium wastes and effluents in near-term fusion-research facilities

    International Nuclear Information System (INIS)

    Bickford, W.E.; Dingee, D.A.; Willingham, C.E.

    1981-08-01

    The use of tritium control technology in near-term research facilities has been studied for both the magnetic and inertial confinement fusion programs. This study focused on routine generation of tritium wastes and effluents, with little referene to accidents or facility decommissioning. This report serves as an independent review of the effectiveness of planned control technology and radiological hazards associated with operation. The facilities examined for the magnetic fusion program included Fusion Materials Irradiation Testing Facility (FMIT), Tritium Systems Test Assembly (TSTA), and Tokamak Fusion Test Reactor (TFTR) in the magnetic fusion program, while NOVA and Antares facilities were examined for the inertial confinement program

  10. Capital investment requirements for greenhouse gas emissions mitigation in power generation on near term to century time scales and global to regional spatial scales

    International Nuclear Information System (INIS)

    Chaturvedi, Vaibhav; Clarke, Leon; Edmonds, James; Calvin, Katherine; Kyle, Page

    2014-01-01

    Our paper explores the implication of climate mitigation policy and electricity generation technology performance for capital investment demands by the electric power sector on near term to century time scales. We find that stabilizing GHG emissions will require additional investment in the electricity generation sector over and above investments that would be needed in the absence of climate policy, in the range of 15 to 29 trillion US$ (48–94%) depending on the stringency of climate policy during the period 2015 to 2095 under default technology assumptions. This increase reflects the higher capital intensity of power systems that control emissions as well as increased electrification of the global economy. Limits on the penetration of nuclear and carbon capture and storage technology could increase costs substantially. Energy efficiency improvements can reduce the investment requirement by 18 to 24 trillion US$ (compared to default technology climate policy assumptions), depending on climate policy scenario. We also highlight the implications of different technology evolution scenarios for different regions. Under default technology set, the heaviest investments across scenarios in power generation were observed in China, India, SE Asia and Africa regions with the latter three regions dominating in the second half of the 21st century. - Highlights: • We present electricity generation investment requirement under different scenarios. • A climate policy will lead to substantial increase in investment requirement. • Stringency of climate policy has significant implications for investments. • Technology evolution and performance alter investment requirements significantly. • China, India, Southeast Asia and Africa dominate as investment destinations

  11. Climate, ecosystems, and planetary futures: The challenge to predict life in Earth system models.

    Science.gov (United States)

    Bonan, Gordon B; Doney, Scott C

    2018-02-02

    Many global change stresses on terrestrial and marine ecosystems affect not only ecosystem services that are essential to humankind, but also the trajectory of future climate by altering energy and mass exchanges with the atmosphere. Earth system models, which simulate terrestrial and marine ecosystems and biogeochemical cycles, offer a common framework for ecological research related to climate processes; analyses of vulnerability, impacts, and adaptation; and climate change mitigation. They provide an opportunity to move beyond physical descriptors of atmospheric and oceanic states to societally relevant quantities such as wildfire risk, habitat loss, water availability, and crop, fishery, and timber yields. To achieve this, the science of climate prediction must be extended to a more multifaceted Earth system prediction that includes the biosphere and its resources. Copyright © 2018, American Association for the Advancement of Science.

  12. A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

    Directory of Open Access Journals (Sweden)

    M Irfan Ashraf

    Full Text Available Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model. Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2 5-year(-1 and volume: 0.0008 m(3 5-year(-1. Model variability described by root mean squared error (RMSE in basal area prediction was 40.53 cm(2 5-year(-1 and 0.0393 m(3 5-year(-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence

  13. Predictive control, with restrictions for the climate of a greenhouse

    International Nuclear Information System (INIS)

    Pinon, Sandra; Pena, Miguel; Kuchen, Benjamin

    2002-01-01

    A proposal for controlling nonlinear systems under constraints is presented. a combination of model predictive control and feedback linearization is used. An alternative that uses extended kalman filter as non-measured variable estimator is applied for performing the constrained optimization. Finally, an observability analysis is done in closed loop in order to demonstrate observer convergence

  14. Contribution of Dynamic Vegetation Phenology to Decadal Climate Predictability

    NARCIS (Netherlands)

    Weiss, M.; Miller, P.A.; Hurk, van den B.J.J.M.; Noije, van T.; Stefanescu, S.; Haarsma, R.; Ulft, van L.H.; Hazeleger, W.; Sager, Le P.; Smith, B.; Schurgers, G.

    2014-01-01

    In this study, the impact of coupling and initializing the leaf area index from the dynamic vegetation model Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) is analyzed on skill of decadal predictions in the fully coupled atmosphere-land-ocean-sea ice model, the European Consortium Earth

  15. Measuring the potential utility of seasonal climate predictions

    Science.gov (United States)

    Tippett, Michael K.; Kleeman, Richard; Tang, Youmin

    2004-11-01

    Variation of sea surface temperature (SST) on seasonal-to-interannual time-scales leads to changes in seasonal weather statistics and seasonal climate anomalies. Relative entropy, an information theory measure of utility, is used to quantify the impact of SST variations on seasonal precipitation compared to natural variability. An ensemble of general circulation model (GCM) simulations is used to estimate this quantity in three regions where tropical SST has a large impact on precipitation: South Florida, the Nordeste of Brazil and Kenya. We find the yearly variation of relative entropy is strongly correlated with shifts in ensemble mean precipitation and weakly correlated with ensemble variance. Relative entropy is also found to be related to measures of the ability of the GCM to reproduce observations.

  16. Predicting Chronic Climate-Driven Disturbances and Their Mitigation

    Energy Technology Data Exchange (ETDEWEB)

    McDowell, Nate G.; Michaletz, Sean T.; Bennett, Katrina E.; Solander, Kurt C.; Xu, Chonggang; Maxwell, Reed M.; Middleton, Richard S.

    2018-01-01

    Society increasingly demands the stable provision of ecosystem resources to support our population. Resource risks from climate-driven disturbances--including drought, heat, insect outbreaks, and wildfire--are rising as a chronic state of disequilibrium results from increasing temperatures and a greater frequency of extreme events. This confluence of increased demand and risk may soon reach critical thresholds. We explain here why extreme chronic disequilibrium of ecosystem function is likely to increase dramatically across the globe, creating no-analog conditions that challenge adaptation. We also present novel mechanistic theory that combines models for disturbance mortality and metabolic scaling to link size-dependent plant mortality to changes in ecosystem stocks and fluxes. Efforts must anticipate and model chronic ecosystem disequilibrium to properly prepare for resilience planning.

  17. Life history and spatial traits predict extinction risk due to climate change

    Science.gov (United States)

    Pearson, Richard G.; Stanton, Jessica C.; Shoemaker, Kevin T.; Aiello-Lammens, Matthew E.; Ersts, Peter J.; Horning, Ned; Fordham, Damien A.; Raxworthy, Christopher J.; Ryu, Hae Yeong; McNees, Jason; Akçakaya, H. Reşit

    2014-03-01

    There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate. Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change based on the expectation that established assessments such as the IUCN Red List need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened, no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.

  18. Contribution of maternal thyroxine to fetal thyroxine pools in normal rats near term

    International Nuclear Information System (INIS)

    Morreale de Escobar, G.; Calvo, R.; Obregon, M.J.; Escobar Del Rey, F.

    1990-01-01

    Normal dams were equilibrated isotopically with [ 125 I]T4 infused from 11 to 21 days of gestation, at which time maternal and fetal extrathyroidal tissues were obtained to determine their [ 125 I]T4 and T4 contents. The specific activity of the [ 125 I]T4 in the fetal tissues was lower than in maternal T4 pools. The extent of this change allows evaluation of the net contribution of maternal T4 to the fetal extrathyroidal T4 pools. At 21 days of gestation, near term, this represents 17.5 +/- 0.9% of the T4 in fetal tissues, a value considerably higher than previously calculated. The methodological approach was validated in dams given a goitrogen to block fetal thyroid function. The specific activities of the [ 125 I]T4 in maternal and fetal T4 pools were then similar, confirming that in cases of fetal thyroid impairment the T4 in fetal tissues is determined by the maternal contribution. Thus, previous statements that in normal conditions fetal thyroid economy near term is totally independent of maternal thyroid status ought to be reconsidered

  19. Near-term and next-generation nuclear power plant concepts

    International Nuclear Information System (INIS)

    Shiga, Shigenori; Handa, Norihiko; Heki, Hideaki

    2002-01-01

    Near-term and next-generation nuclear reactors will be required to have high economic competitiveness in the deregulated electricity market, flexibility with respect to electricity demand and investment, and good public acceptability. For near-term reactors in the 2010s, Toshiba is developing an improved advanced boiling water reactor (ABWR) based on the present ABWR with newly rationalized systems and components; a construction period of 36 months, one year shorter than the current period; and a power lineup ranging from 800 MWe to 1,600 MWe. For future reactors in the 2020s and beyond, Toshiba is developing the ABWR-II for large-scale, centralized power sources; a supercritical water-cooled power reactor with high thermal efficiency for medium-scale power sources; a modular reactor with siting flexibility for small-scale power sources; and a small, fast neutron reactor with inherent safety for independent power sources. From the viewpoint of efficient uranium resource utilization, a low-moderation BWR core with a high conversion factor is also being developed. (author)

  20. Economic analysis of direct hydrogen PEM fuel cells in three near-term markets

    International Nuclear Information System (INIS)

    Mahadevan, K.; Stone, H.; Judd, K.; Paul, D.

    2007-01-01

    Direct hydrogen polymer electrolyte membrane fuel cells (H-PEMFCs) offer several near-term opportunities including backup power applications in state and local agencies of emergency response; forklifts in high throughput distribution centers; and, airport ground support equipment. This paper presented an analysis of the market requirements for introducing H-PEMFCs successfully, as well as an analysis of the lifecycle costs of H-PEMFCs and competing alternatives in three near-term markets. It also used three scenarios as examples of the potential for market penetration of H-PEMFCs. For each of the three potential opportunities, the paper presented the market requirements, a lifecycle cost analysis, and net present value of the lifecycle costs. A sensitivity analysis of the net present value of the lifecycle costs and of the average annual cost of owning and operating each of the H-PEMFC opportunities was also conducted. It was concluded that H-PEMFC-powered pallet trucks in high-productivity environments represented a promising early opportunity. However, the value of H-PEMFC-powered forklifts compared to existing alternatives was reduced for applications with lower hours of operation and declining labor rates. In addition, H-PEMFC-powered baggage tractors in airports were more expensive than battery-powered baggage tractors on a lifecycle cost basis. 9 tabs., 4 figs

  1. Antimatter Requirements and Energy Costs for Near-Term Propulsion Applications

    Science.gov (United States)

    Schmidt, G. R.; Gerrish, H. P.; Martin, J. J.; Smith, G. A.; Meyer, K. J.

    1999-01-01

    The superior energy density of antimatter annihilation has often been pointed to as the ultimate source of energy for propulsion. However, the limited capacity and very low efficiency of present-day antiproton production methods suggest that antimatter may be too costly to consider for near-term propulsion applications. We address this issue by assessing the antimatter requirements for six different types of propulsion concepts, including two in which antiprotons are used to drive energy release from combined fission/fusion. These requirements are compared against the capacity of both the current antimatter production infrastructure and the improved capabilities that could exist within the early part of next century. Results show that although it may be impractical to consider systems that rely on antimatter as the sole source of propulsive energy, the requirements for propulsion based on antimatter-assisted fission/fusion do fall within projected near-term production capabilities. In fact, a new facility designed solely for antiproton production but based on existing technology could feasibly support interstellar precursor missions and omniplanetary spaceflight with antimatter costs ranging up to $6.4 million per mission.

  2. Landscape genomic prediction for restoration of a Eucalyptus foundation species under climate change.

    Science.gov (United States)

    Supple, Megan Ann; Bragg, Jason G; Broadhurst, Linda M; Nicotra, Adrienne B; Byrne, Margaret; Andrew, Rose L; Widdup, Abigail; Aitken, Nicola C; Borevitz, Justin O

    2018-04-24

    As species face rapid environmental change, we can build resilient populations through restoration projects that incorporate predicted future climates into seed sourcing decisions. Eucalyptus melliodora is a foundation species of a critically endangered community in Australia that is a target for restoration. We examined genomic and phenotypic variation to make empirical based recommendations for seed sourcing. We examined isolation by distance and isolation by environment, determining high levels of gene flow extending for 500 km and correlations with climate and soil variables. Growth experiments revealed extensive phenotypic variation both within and among sampling sites, but no site-specific differentiation in phenotypic plasticity. Model predictions suggest that seed can be sourced broadly across the landscape, providing ample diversity for adaptation to environmental change. Application of our landscape genomic model to E. melliodora restoration projects can identify genomic variation suitable for predicted future climates, thereby increasing the long term probability of successful restoration. © 2018, Supple et al.

  3. Prediction of abundance of forest spiders according to climate warming in South Korea

    Directory of Open Access Journals (Sweden)

    Tae-Sung Kwon

    2014-06-01

    Full Text Available Distribution of spiders will be changed as climate warms. Abundance of spider species was predicted nationwide in South Korea. Abundance of spiders was projected using temperature species distribution model based on a nationwide data (366 forest sites according to climate change scenario RCP 4.5 and 8.5. The model predicts that 9 out of 17 species will increase in abundance while 8 species will decrease. Based on this finding, a qualitative prediction (increase or decrease was conducted on the species with more than 1% occurrence: 68 species are expected to decrease, 9 to increase, and 8 to change a little. In pooled estimation, 76 species (75% are expected to decrease, 18 species (18% to increase, and by 8 species (8% to have little change. The projection indicates that majority of spider species will decrease, but minority of species will increase as climate warms, suggesting great increase of remained species in lowlands.

  4. Thermal and hydrologic responses to climate change predict marked alterations in boreal stream invertebrate assemblages.

    Science.gov (United States)

    Mustonen, Kaisa-Riikka; Mykrä, Heikki; Marttila, Hannu; Sarremejane, Romain; Veijalainen, Noora; Sippel, Kalle; Muotka, Timo; Hawkins, Charles P

    2018-06-01

    Air temperature at the northernmost latitudes is predicted to increase steeply and precipitation to become more variable by the end of the 21st century, resulting in altered thermal and hydrological regimes. We applied five climate scenarios to predict the future (2070-2100) benthic macroinvertebrate assemblages at 239 near-pristine sites across Finland (ca. 1200 km latitudinal span). We used a multitaxon distribution model with air temperature and modeled daily flow as predictors. As expected, projected air temperature increased the most in northernmost Finland. Predicted taxonomic richness also increased the most in northern Finland, congruent with the predicted northwards shift of many species' distributions. Compositional changes were predicted to be high even without changes in richness, suggesting that species replacement may be the main mechanism causing climate-induced changes in macroinvertebrate assemblages. Northern streams were predicted to lose much of the seasonality of their flow regimes, causing potentially marked changes in stream benthic assemblages. Sites with the highest loss of seasonality were predicted to support future assemblages that deviate most in compositional similarity from the present-day assemblages. Macroinvertebrate assemblages were also predicted to change more in headwaters than in larger streams, as headwaters were particularly sensitive to changes in flow patterns. Our results emphasize the importance of focusing protection and mitigation on headwater streams with high-flow seasonality because of their vulnerability to climate change. © 2018 John Wiley & Sons Ltd.

  5. Simulating infectious disease risk based on climatic drivers: from numerical weather prediction to long term climate change scenario

    Science.gov (United States)

    Caminade, C.; Ndione, J. A.; Diallo, M.; MacLeod, D.; Faye, O.; Ba, Y.; Dia, I.; Medlock, J. M.; Leach, S.; McIntyre, K. M.; Baylis, M.; Morse, A. P.

    2012-04-01

    Climate variability is an important component in determining the incidence of a number of diseases with significant health and socioeconomic impacts. In particular, vector born diseases are the most likely to be affected by climate; directly via the development rates and survival of both the pathogen and the vector, and indirectly through changes in the surrounding environmental conditions. Disease risk models of various complexities using different streams of climate forecasts as inputs have been developed within the QWeCI EU and ENHanCE ERA-NET project frameworks. This work will present two application examples, one for Africa and one for Europe. First, we focus on Rift Valley fever over sub-Saharan Africa, a zoonosis that affects domestic animals and humans by causing an acute fever. We show that the Rift Valley fever outbreak that occurred in late 2010 in the northern Sahelian region of Mauritania might have been anticipated ten days in advance using the GFS numerical weather prediction system. Then, an ensemble of regional climate projections is employed to model the climatic suitability of the Asian tiger mosquito for the future over Europe. The Asian tiger mosquito is an invasive species originally from Asia which is able to transmit West Nile and Chikungunya Fever among others. This species has spread worldwide during the last decades, mainly through the shipments of goods from Asia. Different disease models are employed and inter-compared to achieve such a task. Results show that the climatic conditions over southern England, central Western Europe and the Balkans might become more suitable for the mosquito (including the proviso that the mosquito has already been introduced) to establish itself in the future.

  6. Predicting athletes' functional and dysfunctional emotions: The role of the motivational climate and motivation regulations.

    Science.gov (United States)

    Ruiz, Montse C; Haapanen, Saara; Tolvanen, Asko; Robazza, Claudio; Duda, Joan L

    2017-08-01

    This study examined the relationships between perceptions of the motivational climate, motivation regulations, and the intensity and functionality levels of athletes' pleasant and unpleasant emotional states. Specifically, we examined the hypothesised mediational role of motivation regulations in the climate-emotion relationship. We also tested a sequence in which emotions were assumed to be predicted by the motivational climate dimensions and then served as antecedents to variability in motivation regulations. Participants (N = 494) completed a multi-section questionnaire assessing targeted variables. Structural equation modelling (SEM) revealed that a perceived task-involving climate was a positive predictor of autonomous motivation and of the impact of functional anger, and a negative predictor of the intensity of anxiety and dysfunctional anger. Autonomous motivation was a partial mediator of perceptions of a task-involving climate and the impact of functional anger. An ego-involving climate was a positive predictor of controlled motivation, and of the intensity and impact of functional anger and the intensity of dysfunctional anger. Controlled motivation partially mediated the relationship between an ego-involving climate and the intensity of dysfunctional anger. Good fit to the data also emerged for the motivational climate, emotional states, and motivation regulations sequence. Findings provide support for the consideration of hedonic tone and functionality distinctions in the assessment of athletes' emotional states.

  7. Predicting climate-driven regime shifts versus rebound potential in coral reefs.

    Science.gov (United States)

    Graham, Nicholas A J; Jennings, Simon; MacNeil, M Aaron; Mouillot, David; Wilson, Shaun K

    2015-02-05

    Climate-induced coral bleaching is among the greatest current threats to coral reefs, causing widespread loss of live coral cover. Conditions under which reefs bounce back from bleaching events or shift from coral to algal dominance are unknown, making it difficult to predict and plan for differing reef responses under climate change. Here we document and predict long-term reef responses to a major climate-induced coral bleaching event that caused unprecedented region-wide mortality of Indo-Pacific corals. Following loss of >90% live coral cover, 12 of 21 reefs recovered towards pre-disturbance live coral states, while nine reefs underwent regime shifts to fleshy macroalgae. Functional diversity of associated reef fish communities shifted substantially following bleaching, returning towards pre-disturbance structure on recovering reefs, while becoming progressively altered on regime shifting reefs. We identified threshold values for a range of factors that accurately predicted ecosystem response to the bleaching event. Recovery was favoured when reefs were structurally complex and in deeper water, when density of juvenile corals and herbivorous fishes was relatively high and when nutrient loads were low. Whether reefs were inside no-take marine reserves had no bearing on ecosystem trajectory. Although conditions governing regime shift or recovery dynamics were diverse, pre-disturbance quantification of simple factors such as structural complexity and water depth accurately predicted ecosystem trajectories. These findings foreshadow the likely divergent but predictable outcomes for reef ecosystems in response to climate change, thus guiding improved management and adaptation.

  8. Streamflow predictions under climate scenarios in the Boulder Creek Watershed at Orodell

    Science.gov (United States)

    Zhang, Q.; Williams, M. W.; Livneh, B.

    2016-12-01

    Mountainous areas have complex geological features and climatic variability, which limit our ability to simulate and predict hydrologic processes, especially in face to a changing climate. Hydrologic models can improve our understanding of land surface water and energy budgets in these regions. In this study, a distributed physically-based hydrologic model is applied to the Boulder Creek Watershed, USA to study streamflow conditions under future climatic scenarios. Model parameters were adjusted using observed streamflow data at 1/16th degree resolution, with a NSE value of 0.69. The results from CMIP5 models can give a general range of streamflow conditions under different climatic scenarios. Two scenarios are being applied, including the RCP 4.5 and 8.5 scenarios. RCP 8.5 has higher emission concentrations than RCP 4.5, but not very significant in the period of study. Using pair t-test and Mann-Whitney test at specific grid cells to compare modeled and observed climate data, four CMIP5 models were chosen to predict streamflow from 2010 to 2025. Of the four models, two models predicted increased precipitation, while the other two models predicted decreased precipitation, and the four models predicted increased minimum and maximum temperature in RCP 4.5. Average streamflow decreased by 2% 14%, while maximum SWE varies from -7% to +210% from 2010 to 2025, relative to 2006 to 2010. In RCP 8.5, three models predicted increased precipitation, while the other one model predicted decreased precipitation, and the four models predicted increased maximum and minimum temperature. Besides one model, the other three models predicted increased average streamflow by 3.5% 32%, which results from the higher increasing magnitude in precipitation. Maximum SWE varies by 6% 55% higher than that from 2006 to 2010. This study shows that average daily maximum and minimum temperature will increase toward 2025 from different climate models, while average streamflow will decrease in RCP 4

  9. Climate extremes and predicted warming threaten Mediterranean Holocene firs forests refugia.

    Science.gov (United States)

    Sánchez-Salguero, Raúl; Camarero, J Julio; Carrer, Marco; Gutiérrez, Emilia; Alla, Arben Q; Andreu-Hayles, Laia; Hevia, Andrea; Koutavas, Athanasios; Martínez-Sancho, Elisabet; Nola, Paola; Papadopoulos, Andreas; Pasho, Edmond; Toromani, Ervin; Carreira, José A; Linares, Juan C

    2017-11-21

    Warmer and drier climatic conditions are projected for the 21st century; however, the role played by extreme climatic events on forest vulnerability is still little understood. For example, more severe droughts and heat waves could threaten quaternary relict tree refugia such as Circum-Mediterranean fir forests (CMFF). Using tree-ring data and a process-based model, we characterized the major climate constraints of recent (1950-2010) CMFF growth to project their vulnerability to 21st-century climate. Simulations predict a 30% growth reduction in some fir species with the 2050s business-as-usual emission scenario, whereas growth would increase in moist refugia due to a longer and warmer growing season. Fir populations currently subjected to warm and dry conditions will be the most vulnerable in the late 21st century when climatic conditions will be analogous to the most severe dry/heat spells causing dieback in the late 20th century. Quantification of growth trends based on climate scenarios could allow defining vulnerability thresholds in tree populations. The presented predictions call for conservation strategies to safeguard relict tree populations and anticipate how many refugia could be threatened by 21st-century dry spells.

  10. Ensembles-based predictions of climate change impacts on bioclimatic zones in Northeast Asia

    Science.gov (United States)

    Choi, Y.; Jeon, S. W.; Lim, C. H.; Ryu, J.

    2017-12-01

    Biodiversity is rapidly declining globally and efforts are needed to mitigate this continually increasing loss of species. Clustering of areas with similar habitats can be used to prioritize protected areas and distribute resources for the conservation of species, selection of representative sample areas for research, and evaluation of impacts due to environmental changes. In this study, Northeast Asia (NEA) was classified into 14 bioclimatic zones using statistical techniques, which are correlation analysis and principal component analysis (PCA), and the iterative self-organizing data analysis technique algorithm (ISODATA). Based on these bioclimatic classification, we predicted shift of bioclimatic zones due to climate change. The input variables include the current climatic data (1960-1990) and the future climatic data of the HadGEM2-AO model (RCP 4.5(2050, 2070) and 8.5(2050, 2070)) provided by WorldClim. Using these data, multi-modeling methods including maximum likelihood classification, random forest, and species distribution modelling have been used to project the impact of climate change on the spatial distribution of bioclimatic zones within NEA. The results of various models were compared and analyzed by overlapping each result. As the result, significant changes in bioclimatic conditions can be expected throughout the NEA by 2050s and 2070s. The overall zones moved upward and some zones were predicted to disappear. This analysis provides the basis for understanding potential impacts of climate change on biodiversity and ecosystem. Also, this could be used more effectively to support decision making on climate change adaptation.

  11. A Quantum Annealing Computer Team Addresses Climate Change Predictability

    Science.gov (United States)

    Halem, M. (Principal Investigator); LeMoigne, J.; Dorband, J.; Lomonaco, S.; Yesha, Ya.; Simpson, D.; Clune, T.; Pelissier, C.; Nearing, G.; Gentine, P.; hide

    2016-01-01

    The near confluence of the successful launch of the Orbiting Carbon Observatory2 on July 2, 2014 and the acceptance on August 20, 2015 by Google, NASA Ames Research Center and USRA of a 1152 qubit D-Wave 2X Quantum Annealing Computer (QAC), offered an exceptional opportunity to explore the potential of this technology to address the scientific prediction of global annual carbon uptake by land surface processes. At UMBC,we have collected and processed 20 months of global Level 2 light CO2 data as well as fluorescence data. In addition we have collected ARM data at 2sites in the US and Ameriflux data at more than 20 stations. J. Dorband has developed and implemented a multi-hidden layer Boltzmann Machine (BM) algorithm on the QAC. Employing the BM, we are calculating CO2 fluxes by training collocated OCO-2 level 2 CO2 data with ARM ground station tower data to infer to infer measured CO2 flux data. We generate CO2 fluxes with a regression analysis using these BM derived weights on the level 2 CO2 data for three Ameriflux sites distinct from the ARM stations. P. Gentine has negotiated for the access of K34 Ameriflux data in the Amazon and is applying a neural net to infer the CO2 fluxes. N. Talik validated the accuracy of the BM performance on the QAC against a restricted BM implementation on the IBM Softlayer Cloud with the Nvidia co-processors utilizing the same data sets. G. Nearing and K. Harrison have extended the GSFC LIS model with the NCAR Noah photosynthetic parameterization and have run a 10 year global prediction of the net ecosystem exchange. C. Pellisier is preparing a BM implementation of the Kalman filter data assimilation of CO2 fluxes. At UMBC, R. Prouty is conducting OSSE experiments with the LISNoah model on the IBM iDataPlex to simulate the impact of CO2 fluxes to improve the prediction of global annual carbon uptake. J. LeMoigne and D. Simpson have developed a neural net image registration system that will be used for MODIS ENVI and will be

  12. Analysis of near-term production and market opportunities for hydrogen and related activities

    Energy Technology Data Exchange (ETDEWEB)

    Mauro, R.; Leach, S. [National Hydrogen Association, Washington, DC (United States)

    1995-09-01

    This paper summarizes current and planned activities in the areas of hydrogen production and use, near-term venture opportunities, and codes and standards. The rationale for these efforts is to assess industry interest and engage in activities that move hydrogen technologies down the path to commercialization. Some of the work presented in this document is a condensed, preliminary version of reports being prepared under the DOE/NREL contract. In addition, the NHA work funded by Westinghouse Savannah River Corporation (WSRC) to explore the opportunities and industry interest in a Hydrogen Research Center is briefly described. Finally, the planned support of and industry input to the Hydrogen Technical Advisory Panel (HTAP) on hydrogen demonstration projects is discussed.

  13. Chemicals from Biomass: A Market Assessment of Bioproducts with Near-Term Potential

    Energy Technology Data Exchange (ETDEWEB)

    Biddy, Mary J. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Scarlata, Christopher [National Renewable Energy Lab. (NREL), Golden, CO (United States); Kinchin, Christopher [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-03-23

    Production of chemicals from biomass offers a promising opportunity to reduce U.S. dependence on imported oil, as well as to improve the overall economics and sustainability of an integrated biorefinery. Given the increasing momentum toward the deployment and scale-up of bioproducts, this report strives to: (1) summarize near-term potential opportunities for growth in biomass-derived products; (2) identify the production leaders who are actively scaling up these chemical production routes; (3) review the consumers and market champions who are supporting these efforts; (4) understand the key drivers and challenges to move biomass-derived chemicals to market; and (5) evaluate the impact that scale-up of chemical strategies will have on accelerating the production of biofuels.

  14. Near-term electric-vehicle program. Phase II. Mid-term review summary report

    Energy Technology Data Exchange (ETDEWEB)

    1978-07-27

    The general objective of the Near-Term Electric Vehicle Program is to confirm that, in fact, the complete spectrum of requirements placed on the automobile (e.g., safety, producibility, utility, etc.) can still be satisfied if electric power train concepts are incorporated in lieu of contemporary power train concepts, and that the resultant set of vehicle characteristics are mutually compatible, technologically achievable, and economically achievable. The focus of the approach to meeting this general objective involves the design, development, and fabrication of complete electric vehicles incorporating, where necessary, extensive technological advancements. A mid-term summary is presented of Phase II which is a continuation of the preliminary design study conducted in Phase I of the program. Information is included on vehicle performance and performance simulation models; battery subsystems; control equipment; power systems; vehicle design and components for suspension, steering, and braking; scale model testing; structural analysis; and vehicle dynamics analysis. (LCL)

  15. Closed Nuclear Fuel Cycle Technologies to Meet Near-Term and Transition Period Requirements

    International Nuclear Information System (INIS)

    Collins, E.D.; Felker, L.K.; Benker, D.E.; Campbell, D.O.

    2008-01-01

    A scenario that very likely fits conditions in the U.S. nuclear power industry and can meet the goals of cost minimization, waste minimization, and provisions of engineered safeguards for proliferation resistance, including no separated plutonium, to close the fuel cycle with full actinide recycle is evaluated. Processing aged fuels, removed from the reactor for 30 years or more, can provide significant advantages in cost reduction and waste minimization. The UREX+3 separations process is being developed to separate used fuel components for reuse, thus minimizing waste generation and storage in geologic repositories. Near-term use of existing and new thermal spectrum reactors can be used initially for recycle actinide transmutation. A transition period will eventually occur, when economic conditions will allow commercial deployment of fast reactors; during this time, recycled plutonium can be diverted into fast reactor fuel and conversion of depleted uranium into additional fuel material can be considered. (authors)

  16. Heliostat Manufacturing for near-term markets. Phase II final report

    International Nuclear Information System (INIS)

    1998-01-01

    This report describes a project by Science Applications International Corporation and its subcontractors Boeing/Rocketdyne and Bechtel Corp. to develop manufacturing technology for production of SAIC stretched membrane heliostats. The project consists of three phases, of which two are complete. This first phase had as its goals to identify and complete a detailed evaluation of manufacturing technology, process changes, and design enhancements to be pursued for near-term heliostat markets. In the second phase, the design of the SAIC stretched membrane heliostat was refined, manufacturing tooling for mirror facet and structural component fabrication was implemented, and four proof-of-concept/test heliostats were produced and installed in three locations. The proposed plan for Phase III calls for improvements in production tooling to enhance product quality and prepare increased production capacity. This project is part of the U.S. Department of Energy's Solar Manufacturing Technology Program (SolMaT)

  17. Closed Nuclear Fuel Cycle Technologies to Meet Near-Term and Transition Period Requirements

    Energy Technology Data Exchange (ETDEWEB)

    Collins, E.D.; Felker, L.K.; Benker, D.E.; Campbell, D.O. [Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, Tennessee, 37831-6152 (United States)

    2008-07-01

    A scenario that very likely fits conditions in the U.S. nuclear power industry and can meet the goals of cost minimization, waste minimization, and provisions of engineered safeguards for proliferation resistance, including no separated plutonium, to close the fuel cycle with full actinide recycle is evaluated. Processing aged fuels, removed from the reactor for 30 years or more, can provide significant advantages in cost reduction and waste minimization. The UREX+3 separations process is being developed to separate used fuel components for reuse, thus minimizing waste generation and storage in geologic repositories. Near-term use of existing and new thermal spectrum reactors can be used initially for recycle actinide transmutation. A transition period will eventually occur, when economic conditions will allow commercial deployment of fast reactors; during this time, recycled plutonium can be diverted into fast reactor fuel and conversion of depleted uranium into additional fuel material can be considered. (authors)

  18. Near term and long term materials issues and development needs for plasma interactive components

    International Nuclear Information System (INIS)

    Mattas, R.F.

    1986-01-01

    Plasma interactive components (PICs), including the first wall, limiter blades, divertor collector plates, halo scrapers, and RF launchers, are exposed to high particle fluxes that can result in high sputtering erosion rates and high heat fluxes. In addition, the materials in reactors are exposed to high neutron fluxes which will degrade the bulk properties. This severe environment will limit the materials and designs which can be used in fusion devices. In order to provide a reasonable degree of confidence that plasma interactive components will operate successfully, a comprehensive development program is needed. Materials research and development plays a key role in the successful development of PICs. The range of operating conditions along with a summary of the major issues for materials development is described. The areas covered include plasma/materials interactions, erosion/redeposition, baseline materials properties, fabrication, and irradiation damage effects. Candidate materials and materials development needs in the near term and long term are identified

  19. Collaborative Research: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-12-28

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

  20. Predicting Satisfaction in Physical Education from Motivational Climate and Self-Determined Motivation

    Science.gov (United States)

    Baena-Extremera, Antonio; Gómez-López, Manuel; Granero-Gallegos, Antonio; Ortiz-Camacho, Maria del Mar

    2015-01-01

    The purpose of this research study was to determine to what extent the motivational climate perceived by students in Physical Education (PE) classes predicts self-determined motivation, and satisfaction with physical education classes. Questionnaires were administered to 758 high school students aged 13-18 years. We used the Spanish versions of…

  1. Prediction of the impacts of climate changes on the stream flow of ...

    African Journals Online (AJOL)

    Abstract. Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on Ajali River watershed, Aguobu-Umumba, Ezeagu, Enugu State, Nigeria. The model was first used to simulate stream flow using observed data. After model run, parameterization, sensitivity analysis, the monthly ...

  2. Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions.

    Science.gov (United States)

    Fox, Naomi J; Marion, Glenn; Davidson, Ross S; White, Piran C L; Hutchings, Michael R

    2012-03-06

    Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed.

  3. Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions

    Directory of Open Access Journals (Sweden)

    Ross S. Davidson

    2012-03-01

    Full Text Available Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed.

  4. A physical model to predict climate dynamics in ventilated bulk-storage of agricultural produce

    NARCIS (Netherlands)

    Lukasse, L.J.S.; Kramer-Cuppen, de J.E.; Voort, van der A.J.

    2007-01-01

    This paper presents a physical model for predicting climate dynamics in ventilated bulk-storage of agricultural produce. A well-ordered model presentation was obtained by combining an object-oriented zonal decomposition with a process-oriented decomposition through matrix¿vector notation. The

  5. Evaluation and attribution of vegetation contribution to seasonal climate predictability

    Science.gov (United States)

    Catalano, Franco; Alessandri, Andrea; De Felice, Matteo

    2015-04-01

    The land surface model of EC-Earth has been modified to include dependence of vegetation densities on the Leaf Area Index (LAI), based on the Lambert-Beer formulation. Effective vegetation fractional coverage can now vary at seasonal and interannual time-scales and therefore affect biophysical parameters such as the surface roughness, albedo and soil field capacity. The modified model is used to perform a real predictability seasonal hindcast experiment. LAI is prescribed using a recent observational dataset based on the third generation GIMMS and MODIS satellite data. Hindcast setup is: 7 months forecast length, 2 start dates (1st May and 1st November), 10 members, 28 years (1982-2009). The effect of the realistic LAI prescribed from observation is evaluated with respect to a control experiment where LAI does not vary. Hindcast results demonstrate that a realistic representation of vegetation significantly improves the forecasts of temperature and precipitation. The sensitivity is particularly large for temperature during boreal winter over central North America and Central Asia. This may be attributed in particular to the effect of the high vegetation component on the snow cover. Summer forecasts are improved in particular for precipitation over Europe, Sahel, North America, West Russia and Nordeste. Correlation improvements depends on the links between targets (temperature and precipitation) and drivers (surface heat fluxes, albedo, soil moisture, evapotranspiration, moisture divergence) which varies from region to region.

  6. Wave climate change, coastline response and hazard prediction in New South Wales, Australia

    International Nuclear Information System (INIS)

    Goodwin, Ian D.; Verdon, Danielle; Cowell, Peter

    2007-01-01

    Full text: Full text: Considerable research effort has been directed towards understanding and the gross prediction of shoreline response to sea level rise (eg. Cowell ef a/. 2003a, b). In contrast, synoptic prediction of changes in the planform configuration of shorelines in response to changes in wind and wave climates over many decades has been limited by the lack of geohistorical data on shoreline alignment evolution and long time series of wave climate. This paper presents new data sets on monthly mean wave direction variability based on: a. Waverider buoy data; b. a reconstruction of monthly mid-shelf wave direction, 1877 to 2002 AD from historical MSLP data (Goodwin 2005); and c. a multi-decadal reconstruction of wave direction, in association with the Interdecadal Pacific Oscillation and the Southern Annular Mode of climate variability, covering the past millennium. A model of coastline response to the wave climate variability is presented for northern and central New South Wales (NSW) for decadal to multi-decadal time scales, and is based on instrumental and geohistorical data. The sensitivity of the coastline position and alignment, and beach state to mean and extreme wave climate changes is demonstrated (e.g. Goodwin et al. 2006). State changes in geometric shoreline alignment rotation, sand volume (progradation/recession) for NSW and mean wave direction, are shown to be in agreement with the low-frequency change in Pacific-wide climate. Synoptic typing of climate patterns using Self Organised Mapping methods is used to downscale CSIRO GCM output for this century. The synoptic types are correlated to instrumental wave climate data and coastal behaviour. The shifts in downscaled synoptic types for 2030 and 2070 AD are then used as the basis for predicting mean wave climate changes, coastal behaviour and hazards along the NSW coastline. The associated coastal hazards relate to the definition of coastal land loss through rising sea levels and shoreline

  7. Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

    Science.gov (United States)

    Gilligan, J. M.; John, N. J.; van der Linden, M.

    2015-12-01

    Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

  8. Predicting the impact of climate change on threatened species in UK waters.

    Directory of Open Access Journals (Sweden)

    Miranda C Jones

    Full Text Available Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis and angelshark (Squatina squatina.

  9. Approaches to predicting potential impacts of climate change on forest disease: an example with Armillaria root disease

    Science.gov (United States)

    Ned B. Klopfenstein; Mee-Sook Kim; John W. Hanna; Bryce A. Richardson; John E. Lundquist

    2009-01-01

    Predicting climate change influences on forest diseases will foster forest management practices that minimize adverse impacts of diseases. Precise locations of accurately identified pathogens and hosts must be documented and spatially referenced to determine which climatic factors influence species distribution. With this information, bioclimatic models can predict the...

  10. Prediction of trace gas emissions and their climatic impacts. Some geographical considerations

    Energy Technology Data Exchange (ETDEWEB)

    Nicholson, S E [Florida State Univ., Dept. ofMeteorology, Tallahassee, FL (United States)

    1993-12-31

    This paper examines two major areas of uncertainty in the prediction of the impact of trace gas emissions on climate. The first is socioeconomic factors which determine the rate of such processes as resource use, industrial production or land conversion. The second is the feedback between the earth`s land surface and climate. Since the land surface is the source of trace gas emissions, both natural and anthropogenic changes of vegetation will affect the nature and quantity of emissions. This paper demonstrates large-scale land surface changes which have taken place naturally or from human activities, either intentionally or inadvertently, and describes the dwindling availability of natural resources, using water as an example. Vegetation is also examined as both a response to and a determining factor in climate. Hence, the intricate feedback between vegetation and climate complicates any attempt to predict climatic change. Better quantitative assessment of all relationships and processes is required to achieve realistic forecasts of global change. (au) 31 refs.

  11. Space can substitute for time in predicting climate-change effects on biodiversity

    Science.gov (United States)

    Blois, Jessica L.; Williams, John W.; Fitzpatrick, Matthew C.; Jackson, Stephen T.; Ferrier, Simon

    2013-01-01

    “Space-for-time” substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption—that drivers of spatial gradients of species composition also drive temporal changes in diversity—rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as “time-for-time” predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

  12. Space can substitute for time in predicting climate-change effects on biodiversity.

    Science.gov (United States)

    Blois, Jessica L; Williams, John W; Fitzpatrick, Matthew C; Jackson, Stephen T; Ferrier, Simon

    2013-06-04

    "Space-for-time" substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption--that drivers of spatial gradients of species composition also drive temporal changes in diversity--rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as "time-for-time" predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

  13. Shifts in frog size and phenology: Testing predictions of climate change on a widespread anuran using data from prior to rapid climate warming.

    Science.gov (United States)

    Sheridan, Jennifer A; Caruso, Nicholas M; Apodaca, Joseph J; Rissler, Leslie J

    2018-01-01

    Changes in body size and breeding phenology have been identified as two major ecological consequences of climate change, yet it remains unclear whether climate acts directly or indirectly on these variables. To better understand the relationship between climate and ecological changes, it is necessary to determine environmental predictors of both size and phenology using data from prior to the onset of rapid climate warming, and then to examine spatially explicit changes in climate, size, and phenology, not just general spatial and temporal trends. We used 100 years of natural history collection data for the wood frog, Lithobates sylvaticus with a range >9 million km 2 , and spatially explicit environmental data to determine the best predictors of size and phenology prior to rapid climate warming (1901-1960). We then tested how closely size and phenology changes predicted by those environmental variables reflected actual changes from 1961 to 2000. Size, phenology, and climate all changed as expected (smaller, earlier, and warmer, respectively) at broad spatial scales across the entire study range. However, while spatially explicit changes in climate variables accurately predicted changes in phenology, they did not accurately predict size changes during recent climate change (1961-2000), contrary to expectations from numerous recent studies. Our results suggest that changes in climate are directly linked to observed phenological shifts. However, the mechanisms driving observed body size changes are yet to be determined, given the less straightforward relationship between size and climate factors examined in this study. We recommend that caution be used in "space-for-time" studies where measures of a species' traits at lower latitudes or elevations are considered representative of those under future projected climate conditions. Future studies should aim to determine mechanisms driving trends in phenology and body size, as well as the impact of climate on population

  14. Predicting Nitrate Transport under Future Climate Scenarios beneath the Nebraska Management Systems Evaluation Area (MSEA) site

    Science.gov (United States)

    Li, Y.; Akbariyeh, S.; Gomez Peña, C. A.; Bartlet-Hunt, S.

    2017-12-01

    Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize adverse impacts of agricultural activities on groundwater quality. The goal of this work is to evaluate the direct effects of climate change on the fate and transport of nitrate beneath a center-pivot irrigated corn field in Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge rate and actual evapotranspiration rate were predicted based on an inverse modeling approach using climate data generated by Weather Research and Forecasting (WRF) model under the RCP 8.5 scenario, which was downscaled from global CCSM4 model to a resolution of 24 by 24 km2. A groundwater flow model was first calibrated based on historical groundwater table measurement and was then applied to predict future groundwater table in the period 2057-2060. Finally, predicted future groundwater recharge rate, actual evapotranspiration rate, and groundwater level, together with future precipitation data from WRF, were used in a three-dimensional (3D) model, which was validated based on rich historic data set collected from 1993-1996, to predict nitrate concentration in soil and groundwater from the year 2057 to 2060. Future groundwater recharge was found to be decreasing in the study area compared to average groundwater recharge data from the literature. Correspondingly, groundwater elevation was predicted to decrease (1 to 2 ft) over the five years of simulation. Predicted higher transpiration data from climate model resulted in lower infiltration of nitrate concentration in subsurface within the root zone.

  15. Dynamic response of airborne infections to climate change: predictions for varicella

    Science.gov (United States)

    Baker, R.; Mahmud, A. S.; Metcalf, C. J. E.

    2017-12-01

    Characterizing how climate change will alter the burden of infectious diseases has clear applications for public health policy. Despite our uniquely detailed understanding of the transmission process for directly transmitted infections, the impact of climate variables on these infections remains understudied. We develop a novel methodology for estimating the causal relationship between climate and directly transmitted infections, which combines an epidemiological model of disease transmission with panel regression techniques. Our method allows us to move beyond correlational approaches to studying the link between climate and infectious diseases. Further, we can generate semi-mechanistic projections of incidence across climate scenarios. We illustrate our approach using 30 years of reported cases of varicella, a common airborne childhood infection, across 32 states in Mexico. We find significantly increased varicella transmission in drier conditions. We use this to map potential changes in the magnitude and variability of varicella incidence in Mexico as a result of projected changes in future climate conditions. Our results indicate that the predicted decrease in humidity in Mexico towards the end of the century will increase incidence of varicella, all else equal, and that these changes in incidence will be non-uniform across the year.

  16. Projected climate change impacts and short term predictions on staple crops in Sub-Saharan Africa

    Science.gov (United States)

    Mereu, V.; Spano, D.; Gallo, A.; Carboni, G.

    2013-12-01

    . Multiple combinations of soils and climate conditions, crop management and varieties were considered for the different Agro-Ecological Zones. The climate impact was assessed using future climate prediction, statistically and/or dynamically downscaled, for specific areas. Direct and indirect effects of different CO2 concentrations projected for the future periods were separately explored to estimate their effects on crops. Several adaptation strategies (e.g., introduction of full irrigation, shift of the ordinary sowing/planting date, changes in the ordinary fertilization management) were also evaluated with the aim to reduce the negative impact of climate change on crop production. The results of the study, analyzed at local, AEZ and country level, will be discussed.

  17. Antibiotic prophylaxis for term or near-term premature rupture of membranes: metaanalysis of randomized trials.

    Science.gov (United States)

    Saccone, Gabriele; Berghella, Vincenzo

    2015-05-01

    The objective of the study was to evaluate the efficacy of antibiotic prophylaxis in women with term or near-term premature rupture of membranes. Searches were performed in MEDLINE, OVID, Scopus, ClinicalTrials.gov, the PROSPERO International Prospective Register of Systematic Reviews, EMBASE, ScienceDirect.com, MEDSCAPE, and the Cochrane Central Register of Controlled Trials with the use of a combination of key words and text words related to antibiotics, premature rupture of membranes, term, and trials from inception of each database to September 2014. We included all randomized trials of singleton gestations with premature rupture of membranes at 36 weeks or more, who were randomized to antibiotic prophylaxis or control (either placebo or no treatment). The primary outcomes included maternal chorioamnionitis and neonatal sepsis. A subgroup analysis on studies with latency more than 12 hours was planned. Before data extraction, the review was registered with the PROSPERO International Prospective Register of Systematic Reviews (registration number CRD42014013928). The metaanalysis was performed following the Preferred Reporting Item for Systematic Reviews and Meta-analyses statement. Women who received antibiotics had the same rate of chorioamnionitis (2.7% vs 3.7%; relative risk [RR], 0.73, 95% confidence interval [CI], 0.48-1.12), endometritis (0.4% vs 0.9%; RR, 0.44, 95% CI, 0.18-1.10), maternal infection (3.1% vs 4.6%; RR, 0.48, 95% CI, 0.19-1.21), and neonatal sepsis (1.0% vs 1.4%; RR, 0.69, 95% CI, 0.34-1.39). In the planned subgroup analysis, women with latency longer than 12 hours, who received antibiotics, had a lower rate of chorioamnionitis (2.9% vs 6.1%; RR, 0.49, 95% CI, 0.27-0.91) and endometritis (0% vs 2.2%; RR, 0.12, 95% CI, 0.02-0.62) compared with the control group. Antibiotic prophylaxis for term or near-term premature rupture of membranes is not associated with any benefits in either maternal or neonatal outcomes. In women with latency longer

  18. Prediction of seasonal climate-induced variations in global food production

    Science.gov (United States)

    Iizumi, Toshichika; Sakuma, Hirofumi; Yokozawa, Masayuki; Luo, Jing-Jia; Challinor, Andrew J.; Brown, Molly E.; Sakurai, Gen; Yamagata, Toshio

    2013-10-01

    Consumers, including the poor in many countries, are increasingly dependent on food imports and are thus exposed to variations in yields, production and export prices in the major food-producing regions of the world. National governments and commercial entities are therefore paying increased attention to the cropping forecasts of important food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years. Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We found that moderate-to-marked yield loss over a substantial percentage (26-33%) of the harvested area of these crops is reliably predictable if climatic forecasts are near perfect. However, only rice and wheat production are reliably predictable at three months before the harvest using within-season hindcasts. The reliabilities of estimates varied substantially by crop--rice and wheat yields were the most predictable, followed by soybean and maize. The reasons for variation in the reliability of the estimates included the differences in crop sensitivity to the climate and the technology used by the crop-producing regions. Our findings reveal that the use of seasonal climatic forecasts to predict crop failures will be useful for monitoring global food production and will encourage the adaptation of food systems toclimatic extremes.

  19. Understanding and predicting climate variations in the Middle East for sustainable water resource management and development

    Science.gov (United States)

    Samuels, Rana

    Water issues are a source of tension between Israelis and Palestinians. In the and region of the Middle East, water supply is not just scarce but also uncertain: It is not uncommon for annual rainfall to be as little as 60% or as much as 125% of the multiannual average. This combination of scarcity and uncertainty exacerbates the already strained economy and the already tensed political situation. The uncertainty could be alleviated if it were possible to better forecast water availability. Such forecasting is key not only for water planning and management, but also for economic policy and for political decision making. Water forecasts at multiple time scales are necessary for crop choice, aquifer operation and investments in desalination infrastructure. The unequivocal warming of the climate system adds another level of uncertainty as global and regional water cycles change. This makes the prediction of water availability an even greater challenge. Understanding the impact of climate change on precipitation can provide the information necessary for appropriate risk assessment and water planning. Unfortunately, current global circulation models (GCMs) are only able to predict long term climatic evolution at large scales but not local rainfall. The statistics of local precipitation are traditionally predicted using historical rainfall data. Obviously these data cannot anticipate changes that result from climate change. It is therefore clear that integration of the global information about climate evolution and local historical data is needed to provide the much needed predictions of regional water availability. Currently, there is no theoretical or computational framework that enables such integration for this region. In this dissertation both a conceptual framework and a computational platform for such integration are introduced. In particular, suite of models that link forecasts of climatic evolution under different CO2 emissions scenarios to observed rainfall

  20. Using Prediction Markets to Generate Probability Density Functions for Climate Change Risk Assessment

    Science.gov (United States)

    Boslough, M.

    2011-12-01

    Climate-related uncertainty is traditionally presented as an error bar, but it is becoming increasingly common to express it in terms of a probability density function (PDF). PDFs are a necessary component of probabilistic risk assessments, for which simple "best estimate" values are insufficient. Many groups have generated PDFs for climate sensitivity using a variety of methods. These PDFs are broadly consistent, but vary significantly in their details. One axiom of the verification and validation community is, "codes don't make predictions, people make predictions." This is a statement of the fact that subject domain experts generate results using assumptions within a range of epistemic uncertainty and interpret them according to their expert opinion. Different experts with different methods will arrive at different PDFs. For effective decision support, a single consensus PDF would be useful. We suggest that market methods can be used to aggregate an ensemble of opinions into a single distribution that expresses the consensus. Prediction markets have been shown to be highly successful at forecasting the outcome of events ranging from elections to box office returns. In prediction markets, traders can take a position on whether some future event will or will not occur. These positions are expressed as contracts that are traded in a double-action market that aggregates price, which can be interpreted as a consensus probability that the event will take place. Since climate sensitivity cannot directly be measured, it cannot be predicted. However, the changes in global mean surface temperature are a direct consequence of climate sensitivity, changes in forcing, and internal variability. Viable prediction markets require an undisputed event outcome on a specific date. Climate-related markets exist on Intrade.com, an online trading exchange. One such contract is titled "Global Temperature Anomaly for Dec 2011 to be greater than 0.65 Degrees C." Settlement is based

  1. Near term hybrid passenger vehicle development program. Phase I. Appendices C and D. Final report

    Energy Technology Data Exchange (ETDEWEB)

    1980-01-01

    The derivation of and actual preliminary design of the Near Term Hybrid Vehicle (NTHV) are presented. The NTHV uses a modified GM Citation body, a VW Rabbit turbocharged diesel engine, a 24KW compound dc electric motor, a modified GM automatic transmission, and an on-board computer for transmission control. The following NTHV information is presented: the results of the trade-off studies are summarized; the overall vehicle design; the selection of the design concept and the base vehicle (the Chevrolet Citation), the battery pack configuration, structural modifications, occupant protection, vehicle dynamics, and aerodynamics; the powertrain design, including the transmission, coupling devices, engine, motor, accessory drive, and powertrain integration; the motor controller; the battery type, duty cycle, charger, and thermal requirements; the control system (electronics); the identification of requirements, software algorithm requirements, processor selection and system design, sensor and actuator characteristics, displays, diagnostics, and other topics; environmental system including heating, air conditioning, and compressor drive; the specifications, weight breakdown, and energy consumption measures; advanced technology components, and the data sources and assumptions used. (LCL)

  2. Alternative routes to improved fuel utilization: Analysis of near-term economic incentives

    International Nuclear Information System (INIS)

    Salo, J.P.; Vieno, T.; Vira, J.

    1984-01-01

    The potential for savings in the nuclear fuel cycle costs is discussed from the point of view of a single utility. The analysis is concentrated on the existing and near-term economic incentives for improved fuel utilization, and the context is that of a small country without domestic fuel cycle services. In the uranium fuel cycle the extended burnup produces savings in the uranium feed as well as in the fuel fabrication and waste management requirements. The front-end fuel cycle cost impact is evaluated for BWRs. In the back-end part the situation is more specific of the concrete back-end solution. Estimates for savings in the cost of direct disposal of spent fuel are presented for a Finnish case. The economics of recycle is reviewed from a recent study on the use of MOX fuel in the Finnish BWRs. The results from a comparison with once-through alternative show that spent fuel reprocessing with consequent recycle of uranium and plutonium would be economically justified only with very high uranium prices. (author)

  3. The near-term impacts of carbon mitigation policies on manufacturing industries

    International Nuclear Information System (INIS)

    Morgenstern, Richard D.; Ho Mun; Shih, J.-S.; Zhang Xuehua

    2004-01-01

    Who pays for new policies to reduce carbon dioxide and other greenhouse gas emissions in the United States? This paper considers a slice of the question by examining the near-term impact on domestic manufacturing industries of both upstream (economy-wide) and downstream (electric power industry only) carbon mitigation policies. Detailed Census data on the electricity use of four-digit manufacturing industries are combined with input-output information on inter-industry purchases to paint a detailed picture of carbon use, including effects on final demand. Regional information on electricity supply and use by region is also incorporated. A relatively simple model is developed which yields estimates of the relative burdens within the manufacturing sector of alternative carbon policies. Overall, the principal conclusion is that within the manufacturing sector (which by definition excludes coal production and electricity generation), only a small number of industries would bear a disproportionate short-term burden of a carbon tax or similar policy. Not surprisingly, an electricity-only policy affects very different manufacturing industries than an economy-wide carbon tax

  4. Phase I of the Near-Term Hybrid Passenger-Vehicle Development Program. Final report

    Energy Technology Data Exchange (ETDEWEB)

    1980-10-01

    Under contract to the Jet Propulsion Laboratory of the California Institute of Technology, Minicars conducted Phase I of the Near-Term Hybrid Passenger Vehicle (NTHV) Development Program. This program led to the preliminary design of a hybrid (electric and internal combustion engine powered) vehicle and fulfilled the objectives set by JPL. JPL requested that the report address certain specific topics. A brief summary of all Phase I activities is given initially; the hybrid vehicle preliminary design is described in Sections 4, 5, and 6. Table 2 of the Summary lists performance projections for the overall vehicle and some of its subsystems. Section 4.5 gives references to the more-detailed design information found in the Preliminary Design Data Package (Appendix C). Alternative hybrid-vehicle design options are discussed in Sections 3 through 6. A listing of the tradeoff study alternatives is included in Section 3. Computer simulations are discussed in Section 9. Section 8 describes the supporting economic analyses. Reliability and safety considerations are discussed specifically in Section 7 and are mentioned in Sections 4, 5, and 6. Section 10 lists conclusions and recommendations arrived at during the performance of Phase I. A complete bibliography follows the list of references.

  5. California Power-to-Gas and Power-to-Hydrogen Near-Term Business Case Evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Eichman, Josh [National Renewable Energy Lab. (NREL), Golden, CO (United States); Flores-Espino, Francisco [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-12-01

    Flexible operation of electrolysis systems represents an opportunity to reduce the cost of hydrogen for a variety of end-uses while also supporting grid operations and thereby enabling greater renewable penetration. California is an ideal location to realize that value on account of growing renewable capacity and markets for hydrogen as a fuel cell electric vehicle (FCEV) fuel, refineries, and other end-uses. Shifting the production of hydrogen to avoid high cost electricity and participation in utility and system operator markets along with installing renewable generation to avoid utility charges and increase revenue from the Low Carbon Fuel Standard (LCFS) program can result in around $2.5/kg (21%) reduction in the production and delivery cost of hydrogen from electrolysis. This reduction can be achieved without impacting the consumers of hydrogen. Additionally, future strategies for reducing hydrogen cost were explored and include lower cost of capital, participation in the Renewable Fuel Standard program, capital cost reduction, and increased LCFS value. Each must be achieved independently and could each contribute to further reductions. Using the assumptions in this study found a 29% reduction in cost if all future strategies are realized. Flexible hydrogen production can simultaneously improve the performance and decarbonize multiple energy sectors. The lessons learned from this study should be used to understand near-term cost drivers and to support longer-term research activities to further improve cost effectiveness of grid integrated electrolysis systems.

  6. Evaluation of the Terminal Precision Scheduling and Spacing System for Near-Term NAS Application

    Science.gov (United States)

    Thipphavong, Jane; Martin, Lynne Hazel; Swenson, Harry N.; Lin, Paul; Nguyen, Jimmy

    2012-01-01

    NASA has developed a capability for terminal area precision scheduling and spacing (TAPSS) to provide higher capacity and more efficiently manage arrivals during peak demand periods. This advanced technology is NASA's vision for the NextGen terminal metering capability. A set of human-in-the-loop experiments was conducted to evaluate the performance of the TAPSS system for near-term implementation. The experiments evaluated the TAPSS system under the current terminal routing infrastructure to validate operational feasibility. A second goal of the study was to measure the benefit of the Center and TRACON advisory tools to help prioritize the requirements for controller radar display enhancements. Simulation results indicate that using the TAPSS system provides benefits under current operations, supporting a 10% increase in airport throughput. Enhancements to Center decision support tools had limited impact on improving the efficiency of terminal operations, but did provide more fuel-efficient advisories to achieve scheduling conformance within 20 seconds. The TRACON controller decision support tools were found to provide the most benefit, by improving the precision in schedule conformance to within 20 seconds, reducing the number of arrivals having lateral path deviations by 50% and lowering subjective controller workload. Overall, the TAPSS system was found to successfully develop an achievable terminal arrival metering plan that was sustainable under heavy traffic demand levels and reduce the complexity of terminal operations when coupled with the use of the terminal controller advisory tools.

  7. Ceramic composites for near term reactor application - HTR2008-58050

    International Nuclear Information System (INIS)

    Snead, L. L.; Katoh, Y.; Windes, W. E.; Shinavski, R. J.; Burchell, T. D.

    2008-01-01

    Currently, two composites types are being developed for in-core application: carbon fiber carbon composite (CFC), and silicon carbide fiber composite (SiC/SiC.) Irradiation effects studies have been carried out over the past few decades yielding radiation-tolerant CFC's and a composite of SiC/SiC with no apparent degradation in mechanical properties to very high neutron exposure. While CFC's can be engineered with significantly higher thermal conductivity, and a slight advantage in manufacturability than SiC/SiC, they do have a neutron irradiation-limited lifetime. The SiC composite, while possessing lower thermal conductivity (especially following irradiation), appears to have mechanical properties insensitive to irradiation. Both materials are currently being produced to sizes much larger than that considered for nuclear application. In addition to materials aspects, results of programs focusing on practical aspects of deploying composites for near-term reactors will be discussed. In particular, significant progress has been made in the fabrication, testing, and qualification of composite gas-cooled reactor control rod sheaths and the ASTM standardization required for eventual qualification. (authors)

  8. Landmine policy in the near-term: a framework for technology analysis and action

    Energy Technology Data Exchange (ETDEWEB)

    Eimerl, D., LLNL

    1997-08-01

    Any effective solution to the problem of leftover landmines and other post-conflict unexploded ordnance (UXO) must take into account the real capabilities of demining technologies and the availability of sufficient resources to carry out demining operations. Economic and operational factors must be included in analyses of humanitarian demining. These factors will provide a framework for using currently available resources and technologies to complete this task in a time frame that is both practical and useful. Since it is likely that reliable advanced technologies for demining are still several years away, this construct applies to the intervening period. It may also provide a framework for utilizing advanced technologies as they become available. This study is an economic system model for demining operations carried out by the developed nations that clarifies the role and impact of technology on the economic performance and viability of these operations. It also provides a quantitative guide to assess the performance penalties arising from gaps in current technology, as well as the potential advantages and desirable features of new technologies that will significantly affect the international community`s ability to address this problem. Implications for current and near-term landmine and landmine technology policies are drawn.

  9. Three near term commercial markets in space and their potential role in space exploration

    Science.gov (United States)

    Gavert, Raymond B.

    2001-02-01

    Independent market studies related to Low Earth Orbit (LEO) commercialization have identified three near term markets that have return-on-investment potential. These markets are: (1) Entertainment (2) Education (3) Advertising/sponsorship. Commercial activity is presently underway focusing on these areas. A private company is working with the Russians on a commercial module attached to the ISS that will involve entertainment and probably the other two activities as well. A separate corporation has been established to commercialize the Russian Mir Space Station with entertainment and promotional advertising as important revenue sources. A new startup company has signed an agreement with NASA for commercial media activity on the International Space Station (ISS). Profit making education programs are being developed by a private firm to allow students to play the role of an astronaut and work closely with space scientists and astronauts. It is expected that the success of these efforts on the ISS program will extend to exploration missions beyond LEO. The objective of this paper is to extrapolate some of the LEO commercialization experiences to see what might be expected in space exploration missions to Mars, the Moon and beyond. .

  10. Isolation systems influence in the seismic loading propagation analysis applied to an innovative near term reactor

    International Nuclear Information System (INIS)

    Lo Frano, R.; Forasassi, G.

    2010-01-01

    Integrity of a Nuclear Power Plant (NPP) must be ensured during the plant life in any design condition and, particularly, in the event of a severe earthquake. To investigate the seismic resistance capability of as-built structures systems and components, in the event of a Safe Shutdown Earthquake (SSE), and analyse its related effects on a near term deployment reactor and its internals, a deterministic methodological approach, based on the evaluation of the propagation of seismic waves along the structure, was applied considering, also, the use of innovative anti-seismic techniques. In this paper the attention is focused on the use and influence of seismic isolation technologies (e.g. isolators based on passive energy dissipation) that seem able to ensure the full integrity and operability of NPP structures, to enhance the seismic safety (improving the design of new NPPs and if possible, to retrofit existing facilities) and to attain a standardization plant design. To the purpose of this study a numerical assessment of dynamic response/behaviour of the structures was accomplished by means of the finite element approach and setting up, as accurately as possible, a representative three-dimensional model of mentioned NPP structures. The obtained results in terms of response spectra (carried out from both cases of isolated and not isolated seismic analyses) are herein presented and compared in order to highlight the isolation technique effectiveness.

  11. Predicting Climate-sensitive Infectious Diseases: Development of a Federal Science Plan and the Path Forward

    Science.gov (United States)

    Trtanj, J.; Balbus, J. M.; Brown, C.; Shimamoto, M. M.

    2017-12-01

    The transmission and spread of infectious diseases, especially vector-borne diseases, water-borne diseases and zoonosis, are influenced by short and long-term climate factors, in conjunction with numerous other drivers. Public health interventions, including vaccination, vector control programs, and outreach campaigns could be made more effective if the geographic range and timing of increased disease risk could be more accurately targeted, and high risk areas and populations identified. While some progress has been made in predictive modeling for transmission of these diseases using climate and weather data as inputs, they often still start after the first case appears, the skill of those models remains limited, and their use by public health officials infrequent. And further, predictions with lead times of weeks, months or seasons are even rarer, yet the value of acting early holds the potential to save more lives, reduce cost and enhance both economic and national security. Information on high-risk populations and areas for infectious diseases is also potentially useful for the federal defense and intelligence communities as well. The US Global Change Research Program, through its Interagency Group on Climate Change and Human Health (CCHHG), has put together a science plan that pulls together federal scientists and programs working on predictive modeling of climate-sensitive diseases, and draws on academic and other partners. Through a series of webinars and an in-person workshop, the CCHHG has convened key federal and academic stakeholders to assess the current state of science and develop an integrated science plan to identify data and observation systems needs as well as a targeted research agenda for enhancing predictive modeling. This presentation will summarize the findings from this effort and engage AGU members on plans and next steps to improve predictive modeling for infectious diseases.

  12. Agricultural drought prediction using climate indices based on Support Vector Regression in Xiangjiang River basin.

    Science.gov (United States)

    Tian, Ye; Xu, Yue-Ping; Wang, Guoqing

    2018-05-01

    Drought can have a substantial impact on the ecosystem and agriculture of the affected region and does harm to local economy. This study aims to analyze the relation between soil moisture and drought and predict agricultural drought in Xiangjiang River basin. The agriculture droughts are presented with the Precipitation-Evapotranspiration Index (SPEI). The Support Vector Regression (SVR) model incorporating climate indices is developed to predict the agricultural droughts. Analysis of climate forcing including El Niño Southern Oscillation and western Pacific subtropical high (WPSH) are carried out to select climate indices. The results show that SPEI of six months time scales (SPEI-6) represents the soil moisture better than that of three and one month time scale on drought duration, severity and peaks. The key factor that influences the agriculture drought is the Ridge Point of WPSH, which mainly controls regional temperature. The SVR model incorporating climate indices, especially ridge point of WPSH, could improve the prediction accuracy compared to that solely using drought index by 4.4% in training and 5.1% in testing measured by Nash Sutcliffe efficiency coefficient (NSE) for three month lead time. The improvement is more significant for the prediction with one month lead (15.8% in training and 27.0% in testing) than that with three months lead time. However, it needs to be cautious in selection of the input parameters, since adding redundant information could have a counter effect in attaining a better prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Climate Prediction for Brazil's Nordeste: Performance of Empirical and Numerical Modeling Methods.

    Science.gov (United States)

    Moura, Antonio Divino; Hastenrath, Stefan

    2004-07-01

    Comparisons of performance of climate forecast methods require consistency in the predictand and a long common reference period. For Brazil's Nordeste, empirical methods developed at the University of Wisconsin use preseason (October January) rainfall and January indices of the fields of meridional wind component and sea surface temperature (SST) in the tropical Atlantic and the equatorial Pacific as input to stepwise multiple regression and neural networking. These are used to predict the March June rainfall at a network of 27 stations. An experiment at the International Research Institute for Climate Prediction, Columbia University, with a numerical model (ECHAM4.5) used global SST information through February to predict the March June rainfall at three grid points in the Nordeste. The predictands for the empirical and numerical model forecasts are correlated at +0.96, and the period common to the independent portion of record of the empirical prediction and the numerical modeling is 1968 99. Over this period, predicted versus observed rainfall are evaluated in terms of correlation, root-mean-square error, absolute error, and bias. Performance is high for both approaches. Numerical modeling produces a correlation of +0.68, moderate errors, and strong negative bias. For the empirical methods, errors and bias are small, and correlations of +0.73 and +0.82 are reached between predicted and observed rainfall.

  14. Prediction of thermal sensation in non-air-conditioned buildings in warm climates

    DEFF Research Database (Denmark)

    Fanger, Povl Ole; Toftum, Jørn

    2002-01-01

    The PMV model agrees well with high-quality field studies in buildings with HVAC systems, situated in cold, temperate and warm climates, studied during both summer and winter. In non-air-conditioned buildings in warm climates, occupants may sense the warmth as being less severe than the PMV...... predicts. The main reason is low expectations, but a metabolic rate that is estimated too high can also contribute to explaining the difference. An extension of the PMV model that includes an expectancy factor is introduced for use in non-air-conditioned buildings in warm climates. The extended PMV model...... agrees well with quality field studies in non-air-conditioned buildings of three continents....

  15. Model structures amplify uncertainty in predicted soil carbon responses to climate change.

    Science.gov (United States)

    Shi, Zheng; Crowell, Sean; Luo, Yiqi; Moore, Berrien

    2018-06-04

    Large model uncertainty in projected future soil carbon (C) dynamics has been well documented. However, our understanding of the sources of this uncertainty is limited. Here we quantify the uncertainties arising from model parameters, structures and their interactions, and how those uncertainties propagate through different models to projections of future soil carbon stocks. Both the vertically resolved model and the microbial explicit model project much greater uncertainties to climate change than the conventional soil C model, with both positive and negative C-climate feedbacks, whereas the conventional model consistently predicts positive soil C-climate feedback. Our findings suggest that diverse model structures are necessary to increase confidence in soil C projection. However, the larger uncertainty in the complex models also suggests that we need to strike a balance between model complexity and the need to include diverse model structures in order to forecast soil C dynamics with high confidence and low uncertainty.

  16. Tolerance and potential for adaptation of a Baltic Sea rockweed under predicted climate change conditions.

    Science.gov (United States)

    Rugiu, Luca; Manninen, Iita; Rothäusler, Eva; Jormalainen, Veijo

    2018-03-01

    Climate change is threating species' persistence worldwide. To predict species responses to climate change we need information not just on their environmental tolerance but also on its adaptive potential. We tested how the foundation species of rocky littoral habitats, Fucus vesiculosus, responds to combined hyposalinity and warming projected to the Baltic Sea by 2070-2099. We quantified responses of replicated populations originating from the entrance, central, and marginal Baltic regions. Using replicated individuals, we tested for the presence of within-population tolerance variation. Future conditions hampered growth and survival of the central and marginal populations whereas the entrance populations fared well. Further, both the among- and within-population variation in responses to climate change indicated existence of genetic variation in tolerance. Such standing genetic variation provides the raw material necessary for adaptation to a changing environment, which may eventually ensure the persistence of the species in the inner Baltic Sea. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Prediction of meningococcal meningitis epidemics in western Africa by using climate information

    Science.gov (United States)

    YAKA, D. P.; Sultan, B.; Tarbangdo, F.; Thiaw, W. M.

    2013-12-01

    The variations of certain climatic parameters and the degradation of ecosystems, can affect human's health by influencing the transmission, the spatiotemporal repartition and the intensity of infectious diseases. It is mainly the case of meningococcal meningitis (MCM) whose epidemics occur particularly in Sahelo-Soudanian climatic area of Western Africa under quite particular climatic conditions. Meningococcal Meningitis (MCM) is a contagious infection disease due to the bacteria Neisseria meningitis. MCM epidemics occur worldwide but the highest incidence is observed in the "meningitis belt" of sub-Saharan Africa, stretching from Senegal to Ethiopia. In spite of standards, strategies of prevention and control of MCS epidemic from World Health Organization (WHO) and States, African Sahelo-Soudanian countries remain frequently afflicted by disastrous epidemics. In fact, each year, during the dry season (February-April), 25 to 250 thousands of cases are observed. Children under 15 are particularly affected. Among favourable conditions for the resurgence and dispersion of the disease, climatic conditions may be important inducing seasonal fluctuations in disease incidence and contributing to explain the spatial pattern of the disease roughly circumscribed to the ecological Sahelo-Sudanian band. In this study, we tried to analyse the relationships between climatic factors, ecosystems degradation and MCM for a better understanding of MCM epidemic dynamic and their prediction. We have shown that MCM epidemics, whether at the regional, national or local level, occur in a specific period of the year, mainly from January to May characterised by a dry, hot and sandy weather. We have identified both in situ (meteorological synoptic stations) and satellitales climatic variables (NCEP reanalysis dataset) whose seasonal variability is dominating in MCM seasonal transmission. Statistical analysis have measured the links between seasonal variation of certain climatic parameters

  18. Predicting Impact of Climate Change on Water Temperature and Dissolved Oxygen in Tropical Rivers

    Directory of Open Access Journals (Sweden)

    Al-Amin Danladi Bello

    2017-07-01

    Full Text Available Predicting the impact of climate change and human activities on river systems is imperative for effective management of aquatic ecosystems. Unique information can be derived that is critical to the survival of aquatic species under dynamic environmental conditions. Therefore, the response of a tropical river system under climate and land-use changes from the aspects of water temperature and dissolved oxygen concentration were evaluated. Nine designed projected climate change scenarios and three future land-use scenarios were integrated into the Hydrological Simulation Program FORTRAN (HSPF model to determine the impact of climate change and land-use on water temperature and dissolved oxygen (DO concentration using basin-wide simulation of river system in Malaysia. The model performance coefficients showed a good correlation between simulated and observed streamflow, water temperature, and DO concentration in a monthly time step simulation. The Nash–Sutcliffe Efficiency for streamflow was 0.88 for the calibration period and 0.82 for validation period. For water temperature and DO concentration, data from three stations were calibrated and the Nash–Sutcliffe Efficiency for both water temperature and DO ranged from 0.53 to 0.70. The output of the calibrated model under climate change scenarios show that increased rainfall and air temperature do not affects DO concentration and water temperature as much as the condition of a decrease in rainfall and increase in air temperature. The regression model on changes in streamflow, DO concentration, and water temperature under the climate change scenarios illustrates that scenarios that produce high to moderate streamflow, produce small predicted change in water temperatures and DO concentrations compared with the scenarios that produced a low streamflow. It was observed that climate change slightly affects the relationship between water temperatures and DO concentrations in the tropical rivers that we

  19. National Scale Prediction of Soil Carbon Sequestration under Scenarios of Climate Change

    Science.gov (United States)

    Izaurralde, R. C.; Thomson, A. M.; Potter, S. R.; Atwood, J. D.; Williams, J. R.

    2006-12-01

    Carbon sequestration in agricultural soils is gaining momentum as a tool to mitigate the rate of increase of atmospheric CO2. Researchers from the Pacific Northwest National Laboratory, Texas A&M University, and USDA-NRCS used the EPIC model to develop national-scale predictions of soil carbon sequestration with adoption of no till (NT) under scenarios of climate change. In its current form, the EPIC model simulates soil C changes resulting from heterotrophic respiration and wind / water erosion. Representative modeling units were created to capture the climate, soil, and management variability at the 8-digit hydrologic unit (USGS classification) watershed scale. The soils selected represented at least 70% of the variability within each watershed. This resulted in 7,540 representative modeling units for 1,412 watersheds. Each watershed was assigned a major crop system: corn, soybean, spring wheat, winter wheat, cotton, hay, alfalfa, corn-soybean rotation or wheat-fallow rotation based on information from the National Resource Inventory. Each representative farm was simulated with conventional tillage and no tillage, and with and without irrigation. Climate change scenarios for two future periods (2015-2045 and 2045-2075) were selected from GCM model runs using the IPCC SRES scenarios of A2 and B2 from the UK Hadley Center (HadCM3) and US DOE PCM (PCM) models. Changes in mean and standard deviation of monthly temperature and precipitation were extracted from gridded files and applied to baseline climate (1960-1990) for each of the 1,412 modeled watersheds. Modeled crop yields were validated against historical USDA NASS county yields (1960-1990). The HadCM3 model predicted the most severe changes in climate parameters. Overall, there would be little difference between the A2 and B2 scenarios. Carbon offsets were calculated as the difference in soil C change between conventional and no till. Overall, C offsets during the first 30-y period (513 Tg C) are predicted to

  20. Climate drift of AMOC, North Atlantic salinity and arctic sea ice in CFSv2 decadal predictions

    Science.gov (United States)

    Huang, Bohua; Zhu, Jieshun; Marx, Lawrence; Wu, Xingren; Kumar, Arun; Hu, Zeng-Zhen; Balmaseda, Magdalena A.; Zhang, Shaoqing; Lu, Jian; Schneider, Edwin K.; Kinter, James L., III

    2015-01-01

    There are potential advantages to extending operational seasonal forecast models to predict decadal variability but major efforts are required to assess the model fidelity for this task. In this study, we examine the North Atlantic climate simulated by the NCEP Climate Forecast System, version 2 (CFSv2), using a set of ensemble decadal hindcasts and several 30-year simulations initialized from realistic ocean-atmosphere states. It is found that a substantial climate drift occurs in the first few years of the CFSv2 hindcasts, which represents a major systematic bias and may seriously affect the model's fidelity for decadal prediction. In particular, it is noted that a major reduction of the upper ocean salinity in the northern North Atlantic weakens the Atlantic meridional overturning circulation (AMOC) significantly. This freshening is likely caused by the excessive freshwater transport from the Arctic Ocean and weakened subtropical water transport by the North Atlantic Current. A potential source of the excessive freshwater is the quick melting of sea ice, which also causes unrealistically thin ice cover in the Arctic Ocean. Our sensitivity experiments with adjusted sea ice albedo parameters produce a sustainable ice cover with realistic thickness distribution. It also leads to a moderate increase of the AMOC strength. This study suggests that a realistic freshwater balance, including a proper sea ice feedback, is crucial for simulating the North Atlantic climate and its variability.

  1. On the importance of paleoclimate modelling for improving predictions of future climate change

    Directory of Open Access Journals (Sweden)

    J. C. Hargreaves

    2009-12-01

    Full Text Available We use an ensemble of runs from the MIROC3.2 AGCM with slab-ocean to explore the extent to which mid-Holocene simulations are relevant to predictions of future climate change. The results are compared with similar analyses for the Last Glacial Maximum (LGM and pre-industrial control climate. We suggest that the paleoclimate epochs can provide some independent validation of the models that is also relevant for future predictions. Considering the paleoclimate epochs, we find that the stronger global forcing and hence larger climate change at the LGM makes this likely to be the more powerful one for estimating the large-scale changes that are anticipated due to anthropogenic forcing. The phenomena in the mid-Holocene simulations which are most strongly correlated with future changes (i.e., the mid to high northern latitude land temperature and monsoon precipitation do, however, coincide with areas where the LGM results are not correlated with future changes, and these are also areas where the paleodata indicate significant climate changes have occurred. Thus, these regions and phenomena for the mid-Holocene may be useful for model improvement and validation.

  2. Sexual selection predicts advancement of avian spring migration in response to climate change

    DEFF Research Database (Denmark)

    Spottiswoode, Claire N; Tøttrup, Anders P; Coppack, Timothy

    2006-01-01

    Global warming has led to earlier spring arrival of migratory birds, but the extent of this advancement varies greatly among species, and it remains uncertain to what degree these changes are phenotypically plastic responses or microevolutionary adaptations to changing environmental conditions. We...... suggest that sexual selection could help to understand this variation, since early spring arrival of males is favoured by female choice. Climate change could weaken the strength of natural selection opposing sexual selection for early migration, which would predict greatest advancement in species...... in the timing of first-arriving individuals, suggesting that selection has not only acted on protandrous males. These results suggest that sexual selection may have an impact on the responses of organisms to climate change, and knowledge of a species' mating system might help to inform attempts at predicting...

  3. Uncertainty of climate change impacts and consequences on the prediction of future hydrological trends

    International Nuclear Information System (INIS)

    Minville, M.; Brissette, F.; Leconte, R.

    2008-01-01

    In the future, water is very likely to be the resource that will be most severely affected by climate change. It has been shown that small perturbations in precipitation frequency and/or quantity can result in significant impacts on the mean annual discharge. Moreover, modest changes in natural inflows result in larger changes in reservoir storage. There is however great uncertainty linked to changes in both the magnitude and direction of future hydrological trends. This presentation discusses the various sources of this uncertainty and their potential impact on the prediction of future hydrological trends. A companion paper will look at adaptation potential, taking into account some of the sources of uncertainty discussed in this presentation. Uncertainty is separated into two main components: climatic uncertainty and 'model and methods' uncertainty. Climatic uncertainty is linked to uncertainty in future greenhouse gas emission scenarios (GHGES) and to general circulation models (GCMs), whose representation of topography and climate processes is imperfect, in large part due to computational limitations. The uncertainty linked to natural variability (which may or may not increase) is also part of the climatic uncertainty. 'Model and methods' uncertainty regroups the uncertainty linked to the different approaches and models needed to transform climate data so that they can be used by hydrological models (such as downscaling methods) and the uncertainty of the models themselves and of their use in a changed climate. The impacts of the various sources of uncertainty on the hydrology of a watershed are demonstrated on the Peribonka River basin (Quebec, Canada). The results indicate that all sources of uncertainty can be important and outline the importance of taking these sources into account for any impact and adaptation studies. Recommendations are outlined for such studies. (author)

  4. Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations

    Science.gov (United States)

    Gerber, Brian D.; Kendall, William L.; Hooten, Mevin B.; Dubovsky, James A.; Drewien, Roderick C.

    2015-01-01

    Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (time-scales and spring/summer weather affects recruitment.Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression.Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring–summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect.Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond

  5. A review of wave climate and prediction along the Spanish Mediterranean coast

    Directory of Open Access Journals (Sweden)

    A. Sánchez-Arcilla

    2008-11-01

    Full Text Available This paper reviews the characterization of wave storms along the Spanish/Catalan Mediterranean coast. It considers the "physical" and "statistical" description of wave parameters and how they are affected by the prevailing meteo patterns and the sharp gradients in orography and bathymetry. The available field data and numerically simulated wave fields are discussed from this perspective. The resulting limits in accuracy and predictability are illustrated with specific examples. This allows deriving some conclusions for both short-term operational predictions and a long-term climatic assessment.

  6. Meeting the near-term demand for hydrogen using nuclear energy in competitive power markets

    International Nuclear Information System (INIS)

    Miller, Alistair I.; Duffey, Romney B.

    2004-01-01

    Hydrogen is becoming the reference fuel for future transportation and, in the USA in particular, a vision for its production from advanced nuclear reactors has been formulated. Fulfillment of this vision depend on its economics in 2020 or later. Prior to 2020, hydrogen needs to gain a substantial foothold without incurring excessive costs for the establishment of the distribution network for the new fuel. Water electrolysis and steam-methane reforming (SMR) are the existing hydrogen-production technologies, used for small-scale and large-scale production, respectively. Provided electricity is produced at costs expected for nuclear reactors of near-term design, electrolysis appears to offer superior economics when the SMR-related costs of distribution and sequestration (or an equivalent emission levy) are included. This is shown to hold at least until several percentage points of road transport have been converted to hydrogen. Electrolysis has large advantages over SMRs in being almost scale-independent and allowing local production. The key requirements for affordable electrolysis are low capital cost and relatively high utilization, although the paper shows that it should be advantageous to avoid the peaks of electricity demand and cost. The electricity source must enable high utilization as well as being itself low-cost and emissions-free. By using off-peak electricity, no extra costs for enhanced electricity distribution should occur. The longer-term supply of hydrogen may ultimately evolve away from low-temperature water electrolysis but it appears to be an excellent technology for early deployment and capable of supplying hydrogen at prices not dissimilar from today's costs for gasoline and diesel provided the vehicle's power unit is a fuel cell. (author)

  7. Preliminary seismic analysis of an innovative near term reactor: Methodology and application

    International Nuclear Information System (INIS)

    Lo Frano, R.; Pugliese, G.; Forasassi, G.

    2010-01-01

    Nuclear power plant (NPP) design is strictly dependent on seismic hazard and safety aspects concerned with the external events of the site. Earthquake resistant structures design requires realistic and accurate physical and theoretical models to describe the response of the nuclear power plants (NPPs) that depend on both the ground motion characteristics and the dynamic properties of the structures themselves. In order to improve the design of new NPPs and, at the same time, to retrofit existing ones the dynamic behaviour of structures subjected to critical seismic excitations that may occur during their expected service life must be evaluated. The aim of this work is to select new effective methods to assess NPPs vulnerability by properly capturing the effects of a safe shutdown earthquake (SSE) event on nuclear structures, like the near term deployment IRIS reactor, and to evaluate the seismic resistance capability of as-built structures systems and components. To attain the purpose a validated deterministic methodology based on an accurate finite element modelling coupled to substructure and time history approaches was employed for studying the overall dynamic behaviour of the NPP relevant components. Moreover the set up three-dimensional model was also validated to evaluate the performance and reliability of the adopted FEM code (mesh refinements and type element influence). This detailed numerical assessment, involving the most widely used finite element numerical codes (MSC.Marc and Ansys, allowed to solve, perform and simulate as accurately as possible the dynamic behaviour of structures which may withstand a lot of more or less complicate structural problems. To evaluate the accuracy and the reliability as well as to determine the related error of the set-up procedure, the obtained seismic analyses results in term of accelerations, propagated from the ground to the auxiliary building systems and components, and displacements were compared highlighting a

  8. Near-term viability of solar heat applications for the federal sector

    Science.gov (United States)

    Williams, T. A.

    1991-12-01

    Solar thermal technologies are capable of providing heat across a wide range of temperatures, making them potentially attractive for meeting energy requirements for industrial process heat applications and institutional heating. The energy savings that could be realized by solar thermal heat are quite large, potentially several quads annually. Although technologies for delivering heat at temperatures above 100 C currently exist within industry, only a fairly small number of commercial systems have been installed to date. The objective of this paper is to investigate and discuss the prospects for near term solar heat sales to federal facilities as a mechanism for providing an early market niche to the aid the widespread development and implementation of the technology. The specific technical focus is on mid-temperature (100 to 350 C) heat demands that could be met with parabolic trough systems. Federal facilities have several features relative to private industry that may make them attractive for solar heat applications relative to other sectors. Key features are specific policy mandates for conserving energy, a long term planning horizon with well defined decision criteria, and prescribed economic return criteria for conservation and solar investments that are generally less stringent than the investment criteria used by private industry. Federal facilities also have specific difficulties in the sale of solar heat technologies that are different from those of other sectors, and strategies to mitigate these difficulties will be important. For the baseline scenario developed in this paper, the solar heat application was economically competitive with heat provided by natural gas. The system levelized energy cost was $5.9/MBtu for the solar heat case, compared to $6.8/MBtu for the life cycle fuel cost of a natural gas case. A third-party ownership would also be attractive to federal users, since it would guarantee energy savings and would not need initial federal funds.

  9. Development of near-term batteries for electric vehicles. Summary report, October 1977-September 1979

    Energy Technology Data Exchange (ETDEWEB)

    Rajan, J.B. (comp.)

    1980-06-01

    The status and results through FY 1979 on the Near-Term Electric Vehicle Battery Project of the Argonne National Laboratory are summarized. This project conducts R and D on lead-acid, nickel/zinc and nickel/iron batteries with the objective of achieving commercialization in electric vehicles in the 1980's. Key results of the R and D indicate major technology advancements and achievement of most of FY 1979 performance goals. In the lead-acid system the specific energy was increased from less than 30 Wh/kg to over 40 Wh/kg at the C/3 rate; the peak power density improved from 70 W/kg to over 110 W/kg at the 50% state of charge; and over 200 deep-discharge cycle life demonstrated. In the nickel/iron system a specific energy of 48 Wh/kg was achieved; a peak power of about 100 W/kg demonstrated and a life of 36 cycles obtained. In the nickel/zinc system, specific energies of up to 64 Wh/kg were shown; peak powers of 133 W/kg obtained; and a life of up to 120 cycles measured. Future R and D will emphasize increased cycle life for nickel/zinc batteries and increased cycle life and specific energy for lead-acid and nickel/iron batteries. Testing of 145 cells was completed by NBTL. Cell evaluation included a full set of performance tests plus the application of a simulated power profile equivalent to the power demands of an electric vehicle in stop-start urban driving. Simplified test profiles which approximate electric vehicle demands are also described.

  10. Advanced wind turbine near-term product development. Final technical report

    Energy Technology Data Exchange (ETDEWEB)

    None

    1996-01-01

    In 1990 the US Department of Energy initiated the Advanced Wind Turbine (AWT) Program to assist the growth of a viable wind energy industry in the US. This program, which has been managed through the National Renewable Energy Laboratory (NREL) in Golden, Colorado, has been divided into three phases: (1) conceptual design studies, (2) near-term product development, and (3) next-generation product development. The goals of the second phase were to bring into production wind turbines which would meet the cost goal of $0.05 kWh at a site with a mean (Rayleigh) windspeed of 5.8 m/s (13 mph) and a vertical wind shear exponent of 0.14. These machines were to allow a US-based industry to compete domestically with other sources of energy and to provide internationally competitive products. Information is given in the report on design values of peak loads and of fatigue spectra and the results of the design process are summarized in a table. Measured response is compared with the results from mathematical modeling using the ADAMS code and is discussed. Detailed information is presented on the estimated costs of maintenance and on spare parts requirements. A failure modes and effects analysis was carried out and resulted in approximately 50 design changes including the identification of ten previously unidentified failure modes. The performance results of both prototypes are examined and adjusted for air density and for correlation between the anemometer site and the turbine location. The anticipated energy production at the reference site specified by NREL is used to calculate the final cost of energy using the formulas indicated in the Statement of Work. The value obtained is $0.0514/kWh in January 1994 dollars. 71 figs., 30 tabs.

  11. An Examination of Selected Datacom Options for the Near-Term Implementation of Trajectory Based Operations

    Science.gov (United States)

    Johnson, Walter W.; Lachter, Joel B.; Battiste, Vernol; Lim, Veranika; Brandt, Summer L.; Koteskey, Robert W.; Dao, Arik-Quang V.; Ligda, Sarah V.; Wu, Shu-Chieh

    2011-01-01

    A primary feature of the Next Generation Air Transportation System (NextGen) is trajectory based operations (TBO). Under TBO, aircraft flight plans are known to computer systems on the ground that aid in scheduling and separation. The Future Air Navigation System (FANS) was developed to support TBO, but relatively few aircraft in the US are FANSequipped. Thus, any near-term implementation must provide TBO procedures for non-FANS aircraft. Previous research has explored controller clearances, but any implementation must also provide procedures for aircraft requests. The work presented here aims to surface issues surrounding TBO communication procedures for non-FANS aircraft and for aircraft requesting deviations around weather. Three types of communication were explored: Voice, FANS, and ACARS,(Aircraft Communications Addressing and Reporting System). ACARS and FANS are datacom systems that differ in that FANS allows uplinked flight plans to be loaded into the Flight Management System (FMS), while ACARS delivers flight plans as text that must be entered manually via the Control Display Unit (CDU). Sixteen pilots (eight two-person flight decks) and four controllers participated in 32 20-minute scenarios that required the flight decks to navigate through convective weather as they approached their top of descents (TODs). Findings: The rate of non-conformance was higher than anticipated, with aircraft off path more than 20% of the time. Controllers did not differentiate between the ACARS and FANS datacom, and were mixed in their preference for Voice vs. datacom (ACARS and FANS). Pilots uniformly preferred Voice to datacom, particularly ACARS. Much of their dislike appears to result from the slow response times in the datacom conditions. As a result, participants frequently resorted to voice communication. These results imply that, before implementing TBO in environments where pilots make weather deviation requests, further research is needed to develop communication

  12. Evolution of near term PBMR steam and cogeneration applications - HTR2008-58219

    International Nuclear Information System (INIS)

    Kuhr, R. W.; Hannink, R.; Paul, K.; Kriel, W.; Greyvenstein, R.; Young, R.

    2008-01-01

    US and international applications for large onsite cogeneration (steam and power) systems are emerging as a near term market for the PBMR. The South African PBMR demonstration project applies a high temperature (900 deg. C) Brayton cycle for high efficiency power generation. In addition, a number of new applications are being investigated using an intermediate temperature range (700-750 deg. C) with a simplified heat supply system design. This intermediate helium delivery temperature supports conventional steam Rankine cycle designs at higher efficiencies than obtained from water type reactor systems. These designs can be adapted for cogeneration of steam, similar to the design of gas turbine cogeneration plants that supply steam and power at many industrial sites. This temperature range allows use of conventional or readily qualifiable materials and equipment, avoiding some cost premiums associated with more difficult operating conditions. As gas prices and CO 2 values increase, the potential value of a small nuclear reactor with advanced safety characteristics increases dramatically. Because of its smaller scale, the 400-500 MWt PBMR offers the economic advantages of onsite thermal integration (steam, hot water and desalination co-production) and of providing onsite power at cost versus at retail industrial rates avoiding transmission and distribution costs. Advanced safety characteristics of the PBMR support the location of plants adjacent to steam users, district energy systems, desalination plants, and other large commercial and industrial facilities. Additional benefits include price stability, long term security of energy supply and substantial CO 2 reductions. Target markets include existing sites using gas fired boilers and cogeneration units, new projects such as refinery and petrochemical expansions, and coal-to-liquids projects where steam and power represent major burdens on fuel use and CO 2 emissions. Lead times associated with the nuclear licensing

  13. Ecological and biomedical effects of effluents from near-term electric vehicle storage battery cycles

    Energy Technology Data Exchange (ETDEWEB)

    1980-05-01

    An assessment of the ecological and biomedical effects due to commercialization of storage batteries for electric and hybrid vehicles is given. It deals only with the near-term batteries, namely Pb/acid, Ni/Zn, and Ni/Fe, but the complete battery cycle is considered, i.e., mining and milling of raw materials, manufacture of the batteries, cases and covers; use of the batteries in electric vehicles, including the charge-discharge cycles; recycling of spent batteries; and disposal of nonrecyclable components. The gaseous, liquid, and solid emissions from various phases of the battery cycle are identified. The effluent dispersal in the environment is modeled and ecological effects are assessed in terms of biogeochemical cycles. The metabolic and toxic responses by humans and laboratory animals to constituents of the effluents are discussed. Pertinent environmental and health regulations related to the battery industry are summarized and regulatory implications for large-scale storage battery commercialization are discussed. Each of the seven sections were abstracted and indexed individually for EDB/ERA. Additional information is presented in the seven appendixes entitled; growth rate scenario for lead/acid battery development; changes in battery composition during discharge; dispersion of stack and fugitive emissions from battery-related operations; methodology for estimating population exposure to total suspended particulates and SO/sub 2/ resulting from central power station emissions for the daily battery charging demand of 10,000 electric vehicles; determination of As air emissions from Zn smelting; health effects: research related to EV battery technologies. (JGB)

  14. The solenoidal transport option: IFE drivers, near term research facilities, and beam dynamics

    International Nuclear Information System (INIS)

    Lee, E.P.; Briggs, R.J.

    1997-09-01

    Solenoidal magnets have been used as the beam transport system in all the high current electron induction accelerators that have been built in the past several decades. They have also been considered for the front end transport system for heavy ion accelerators for Inertial Fusion Energy (IFE) drivers, but this option has received very little attention in recent years. The analysis reported here was stimulated mainly by the recent effort to define an affordable open-quotes Integrated Research Experimentclose quotes (IRE) that can meet the near term needs of the IFE program. The 1996 FESAC IFE review panel agreed that an integrated experiment is needed to fully resolve IFE heavy ion driver science and technology issues; specifically, open-quotes the basic beam dynamics issues in the accelerator, the final focusing and transport issues in a reactor-relevant beam parameter regime, and the target heating phenomenologyclose quotes. The development of concepts that can meet these technical objectives and still stay within the severe cost constraints all new fusion proposals will encounter is a formidable challenge. Solenoidal transport has a very favorable scaling as the particle mass is decreased (the main reason why it is preferred for electrons in the region below 50 MeV). This was recognized in a recent conceptual study of high intensity induction linac-based proton accelerators for Accelerator Driven Transmutation Technologies, where solenoidal transport was chosen for the front end. Reducing the ion mass is an obvious scaling to exploit in an IRE design, since the output beam voltage will necessarily be much lower than that of a full scale driver, so solenoids should certainly be considered as one option for this experiment as well

  15. Developing an Onboard Traffic-Aware Flight Optimization Capability for Near-Term Low-Cost Implementation

    Science.gov (United States)

    Wing, David J.; Ballin, Mark G.; Koczo, Stefan, Jr.; Vivona, Robert A.; Henderson, Jeffrey M.

    2013-01-01

    The concept of Traffic Aware Strategic Aircrew Requests (TASAR) combines Automatic Dependent Surveillance Broadcast (ADS-B) IN and airborne automation to enable user-optimal in-flight trajectory replanning and to increase the likelihood of Air Traffic Control (ATC) approval for the resulting trajectory change request. TASAR is designed as a near-term application to improve flight efficiency or other user-desired attributes of the flight while not impacting and potentially benefiting ATC. Previous work has indicated the potential for significant benefits for each TASAR-equipped aircraft. This paper will discuss the approach to minimizing TASAR's cost for implementation and accelerating readiness for near-term implementation.

  16. Options for near-term phaseout of CO(2) emissions from coal use in the United States.

    Science.gov (United States)

    Kharecha, Pushker A; Kutscher, Charles F; Hansen, James E; Mazria, Edward

    2010-06-01

    The global climate problem becomes tractable if CO(2) emissions from coal use are phased out rapidly and emissions from unconventional fossil fuels (e.g., oil shale and tar sands) are prohibited. This paper outlines technology options for phasing out coal emissions in the United States by approximately 2030. We focus on coal for physical and practical reasons and on the U.S. because it is most responsible for accumulated fossil fuel CO(2) in the atmosphere today, specifically targeting electricity production, which is the primary use of coal. While we recognize that coal emissions must be phased out globally, we believe U.S. leadership is essential. A major challenge for reducing U.S. emissions is that coal provides the largest proportion of base load power, i.e., power satisfying minimum electricity demand. Because this demand is relatively constant and coal has a high carbon intensity, utility carbon emissions are largely due to coal. The current U.S. electric grid incorporates little renewable power, most of which is not base load power. However, this can readily be changed within the next 2-3 decades. Eliminating coal emissions also requires improved efficiency, a "smart grid", additional energy storage, and advanced nuclear power. Any further coal usage must be accompanied by carbon capture and storage (CCS). We suggest that near-term emphasis should be on efficiency measures and substitution of coal-fired power by renewables and third-generation nuclear plants, since these technologies have been successfully demonstrated at the relevant (commercial) scale. Beyond 2030, these measures can be supplemented by CCS at power plants and, as needed, successfully demonstrated fourth-generation reactors. We conclude that U.S. coal emissions could be phased out by 2030 using existing technologies or ones that could be commercially competitive with coal within about a decade. Elimination of fossil fuel subsidies and a substantial rising price on carbon emissions are the

  17. Spin, Unit Climate, and Aggression: Near Term, Long Term, and Reciprocal Predictors of Violence Among Workers in Military Settings

    Science.gov (United States)

    2017-08-01

    bullying, harassment, intimate partner violence) as well as physical health and mental health outcomes often associated with exposure to aggression (e.g... physical aggression, witnessing aggression in the workplace can have negative consequences for unit performance, physical health , and mental health . An...constructs (e.g., physical assault, verbal aggression, anger / rage, bullying, harassment, intimate partner violence) as well as physical health and

  18. Spin, Unit Climate, and Aggression: Near Term, Long Term, and Reciprocal Predictors of Violence Among Workers in Military Settings

    Science.gov (United States)

    2016-08-01

    in our posts, advertisements, etc. The second plan of action involves purchasing advertising through news sites serving specific military...earmarked for providing “thank you” gifts to participants, the delay resulted in shifting a substantial amount of spending from Year 2 to Year 3

  19. Can phenological models predict tree phenology accurately under climate change conditions?

    Science.gov (United States)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2014-05-01

    The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

  20. Psychosocial safety climate moderates the job demand-resource interaction in predicting workgroup distress.

    Science.gov (United States)

    Dollard, Maureen F; Tuckey, Michelle R; Dormann, Christian

    2012-03-01

    Psychosocial safety climate (PSC) arises from workplace policies, practices, and procedures for the protection of worker psychological health and safety that are largely driven by management. Many work stress theories are based on the fundamental interaction hypothesis - that a high level of job demands (D) will lead to psychological distress and that this relationship will be offset when there are high job resources (R). However we proposed that this interaction really depends on the organizational context; in particular high levels of psychosocial safety climate will enable the safe utilization of resources to reduce demands. The study sample consisted of police constables from 23 police units (stations) with longitudinal survey responses at two time points separated by 14 months (Time 1, N=319, Time 2, N=139). We used hierarchical linear modeling to assess the effect of the proposed three-way interaction term (PSC×D×R) on change in workgroup distress variance over time. Specifically we confirmed the interaction between emotional demands and emotional resources (assessed at the individual level), in the context of unit psychosocial safety climate (aggregated individual data). As predicted, high emotional resources moderated the positive relationship between emotional demands and change in workgroup distress but only when there were high levels of unit psychosocial safety climate. Results were confirmed using a split-sample analysis. Results support psychosocial safety climate as a property of the organization and a target for higher order controls for reducing work stress. The 'right' climate enables resources to do their job. Copyright © 2011 Elsevier Ltd. All rights reserved.

  1. Net root growth and nutrient acquisition in response to predicted climate change in two contrasting heathland species

    DEFF Research Database (Denmark)

    Arndal, M.F.; Merrild, M.P.; Michelsen, A.

    2013-01-01

    Accurate predictions of nutrient acquisition by plant roots and mycorrhizas are critical in modelling plant responses to climate change.We conducted a field experiment with the aim to investigate root nutrient uptake in a future climate and studied root production by ingrowth cores, mycorrhizal...... to elevated CO2. The species-specific response to the treatments suggests different sensitivity to global change factors, which could result in changed plant competitive interactions and belowground nutrient pool sizes in response to future climate change....

  2. Evaluation of a new CNRM-CM6 model version for seasonal climate predictions

    Science.gov (United States)

    Volpi, Danila; Ardilouze, Constantin; Batté, Lauriane; Dorel, Laurant; Guérémy, Jean-François; Déqué, Michel

    2017-04-01

    This work presents the quality assessment of a new version of the Météo-France coupled climate prediction system, which has been developed in the EU COPERNICUS Climate Change Services framework to carry out seasonal forecast. The system is based on the CNRM-CM6 model, with Arpege-Surfex 6.2.2 as atmosphere/land component and Nemo 3.2 as ocean component, which has directly embedded the sea-ice component Gelato 6.0. In order to have a robust diagnostic, the experiment is composed by 60 ensemble members generated with stochastic dynamic perturbations. The experiment has been performed over a 37-year re-forecast period from 1979 to 2015, with two start dates per year, respectively in May 1st and November 1st. The evaluation of the predictive skill of the model is shown under two perspectives: on the one hand, the ability of the model to faithfully respond to positive or negative ENSO, NAO and QBO events, independently of the predictability of these events. Such assessment is carried out through a composite analysis, and shows that the model succeeds in reproducing the main patterns for 2-meter temperature, precipitation and geopotential height at 500 hPa during the winter season. On the other hand, the model predictive skill of the same events (positive and negative ENSO, NAO and QBO) is evaluated.

  3. Generating temporal model using climate variables for the prediction of dengue cases in Subang Jaya, Malaysia

    Science.gov (United States)

    Dom, Nazri Che; Hassan, A Abu; Latif, Z Abd; Ismail, Rodziah

    2013-01-01

    Objective To develop a forecasting model for the incidence of dengue cases in Subang Jaya using time series analysis. Methods The model was performed using the Autoregressive Integrated Moving Average (ARIMA) based on data collected from 2005 to 2010. The fitted model was then used to predict dengue incidence for the year 2010 by extrapolating dengue patterns using three different approaches (i.e. 52, 13 and 4 weeks ahead). Finally cross correlation between dengue incidence and climate variable was computed over a range of lags in order to identify significant variables to be included as external regressor. Results The result of this study revealed that the ARIMA (2,0,0) (0,0,1)52 model developed, closely described the trends of dengue incidence and confirmed the existence of dengue fever cases in Subang Jaya for the year 2005 to 2010. The prediction per period of 4 weeks ahead for ARIMA (2,0,0)(0,0,1)52 was found to be best fit and consistent with the observed dengue incidence based on the training data from 2005 to 2010 (Root Mean Square Error=0.61). The predictive power of ARIMA (2,0,0) (0,0,1)52 is enhanced by the inclusion of climate variables as external regressor to forecast the dengue cases for the year 2010. Conclusions The ARIMA model with weekly variation is a useful tool for disease control and prevention program as it is able to effectively predict the number of dengue cases in Malaysia.

  4. Regulating emission of air pollutants for near-term relief from global warming

    Science.gov (United States)

    Ramanathan, V.; Xu, Y.

    2011-12-01

    The manmade greenhouse gases that are now blanketing the planet is thick enough to warm the system beyond the 20C threshold. Even with a targeted reduction in CO2 emission of 50% by 2050, we will still be adding more than 50 ppm of CO2 and add another 10C to the warming. Fortunately, there are still ways to contain the warming by reducing non-CO2 climate warmers (methane, lower atmosphere ozone, black carbon and HFCs), using available and field tested technologies. The major advantage of going for these 'low-hanging fruits' is that this approach will clean up the air and improve health and food security of south and east Asia, thus engaging developing nations more effectively in climate negotiations. These non-CO2 mitigation actions will have significant (beneficial) impacts on the chemistry, clouds and precipitation of the atmosphere and these have to be quantified adequately. For example, reducing black and organic carbon emissions (through cleaner cooking technologies in developing countries) will also lead to significant reductions in carbon monoxide, which is an ozone precursor. The institutional infrastructure for reducing non-CO2 climate warmers already exist and have a proven track record for successful climate mitigation.

  5. Climate services for health: predicting the evolution of the 2016 dengue season in Machala, Ecuador.

    Science.gov (United States)

    Lowe, Rachel; Stewart-Ibarra, Anna M; Petrova, Desislava; García-Díez, Markel; Borbor-Cordova, Mercy J; Mejía, Raúl; Regato, Mary; Rodó, Xavier

    2017-07-01

    El Niño and its effect on local meteorological conditions potentially influences interannual variability in dengue transmission in southern coastal Ecuador. El Oro province is a key dengue surveillance site, due to the high burden of dengue, seasonal transmission, co-circulation of all four dengue serotypes, and the recent introduction of chikungunya and Zika. In this study, we used climate forecasts to predict the evolution of the 2016 dengue season in the city of Machala, following one of the strongest El Niño events on record. We incorporated precipitation, minimum temperature, and Niño3·4 index forecasts in a Bayesian hierarchical mixed model to predict dengue incidence. The model was initiated on Jan 1, 2016, producing monthly dengue forecasts until November, 2016. We accounted for misreporting of dengue due to the introduction of chikungunya in 2015, by using active surveillance data to correct reported dengue case data from passive surveillance records. We then evaluated the forecast retrospectively with available epidemiological information. The predictions correctly forecast an early peak in dengue incidence in March, 2016, with a 90% chance of exceeding the mean dengue incidence for the previous 5 years. Accounting for the proportion of chikungunya cases that had been incorrectly recorded as dengue in 2015 improved the prediction of the magnitude of dengue incidence in 2016. This dengue prediction framework, which uses seasonal climate and El Niño forecasts, allows a prediction to be made at the start of the year for the entire dengue season. Combining active surveillance data with routine dengue reports improved not only model fit and performance, but also the accuracy of benchmark estimates based on historical seasonal averages. This study advances the state-of-the-art of climate services for the health sector, by showing the potential value of incorporating climate information in the public health decision-making process in Ecuador. European Union

  6. Near-term markets for PEM fuel cell power modules: industrial vehicles and hydrogen recovery

    International Nuclear Information System (INIS)

    Chintawar, P.S.; Block, G.

    2004-01-01

    'Full text:' Nuvera Fuel Cells, Inc. is a global leader in the development and advancement of multifuel processing and fuel cell technology. With offices located in Italy and the USA, Nuvera is committed to advancing the commercialization of hydrogen fuel cell power modules for industrial vehicles and equipment and stationary applications by 2006, natural gas fuel cell power systems for cogeneration applications by 2007, and on-board gasoline fuel processors and fuel cell stacks for automotive applications by 2010. Nuvera Fuel Cells Europe is ISO 9001:2000 certified for 'Research, Development, Design, Production and Servicing of Fuel Cell Stacks and Fuel Cell Systems.' In the chemical industry, one of the largest operating expenses today is the cost of electricity. For example, caustic soda and chlorine are produced today using industrial membrane electrolysis which is an energy intensive process. Production of 1 metric ton of caustic soda consumes 2.5 MWh of energy. However, about 20% of the electricity consumed can be recovered by converting the hydrogen byproduct of the caustic soda production process into electricity via PEM fuel cells. The accessible market is a function of the economic value of the hydrogen whether flared, used as fuel, or as chemical. Responding to this market need, we are currently developing large hydrogen fuel cell power modules 'Forza' that use excess hydrogen to produce electricity, representing a practical economic alternative to reducing the net electricity cost. Due for commercial launch in 2006, Forza is a low-pressure, steady state, base-load power generation solution that will operate at high efficiency and 100% capacity over a 24-hour period. We believe this premise is also true for chemical and electrochemical plants and companies that convert hydrogen to electricity using renewable sources like windmills or hydropower. The second near-term market that Nuvera is developing utilizes a 5.5 kW hydrogen fueled power module 'H 2 e

  7. Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa.

    Science.gov (United States)

    Redding, David W; Tiedt, Sonia; Lo Iacono, Gianni; Bett, Bernard; Jones, Kate E

    2017-07-19

    Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'. © 2017 The Authors.

  8. Regional climate model downscaling may improve the prediction of alien plant species distributions

    Science.gov (United States)

    Liu, Shuyan; Liang, Xin-Zhong; Gao, Wei; Stohlgren, Thomas J.

    2014-12-01

    Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990-1999) to the future (2046-2055). RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa ( Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.

  9. Predicting High School Student Use of Learning Strategies: The Role of Preferred Learning Styles and Classroom Climate

    Science.gov (United States)

    Cheema, Jehanzeb; Kitsantas, Anastasia

    2016-01-01

    This study investigated the predictiveness of preferred learning styles (competitive and cooperative) and classroom climate (teacher support and disciplinary climate) on learning strategy use in mathematics. The student survey part of the Programme for International Student Assessment 2003 comprising of 4633 US observations was used in a weighted…

  10. Predicting summer residential electricity demand across the U.S.A using climate information

    Science.gov (United States)

    Sun, X.; Wang, S.; Lall, U.

    2017-12-01

    We developed a Bayesian Hierarchical model to predict monthly residential per capita electricity consumption at the state level across the USA using climate information. The summer period was selected since cooling requirements may be directly associated with electricity use, while for winter a mix of energy sources may be used to meet heating needs. Historical monthly electricity consumption data from 1990 to 2013 were used to build a predictive model with a set of corresponding climate and non-climate covariates. A clustering analysis was performed first to identify groups of states that had similar temporal patterns for the cooling degree days of each state. Then, a partial pooling model was applied to each cluster to assess the sensitivity of monthly per capita residential electricity demand to each predictor (including cooling-degree-days, gross domestic product (GDP) per capita, per capita electricity demand of previous month and previous year, and the residential electricity price). The sensitivity of residential electricity to cooling-degree-days has an identifiable geographic distribution with higher values in northeastern United States.

  11. Should we assess climate model predictions in light of severe tests?

    Science.gov (United States)

    Katzav, Joel

    2011-06-01

    According to Austro-British philosopher Karl Popper, a system of theoretical claims is scientific only if it is methodologically falsifiable, i.e., only if systematic attempts to falsify or severely test the system are being carried out [Popper, 2005, pp. 20, 62]. He holds that a test of a theoretical system is severe if and only if it is a test of the applicability of the system to a case in which the system's failure is likely in light of background knowledge, i.e., in light of scientific assumptions other than those of the system being tested [Popper, 2002, p. 150]. Popper counts the 1919 tests of general relativity's then unlikely predictions of the deflection of light in the Sun's gravitational field as severe. An implication of Popper's above condition for being a scientific theoretical system is the injunction to assess theoretical systems in light of how well they have withstood severe testing. Applying this injunction to assessing the quality of climate model predictions (CMPs), including climate model projections, would involve assigning a quality to each CMP as a function of how well it has withstood severe tests allowed by its implications for past, present, and nearfuture climate or, alternatively, as a function of how well the models that generated the CMP have withstood severe tests of their suitability for generating the CMP.

  12. Predicting Plant-Accessible Water in the Critical Zone: Mountain Ecosystems in a Mediterranean Climate

    Science.gov (United States)

    Klos, P. Z.; Goulden, M.; Riebe, C. S.; Tague, C.; O'Geen, A. T.; Flinchum, B. A.; Safeeq, M.; Conklin, M. H.; Hart, S. C.; Asefaw Berhe, A.; Hartsough, P. C.; Holbrook, S.; Bales, R. C.

    2017-12-01

    Enhanced understanding of subsurface water storage, and the below-ground architecture and processes that create it, will advance our ability to predict how the impacts of climate change - including drought, forest mortality, wildland fire, and strained water security - will take form in the decades to come. Previous research has examined the importance of plant-accessible water in soil, but in upland landscapes within Mediterranean climates the soil is often only the upper extent of subsurface water storage. We draw insights from both this previous research and a case study of the Southern Sierra Critical Zone Observatory to: define attributes of subsurface storage, review observed patterns in its distribution, highlight nested methods for its estimation across scales, and showcase the fundamental processes controlling its formation. We observe that forest ecosystems at our sites subsist on lasting plant-accessible stores of subsurface water during the summer dry period and during multi-year droughts. This indicates that trees in these forest ecosystems are rooted deeply in the weathered, highly porous saprolite, which reaches up to 10-20 m beneath the surface. This confirms the importance of large volumes of subsurface water in supporting ecosystem resistance to climate and landscape change across a range of spatiotemporal scales. This research enhances the ability to predict the extent of deep subsurface storage across landscapes; aiding in the advancement of both critical zone science and the management of natural resources emanating from similar mountain ecosystems worldwide.

  13. Fire behavior potential in central Saskatchewan under predicted climate change : summary document

    International Nuclear Information System (INIS)

    Parisien, M.; Hirsch, K.; Todd, B.; Flannigan, M.; Kafka, V.; Flynn, N.

    2005-01-01

    This study assesses fire danger and fire behaviour potential in central Saskatchewan using simulated climate scenarios produced by the Canadian Regional Climate Model (CRCM), including scenario analysis of base, double and triple level carbon dioxide in the atmosphere and uses available forest fuels to develop an absolute measure of fire behaviour. For each of these climate scenarios, the CRCM-generated weather was used as input variables into the Canadian Forest Fire Behavior Prediction (FBP) System. Fire behavior potential was quantified using head fire intensity, a measure of the fire's energy output because it can be related to fire behavior characteristics, suppression effectiveness, and fire effects. The report discusses the implications of fire behavior potential changes for fire and forest management. Preliminary results suggest a large increase in area burned in the study area by the end of the twenty-first century. Some of the possible fire management activities for long-term prediction include: pre-positioning of resources, preparedness planning, prioritization of fire and forest management activities and fire threat evaluation. 16 refs., 1 tab, 7 figs

  14. Climate Prediction Center (CPC) 8 to 14 Day Probabilistic Precipitation Outlook for the Contiguous United States and Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) issues 8 to 14 day probabilistic precipitation outlooks for the United States. The 8-14 day Outlook gives the confidence that a...

  15. Climate Prediction Center (CPC) 6 to 10 Day Probabilistic Precipitation Outlook for the Contiguous United States and Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) issues 6 to 10 day probabilistic precipitation outlooks for the United States. The 6-10 day Outlook gives the confidence that a...

  16. Climate Prediction Center(CPC) Monthly Precipitation Reconstruction (PREC)at Spatial Resolution of 0.5 degree.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This global monthly precipitation analysis is called the Climate Prediction Center (CPC) Precipitation Reconstruction (PREC). This analysis consists of two...

  17. Climate Prediction Center (CPC) Monthly Precipitation Reconstruction of Ocean(PRECO)at Spatial Resolution of 2.5 degree.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This global monthly precipitation analysis is called the Climate Prediction Center (CPC) Precipitation Reconstruction (PREC). This analysis consists of two...

  18. Climate Prediction Center (CPC) 6 to 10 Day Probabilistic Temperature Outlook for the Contiguous United States and Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) issues 6 to 10 day probabilistic temperature outlooks for the United States. The 6-10 day Outlook gives the confidence that a...

  19. Climate Prediction Center (CPC) 8 to 14 Day Probabilistic Temperature Outlook for the Contiguous United States and Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) issues 8 to 14 day probabilistic temperature outlooks for the United States. The 8-14 day Outlook gives the confidence that a...

  20. Seasonal prediction and predictability of Eurasian spring snow water equivalent in NCEP Climate Forecast System version 2 reforecasts

    Science.gov (United States)

    He, Qiong; Zuo, Zhiyan; Zhang, Renhe; Zhang, Ruonan

    2018-01-01

    The spring snow water equivalent (SWE) over Eurasia plays an important role in East Asian and Indian monsoon rainfall. This study evaluates the seasonal prediction capability of NCEP Climate Forecast System version 2 (CFSv2) retrospective forecasts (1983-2010) for the Eurasian spring SWE. The results demonstrate that CFSv2 is able to represent the climatological distribution of the observed Eurasian spring SWE with a lead time of 1-3 months, with the maximum SWE occurring over western Siberia and Northeastern Europe. For a longer lead time, the SWE is exaggerated in CFSv2 because the start of snow ablation in CFSv2 lags behind that of the observation, and the simulated snowmelt rate is less than that in the observation. Generally, CFSv2 can simulate the interannual variations of the Eurasian spring SWE 1-5 months ahead of time but with an exaggerated magnitude. Additionally, the downtrend in CFSv2 is also overestimated. Because the initial conditions (ICs) are related to the corresponding simulation results significantly, the robust interannual variability and the downtrend in the ICs are most likely the causes for these biases. Moreover, CFSv2 exhibits a high potential predictability for the Eurasian spring SWE, especially the spring SWE over Siberia, with a lead time of 1-5 months. For forecasts with lead times longer than 5 months, the model predictability gradually decreases mainly due to the rapid decrease in the model signal.

  1. Seasonal streamflow prediction by a combined climate-hydrologic system for river basins of Taiwan

    Science.gov (United States)

    Kuo, Chun-Chao; Gan, Thian Yew; Yu, Pao-Shan

    2010-06-01

    SummaryA combined, climate-hydrologic system with three components to predict the streamflow of two river basins of Taiwan at one season (3-month) lead time for the NDJ and JFM seasons was developed. The first component consists of the wavelet-based, ANN-GA model (Artificial Neural Network calibrated by Genetic Algorithm) which predicts the seasonal rainfall by using selected sea surface temperature (SST) as predictors, given that SST are generally predictable by climate models up to 6-month lead time. For the second component, three disaggregation models, Valencia and Schaake (VS), Lane, and Canonical Random Cascade Model (CRCM), were tested to compare the accuracy of seasonal rainfall disaggregated by these three models to 3-day time scale rainfall data. The third component consists of the continuous rainfall-runoff model modified from HBV (called the MHBV) and calibrated by a global optimization algorithm against the observed rainfall and streamflow data of the Shihmen and Tsengwen river basins of Taiwan. The proposed system was tested, first by disaggregating the predicted seasonal rainfall of ANN-GA to rainfall of 3-day time step using the Lane model; then the disaggregated rainfall data was used to drive the calibrated MHBV to predict the streamflow for both river basins at 3-day time step up to a season's lead time. Overall, the streamflow predicted by this combined system for the NDJ season, which is better than that of the JFM season, will be useful for the seasonal planning and management of water resources of these two river basins of Taiwan.

  2. Predicting, deciding, learning: can one evaluate the 'success' of national climate scenarios?

    International Nuclear Information System (INIS)

    Hulme, Mike; Dessai, Suraje

    2008-01-01

    Scenarios may be understood as products and/or processes. Viewing scenario exercises as productive tends to emphasize their tangibility: scenario products may acquire value unrelated to the processes of their creation. Viewing scenario exercises as procedural tends to emphasize their modes of formation: the process of constructing scenarios may have benefits irrespective of the value of ensuing products. These two framings yield different expectations about how one might evaluate the 'success' or otherwise of scenario exercises. We illustrate three approaches to evaluating the success or otherwise of scenarios using the example of the series of national UK climate scenarios published between 1991 and 2002. These are: predictive success (has the future turned out as envisaged?), decision success (have 'good' decisions subsequently been made?) and learning success (have scenarios proved engaging and enabled learning?). We reflect on the different ways the 'success' of national climate scenarios might be evaluated and on the relationship between the productive and procedural dimensions of scenario exercises.

  3. [Effects of sampling plot number on tree species distribution prediction under climate change].

    Science.gov (United States)

    Liang, Yu; He, Hong-Shi; Wu, Zhi-Wei; Li, Xiao-Na; Luo, Xu

    2013-05-01

    Based on the neutral landscapes under different degrees of landscape fragmentation, this paper studied the effects of sampling plot number on the prediction of tree species distribution at landscape scale under climate change. The tree species distribution was predicted by the coupled modeling approach which linked an ecosystem process model with a forest landscape model, and three contingent scenarios and one reference scenario of sampling plot numbers were assumed. The differences between the three scenarios and the reference scenario under different degrees of landscape fragmentation were tested. The results indicated that the effects of sampling plot number on the prediction of tree species distribution depended on the tree species life history attributes. For the generalist species, the prediction of their distribution at landscape scale needed more plots. Except for the extreme specialist, landscape fragmentation degree also affected the effects of sampling plot number on the prediction. With the increase of simulation period, the effects of sampling plot number on the prediction of tree species distribution at landscape scale could be changed. For generalist species, more plots are needed for the long-term simulation.

  4. Prediction of Monthly Summer Monsoon Rainfall Using Global Climate Models Through Artificial Neural Network Technique

    Science.gov (United States)

    Nair, Archana; Singh, Gurjeet; Mohanty, U. C.

    2018-01-01

    The monthly prediction of summer monsoon rainfall is very challenging because of its complex and chaotic nature. In this study, a non-linear technique known as Artificial Neural Network (ANN) has been employed on the outputs of Global Climate Models (GCMs) to bring out the vagaries inherent in monthly rainfall prediction. The GCMs that are considered in the study are from the International Research Institute (IRI) (2-tier CCM3v6) and the National Centre for Environmental Prediction (Coupled-CFSv2). The ANN technique is applied on different ensemble members of the individual GCMs to obtain monthly scale prediction over India as a whole and over its spatial grid points. In the present study, a double-cross-validation and simple randomization technique was used to avoid the over-fitting during training process of the ANN model. The performance of the ANN-predicted rainfall from GCMs is judged by analysing the absolute error, box plots, percentile and difference in linear error in probability space. Results suggest that there is significant improvement in prediction skill of these GCMs after applying the ANN technique. The performance analysis reveals that the ANN model is able to capture the year to year variations in monsoon months with fairly good accuracy in extreme years as well. ANN model is also able to simulate the correct signs of rainfall anomalies over different spatial points of the Indian domain.

  5. Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

    Science.gov (United States)

    Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha C.; Thompson, Jill; Zimmerman, Jess K.; Murphy, Lora

    2018-01-01

    Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured inter-annual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including above-ground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.

  6. Seasonal Climate Predictability in a Coupled OAGCM Using a Different Approach for Ensemble Forecasts.

    Science.gov (United States)

    Luo, Jing-Jia; Masson, Sebastien; Behera, Swadhin; Shingu, Satoru; Yamagata, Toshio

    2005-11-01

    Predictabilities of tropical climate signals are investigated using a relatively high resolution Scale Interaction Experiment Frontier Research Center for Global Change (FRCGC) coupled GCM (SINTEX-F). Five ensemble forecast members are generated by perturbing the model’s coupling physics, which accounts for the uncertainties of both initial conditions and model physics. Because of the model’s good performance in simulating the climatology and ENSO in the tropical Pacific, a simple coupled SST-nudging scheme generates realistic thermocline and surface wind variations in the equatorial Pacific. Several westerly and easterly wind bursts in the western Pacific are also captured.Hindcast results for the period 1982 2001 show a high predictability of ENSO. All past El Niño and La Niña events, including the strongest 1997/98 warm episode, are successfully predicted with the anomaly correlation coefficient (ACC) skill scores above 0.7 at the 12-month lead time. The predicted signals of some particular events, however, become weak with a delay in the phase at mid and long lead times. This is found to be related to the intraseasonal wind bursts that are unpredicted beyond a few months of lead time. The model forecasts also show a “spring prediction barrier” similar to that in observations. Spatial SST anomalies, teleconnection, and global drought/flood during three different phases of ENSO are successfully predicted at 9 12-month lead times.In the tropical North Atlantic and southwestern Indian Ocean, where ENSO has predominant influences, the model shows skillful predictions at the 7 12-month lead times. The distinct signal of the Indian Ocean dipole (IOD) event in 1994 is predicted at the 6-month lead time. SST anomalies near the western coast of Australia are also predicted beyond the 12-month lead time because of pronounced decadal signals there.

  7. The Grand Challenges of WCRP and the Climate Observing System of the Future

    Science.gov (United States)

    Brasseur, G. P.

    2017-12-01

    The successful implementation the Paris agreement on climate change (COP21) calls for a well-designed global monitoring system of essential climate variables, climate processes and Earth system budgets. The Grand Challenges implemented by the World Climate Research Programme (WCRP) provide an opportunity to investigate issues of high societal relevance, directly related to sea level rise, droughts, floods, extreme heat events, food security, and fresh water availability. These challenges would directly benefit from a well-designed suite of systematic climate observations. Quantification of the evolution of the global energy, water and carbon budgets as well as the development and the production of near-term and regional climate predictions require that a comprehensive, focused, multi-platform observing system (satellites, ground-based and in situ observations) be established in an international context. This system must be accompanied by the development of climate services that should translate and disseminate scientific outcomes as actionable information for users and stakeholders.

  8. Betting and Belief: Modeling the Impact of Prediction Markets on Public Attribution of Climate Change

    Science.gov (United States)

    Gilligan, J. M.; Nay, J. J.; van der Linden, M.

    2016-12-01

    Despite overwhelming scientific evidence and an almost complete consensus among scientists, a large fraction of the American public is not convinced that global warming is anthropogenic. This doubt correlates strongly with political, ideological, and cultural orientation. [1] It has been proposed that people who do not trust climate scientists tend to trust markets, so prediction markets might be able to influence their beliefs about the causes of climate change. [2] We present results from an agent-based simulation of a prediction market in which traders invest based on their beliefs about what drives global temperature change (here, either CO2 concentration or total solar irradiance (TSI), which is a popular hypothesis among many who doubt the dominant role of CO2). At each time step, traders use historical and observed temperatures and projected future forcings (CO2 or TSI) to update Bayesian posterior probability distributions for future temperatures, conditional on their belief about what drives climate change. Traders then bet on future temperatures by trading in climate futures. Trading proceeds by a continuous double auction. Traders are randomly assigned initial beliefs about climate change, and they have some probability of changing their beliefs to match those of the most successful traders in their social network. We simulate two alternate realities in which the global temperature is controlled either by CO2 or by TSI, with stochastic noise. In both cases traders' beliefs converge, with a large majority reaching agreement on the actual cause of climate change. This convergence is robust, but the speed with which consensus emerges depends on characteristics of the traders' psychology and the structure of the market. Our model can serve as a test-bed for studying how beliefs might evolve under different market structures and different modes of decision-making and belief-change. We will report progress on studying alternate models of belief-change. This

  9. A robust empirical seasonal prediction of winter NAO and surface climate.

    Science.gov (United States)

    Wang, L; Ting, M; Kushner, P J

    2017-03-21

    A key determinant of winter weather and climate in Europe and North America is the North Atlantic Oscillation (NAO), the dominant mode of atmospheric variability in the Atlantic domain. Skilful seasonal forecasting of the surface climate in both Europe and North America is reflected largely in how accurately models can predict the NAO. Most dynamical models, however, have limited skill in seasonal forecasts of the winter NAO. A new empirical model is proposed for the seasonal forecast of the winter NAO that exhibits higher skill than current dynamical models. The empirical model provides robust and skilful prediction of the December-January-February (DJF) mean NAO index using a multiple linear regression (MLR) technique with autumn conditions of sea-ice concentration, stratospheric circulation, and sea-surface temperature. The predictability is, for the most part, derived from the relatively long persistence of sea ice in the autumn. The lower stratospheric circulation and sea-surface temperature appear to play more indirect roles through a series of feedbacks among systems driving NAO evolution. This MLR model also provides skilful seasonal outlooks of winter surface temperature and precipitation over many regions of Eurasia and eastern North America.

  10. Retention of knowledge and experience from experts in near-term operating plants

    International Nuclear Information System (INIS)

    Jiang, H.

    2007-01-01

    Full text: Tianwan Nuclear Power Station (TNPS) will be put into commercial operation in May, 2007. Right-sizing is on the way to adapt the organization to the new stage of TNPS. TNPS is facing challenges of dilution of expertise by the rightsizing. This condition is aggravated by the incipient training system and a very competitive fighting for attracting technical experts in nuclear area, because the very ambitious projects of nuclear plants which are thriving in China. This can lead to the compromise of the capability to safely and economically operate TNPS. Indubitably, a personnel training plays a very crucial role in knowledge management, especially for countries as China which are weak in professional education system. Key knowledge and skills for safely and reliably operating nuclear power plants can be effectively identified by personnel training system developed in a systematic way and properly implemented. And only by sound and sufficient training can adequate number of replacements be produced. Well-developed IT platform can help the information management in such an era of information and internet. Information should be collected in a systematic way instead of stacking information on an ad hoc basis. But the project database must be established in an well-organized way, and the information should be aroused from sleeping, so that usable data will not be lost and are readily accessible on intranet and available to users. Or else the engineers take great pain to search for data like looking for a needle in a haystack, while useful data are gathering dust somewhere deep in the databank something. Compared to the well-developed industrial countries, there is quite a room in fundamental aspects which are cardinal requisites for effective knowledge management. These factors Contributing to Knowledge Management in Near-Term Operating Plants include not simply training and information management but also almost all other technical and management related to the

  11. Designing the Climate Observing System of the Future

    Science.gov (United States)

    Weatherhead, Elizabeth C.; Wielicki, Bruce A.; Ramaswamy, V.; Abbott, Mark; Ackerman, Thomas P.; Atlas, Robert; Brasseur, Guy; Bruhwiler, Lori; Busalacchi, Antonio J.; Butler, James H.; Clack, Christopher T. M.; Cooke, Roger; Cucurull, Lidia; Davis, Sean M.; English, Jason M.; Fahey, David W.; Fine, Steven S.; Lazo, Jeffrey K.; Liang, Shunlin; Loeb, Norman G.; Rignot, Eric; Soden, Brian; Stanitski, Diane; Stephens, Graeme; Tapley, Byron D.; Thompson, Anne M.; Trenberth, Kevin E.; Wuebbles, Donald

    2018-01-01

    Climate observations are needed to address a large range of important societal issues including sea level rise, droughts, floods, extreme heat events, food security, and freshwater availability in the coming decades. Past, targeted investments in specific climate questions have resulted in tremendous improvements in issues important to human health, security, and infrastructure. However, the current climate observing system was not planned in a comprehensive, focused manner required to adequately address the full range of climate needs. A potential approach to planning the observing system of the future is presented in this article. First, this article proposes that priority be given to the most critical needs as identified within the World Climate Research Program as Grand Challenges. These currently include seven important topics: melting ice and global consequences; clouds, circulation and climate sensitivity; carbon feedbacks in the climate system; understanding and predicting weather and climate extremes; water for the food baskets of the world; regional sea-level change and coastal impacts; and near-term climate prediction. For each Grand Challenge, observations are needed for long-term monitoring, process studies and forecasting capabilities. Second, objective evaluations of proposed observing systems, including satellites, ground-based and in situ observations as well as potentially new, unidentified observational approaches, can quantify the ability to address these climate priorities. And third, investments in effective climate observations will be economically important as they will offer a magnified return on investment that justifies a far greater development of observations to serve society's needs.

  12. Back from a predicted climatic extinction of an island endemic: a future for the Corsican Nuthatch.

    Directory of Open Access Journals (Sweden)

    Morgane Barbet-Massin

    Full Text Available The Corsican Nuthatch (Sitta whiteheadi is red-listed as vulnerable to extinction by the IUCN because of its endemism, reduced population size, and recent decline. A further cause is the fragmentation and loss of its spatially-restricted favourite habitat, the Corsican pine (Pinus nigra laricio forest. In this study, we aimed at estimating the potential impact of climate change on the distribution of the Corsican Nuthatch using species distribution models. Because this species has a strong trophic association with the Corsican and Maritime pines (P. nigra laricio and P. pinaster, we first modelled the current and future potential distribution of both pine species in order to use them as habitat variables when modelling the nuthatch distribution. However, the Corsican pine has suffered large distribution losses in the past centuries due to the development of anthropogenic activities, and is now restricted to mountainous woodland. As a consequence, its realized niche is likely significantly smaller than its fundamental niche, so that a projection of the current distribution under future climatic conditions would produce misleading results. To obtain a predicted pine distribution at closest to the geographic projection of the fundamental niche, we used available information on the current pine distribution associated to information on the persistence of isolated natural pine coppices. While common thresholds (maximizing the sum of sensitivity and specificity predicted a potential large loss of the Corsican Nuthatch distribution by 2100, the use of more appropriate thresholds aiming at getting closer to the fundamental distribution of the Corsican pine predicted that 98% of the current presence points should remain potentially suitable for the nuthatch and its range could be 10% larger in the future. The habitat of the endemic Corsican Nuthatch is therefore more likely threatened by an increasing frequency and intensity of wildfires or anthropogenic

  13. Predicting plant invasions under climate change: are species distribution models validated by field trials?

    Science.gov (United States)

    Sheppard, Christine S; Burns, Bruce R; Stanley, Margaret C

    2014-09-01

    Climate change may facilitate alien species invasion into new areas, particularly for species from warm native ranges introduced into areas currently marginal for temperature. Although conclusions from modelling approaches and experimental studies are generally similar, combining the two approaches has rarely occurred. The aim of this study was to validate species distribution models by conducting field trials in sites of differing suitability as predicted by the models, thus increasing confidence in their ability to assess invasion risk. Three recently naturalized alien plants in New Zealand were used as study species (Archontophoenix cunninghamiana, Psidium guajava and Schefflera actinophylla): they originate from warm native ranges, are woody bird-dispersed species and of concern as potential weeds. Seedlings were grown in six sites across the country, differing both in climate and suitability (as predicted by the species distribution models). Seedling growth and survival were recorded over two summers and one or two winter seasons, and temperature and precipitation were monitored hourly at each site. Additionally, alien seedling performances were compared to those of closely related native species (Rhopalostylis sapida, Lophomyrtus bullata and Schefflera digitata). Furthermore, half of the seedlings were sprayed with pesticide, to investigate whether enemy release may influence performance. The results showed large differences in growth and survival of the alien species among the six sites. In the more suitable sites, performance was frequently higher compared to the native species. Leaf damage from invertebrate herbivory was low for both alien and native seedlings, with little evidence that the alien species should have an advantage over the native species because of enemy release. Correlations between performance in the field and predicted suitability of species distribution models were generally high. The projected increase in minimum temperature and reduced

  14. Revisiting concepts of thermal physiology: Predicting responses of mammals to climate change.

    Science.gov (United States)

    Mitchell, Duncan; Snelling, Edward P; Hetem, Robyn S; Maloney, Shane K; Strauss, Willem Maartin; Fuller, Andrea

    2018-02-26

    The accuracy of predictive models (also known as mechanistic or causal models) of animal responses to climate change depends on properly incorporating the principles of heat transfer and thermoregulation into those models. Regrettably, proper incorporation of these principles is not always evident. We have revisited the relevant principles of thermal physiology and analysed how they have been applied in predictive models of large mammals, which are particularly vulnerable, to climate change. We considered dry heat exchange, evaporative heat transfer, the thermoneutral zone and homeothermy, and we examined the roles of size and shape in the thermal physiology of large mammals. We report on the following misconceptions in influential predictive models: underestimation of the role of radiant heat transfer, misassignment of the role and misunderstanding of the sustainability of evaporative cooling, misinterpretation of the thermoneutral zone as a zone of thermal tolerance or as a zone of sustainable energetics, confusion of upper critical temperature and critical thermal maximum, overestimation of the metabolic energy cost of evaporative cooling, failure to appreciate that the current advantages of size and shape will become disadvantageous as climate change advances, misassumptions about skin temperature and, lastly, misconceptions about the relationship between body core temperature and its variability with body mass in large mammals. Not all misconceptions invalidate the models, but we believe that preventing inappropriate assumptions from propagating will improve model accuracy, especially as models progress beyond their current typically static format to include genetic and epigenetic adaptation that can result in phenotypic plasticity. © 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society.

  15. An ensemble prediction approach to weekly Dengue cases forecasting based on climatic and terrain conditions

    Directory of Open Access Journals (Sweden)

    Sougata Deb

    2017-11-01

    Full Text Available Introduction: Dengue fever has been one of the most concerning endemic diseases of recent times. Every year, 50-100 million people get infected by the dengue virus across the world. Historically, it has been most prevalent in Southeast Asia and the Pacific Islands. In recent years, frequent dengue epidemics have started occurring in Latin America as well. This study focused on assessing the impact of different short and long-term lagged climatic predictors on dengue cases. Additionally, it assessed the impact of building an ensemble model using multiple time series and regression models, in improving prediction accuracy. Materials and Methods: Experimental data were based on two Latin American cities, viz. San Juan (Puerto Rico and Iquitos (Peru. Due to weather and geographic differences, San Juan recorded higher dengue incidences than Iquitos. Using lagged cross-correlations, this study confirmed the impact of temperature and vegetation on the number of dengue cases for both cities, though in varied degrees and time lags. An ensemble of multiple predictive models using an elaborate set of derived predictors was built and validated. Results: The proposed ensemble prediction achieved a mean absolute error of 21.55, 4.26 points lower than the 25.81 obtained by a standard negative binomial model. Changes in climatic conditions and urbanization were found to be strong predictors as established empirically in other researches. Some of the predictors were new and informative, which have not been explored in any other relevant studies yet. Discussion and Conclusions: Two original contributions were made in this research. Firstly, a focused and extensive feature engineering aligned with the mosquito lifecycle. Secondly, a novel covariate pattern-matching based prediction approach using past time series trend of the predictor variables. Increased accuracy of the proposed model over the benchmark model proved the appropriateness of the analytical approach

  16. The predicted influence of climate change on lesser prairie-chicken reproductive parameters

    Science.gov (United States)

    Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, D.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

    2013-01-01

    The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

  17. Predicting moisture state of timber members in a continuously varying climate

    DEFF Research Database (Denmark)

    Svensson, Staffan; Turk, Goran; Hozjan, Tomaz

    2011-01-01

    A prerequisite for a sensible estimate of moisture induced stresses in timber members is an accurate prediction of the members’ moisture states during their service life. There are, however, an infinite number of possible moisture states for an arbitrary timber member in a natural varying climate...... the realizations were made, are based on a fully coupled transport model including a model for the influential sorption hysteresis of wood. A format containing required information suitable for assessing the “moisture” action on timber members is proposed. In addition it is illustrated how a model of high...

  18. Calibration of the heat balance model for prediction of car climate

    OpenAIRE

    Jícha Miroslav; Fišer Jan; Pokorný Jan

    2012-01-01

    In the paper, the authors refer to development a heat balance model to predict car climate and power heat load. Model is developed in Modelica language using Dymola as interpreter. It is a dynamical system, which describes a heat exchange between car cabin and ambient. Inside a car cabin, there is considered heat exchange between air zone, interior and air-conditioning system. It is considered 1D heat transfer with a heat accumulation and a relative movement Sun respect to the car cabin, whil...

  19. Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

    Science.gov (United States)

    Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

    2015-04-01

    Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for

  20. Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination

    Science.gov (United States)

    Ren, Zhoupeng; Wang, Duoquan; Ma, Aimin; Hwang, Jimee; Bennett, Adam; Sturrock, Hugh J. W.; Fan, Junfu; Zhang, Wenjie; Yang, Dian; Feng, Xinyu; Xia, Zhigui; Zhou, Xiao-Nong; Wang, Jinfeng

    2016-02-01

    Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity.

  1. Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination.

    Science.gov (United States)

    Ren, Zhoupeng; Wang, Duoquan; Ma, Aimin; Hwang, Jimee; Bennett, Adam; Sturrock, Hugh J W; Fan, Junfu; Zhang, Wenjie; Yang, Dian; Feng, Xinyu; Xia, Zhigui; Zhou, Xiao-Nong; Wang, Jinfeng

    2016-02-12

    Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity.

  2. Predicting Circulatory Diseases from Psychosocial Safety Climate: A Prospective Cohort Study from Australia

    Directory of Open Access Journals (Sweden)

    Harry Becher

    2018-02-01

    Full Text Available Circulatory diseases (CDs (including myocardial infarction, angina, stroke or hypertension are among the leading causes of death in the world. In this paper, we explore for the first time the impact of a specific aspect of organizational climate, Psychosocial Safety Climate (PSC, on CDs. We used two waves of interview data from Australia, with an average lag of 5 years (excluding baseline CDs, final n = 1223. Logistic regression was conducted to estimate the prospective associations between PSC at baseline on incident CDs at follow-up. It was found that participants in low PSC environments were 59% more likely to develop new CD than those in high PSC environments. Logistic regression showed that high PSC at baseline predicts lower CD risk at follow-up (OR = 0.98, 95% CI 0.96–1.00 and this risk remained unchanged even after additional adjustment for known job design risk factors (effort reward imbalance and job strain. These results suggest that PSC is an independent risk factor for CDs in Australia. Beyond job design this study implicates organizational climate and prevailing management values regarding worker psychological health as the genesis of CDs.

  3. Predicting the distribution of commercially important invertebrate stocks under future climate.

    Directory of Open Access Journals (Sweden)

    Bayden D Russell

    Full Text Available The future management of commercially exploited species is challenging because techniques used to predict the future distribution of stocks under climate change are currently inadequate. We projected the future distribution and abundance of two commercially harvested abalone species (blacklip abalone, Haliotis rubra and greenlip abalone, H. laevigata inhabiting coastal South Australia, using multiple species distribution models (SDM and for decadal time slices through to 2100. Projections are based on two contrasting global greenhouse gas emissions scenarios. The SDMs identified August (winter Sea Surface Temperature (SST as the best descriptor of abundance and forecast that warming of winter temperatures under both scenarios may be beneficial to both species by allowing increased abundance and expansion into previously uninhabited coasts. This range expansion is unlikely to be realised, however, as projected warming of March SST is projected to exceed temperatures which cause up to 10-fold increases in juvenile mortality. By linking fine-resolution forecasts of sea surface temperature under different climate change scenarios to SDMs and physiological experiments, we provide a practical first approximation of the potential impact of climate-induced change on two species of marine invertebrates in the same fishery.

  4. Ocean-Atmosphere Coupling Processes Affecting Predictability in the Climate System

    Science.gov (United States)

    Miller, A. J.; Subramanian, A. C.; Seo, H.; Eliashiv, J. D.

    2017-12-01

    Predictions of the ocean and atmosphere are often sensitive to coupling at the air-sea interface in ways that depend on the temporal and spatial scales of the target fields. We will discuss several aspects of these types of coupled interactions including oceanic and atmospheric forecast applications. For oceanic mesoscale eddies, the coupling can influence the energetics of the oceanic flow itself. For Madden-Julian Oscillation onset, the coupling timestep should resolve the diurnal cycle to properly raise time-mean SST and latent heat flux prior to deep convection. For Atmospheric River events, the evolving SST field can alter the trajectory and intensity of precipitation anomalies along the California coast. Improvements in predictions will also rely on identifying and alleviating sources of biases in the climate states of the coupled system. Surprisingly, forecast skill can also be improved by enhancing stochastic variability in the atmospheric component of coupled models as found in a multiscale ensemble modeling approach.

  5. Development of the virtual research environment for analysis, evaluation and prediction of global climate change impacts on the regional environment

    Science.gov (United States)

    Okladnikov, Igor; Gordov, Evgeny; Titov, Alexander; Fazliev, Alexander

    2017-04-01

    Description and the first results of the Russian Science Foundation project "Virtual computational information environment for analysis, evaluation and prediction of the impacts of global climate change on the environment and climate of a selected region" is presented. The project is aimed at development of an Internet-accessible computation and information environment providing unskilled in numerical modelling and software design specialists, decision-makers and stakeholders with reliable and easy-used tools for in-depth statistical analysis of climatic characteristics, and instruments for detailed analysis, assessment and prediction of impacts of global climate change on the environment and climate of the targeted region. In the framework of the project, approaches of "cloud" processing and analysis of large geospatial datasets will be developed on the technical platform of the Russian leading institution involved in research of climate change and its consequences. Anticipated results will create a pathway for development and deployment of thematic international virtual research laboratory focused on interdisciplinary environmental studies. VRE under development will comprise best features and functionality of earlier developed information and computing system CLIMATE (http://climate.scert.ru/), which is widely used in Northern Eurasia environment studies. The Project includes several major directions of research listed below. 1. Preparation of geo-referenced data sets, describing the dynamics of the current and possible future climate and environmental changes in detail. 2. Improvement of methods of analysis of climate change. 3. Enhancing the functionality of the VRE prototype in order to create a convenient and reliable tool for the study of regional social, economic and political consequences of climate change. 4. Using the output of the first three tasks, compilation of the VRE prototype, its validation, preparation of applicable detailed description of

  6. Survey of Armillaria spp. in the Oregon East Cascades: Baseline data for predicting climatic influences on Armillaria root disease

    Science.gov (United States)

    J. W. Hanna; A. L. Smith; H. M. Maffei; M.-S. Kim; N. B. Klopfenstein

    2008-01-01

    Root disease pathogens, such as Armillaria solidipes Peck (recently recognized older name for A. ostoyae), will likely have increasing impacts to forest ecosystems as trees undergo stress due to climate change. Before we can predict future impacts of root disease pathogens, we must first develop an ability to predict current distributions of the pathogens (and their...

  7. A Melodic Contour Repeatedly Experienced by Human Near-Term Fetuses Elicits a Profound Cardiac Reaction One Month after Birth

    OpenAIRE

    Granier-Deferre, Carolyn; Bassereau, Sophie; Ribeiro, Aurélie; Jacquet, Anne-Yvonne; DeCasper, Anthony J.

    2011-01-01

    Background Human hearing develops progressively during the last trimester of gestation. Near-term fetuses can discriminate acoustic features, such as frequencies and spectra, and process complex auditory streams. Fetal and neonatal studies show that they can remember frequently recurring sounds. However, existing data can only show retention intervals up to several days after birth. Methodology/Principal Findings Here we show that auditory memories can last at least six weeks. Experimental fe...

  8. Management of hyperbilirubinemia in near ... term newborns according to American Academy of Pediatrics Guidelines: Report of three cases

    OpenAIRE

    Naomi Esthemita Dewanto; Rinawati Rohsiswatmo

    2009-01-01

    All neonates have a transient rise in bilirubin levels, and about 30-50% of infants become visibly jaundiced.1,2 Most jaundice is benign; however, because of the potential brain toxicity of bilirubin, newborn infants must be monitored to identify those who might develop severe hyperbilirubinemia and, in rare cases, acute bilirubin encephalopathy or kernicterus. Ten percent of term infants and 25% of near-term infants have significant hyperbilirubinemia and requir...

  9. Neurodevelopmental outcomes of near-term small-for-gestational-age infants with and without signs of placental underperfusion.

    Science.gov (United States)

    Parra-Saavedra, Miguel; Crovetto, Francesca; Triunfo, Stefania; Savchev, Stefan; Peguero, Anna; Nadal, Alfons; Parra, Guido; Gratacos, Eduard; Figueras, Francesc

    2014-04-01

    To evaluate 2-year neurodevelopmental outcomes of near-term, small-for-gestational-age (SGA) newborns segregated by presence or absence of histopathology reflecting placental underperfusion (PUP). A cohort of consecutive near-term (≥ 34.0 weeks) SGA newborns with normal prenatal umbilical artery Doppler studies was selected. All placentas were inspected for evidence of underperfusion and classified in accordance with established histologic criteria. Neurodevelopmental outcomes at 24 months (age-corrected) were then evaluated, applying the Bayley Scale for Infant and Toddler Development, Third Edition (Bayley-III) to assess cognitive, language, and motor competencies. The impact of PUP on each domain was measured via analysis of covariance, logistic and ordinal regression, with adjustment for smoking, socioeconomic status, gestational age at birth, gender, and breastfeeding. A total of 83 near-term SGA deliveries were studied, 46 (55.4%) of which showed signs of PUP. At 2 years, adjusted neurodevelopmental outcomes were significantly poorer in births involving PUP (relative to SGA infants without PUP) for all three domains of the Bayley scale: cognitive (105.5 vs 96.3, adjusted-p = 0.03), language (98.6 vs 87.8, adjusted-p<0.001), and motor (102.7 vs 94.5, adjusted-p = 0.007). Similarly, the adjusted likelihood of abnormal cognitive, language, and motor competencies in instances of underperfusion was 9.3-, 17.5-, and 1.44-fold higher, respectively, differing significantly for the former two domains. In a substantial fraction of near-term SGA babies without Doppler evidence of placental insufficiency, histologic changes compatible with PUP are still identifiable. These infants are at greater risk of abnormal neurodevelopmental outcomes at 2 years. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Understanding the origin of the solar cyclic activity for an improved earth climate prediction

    Science.gov (United States)

    Turck-Chièze, Sylvaine; Lambert, Pascal

    This review is dedicated to the processes which could explain the origin of the great extrema of the solar activity. We would like to reach a more suitable estimate and prediction of the temporal solar variability and its real impact on the Earth climatic models. The development of this new field is stimulated by the SoHO helioseismic measurements and by some recent solar modelling improvement which aims to describe the dynamical processes from the core to the surface. We first recall assumptions on the potential different solar variabilities. Then, we introduce stellar seismology and summarize the main SOHO results which are relevant for this field. Finally we mention the dynamical processes which are presently introduced in new solar models. We believe that the knowledge of two important elements: (1) the magnetic field interplay between the radiative zone and the convective zone and (2) the role of the gravity waves, would allow to understand the origin of the grand minima and maxima observed during the last millennium. Complementary observables like acoustic and gravity modes, radius and spectral irradiance from far UV to visible in parallel to the development of 1D-2D-3D simulations will improve this field. PICARD, SDO, DynaMICCS are key projects for a prediction of the next century variability. Some helioseismic indicators constitute the first necessary information to properly describe the Sun-Earth climatic connection.

  11. Good Models Gone Bad: Quantifying and Predicting Parameter-Induced Climate Model Simulation Failures

    Science.gov (United States)

    Lucas, D. D.; Klein, R.; Tannahill, J.; Brandon, S.; Covey, C. C.; Domyancic, D.; Ivanova, D. P.

    2012-12-01

    Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Statistical analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation failures of the Parallel Ocean Program (POP2). About 8.5% of our POP2 runs failed for numerical reasons at certain combinations of parameter values. We apply support vector machine (SVM) classification from the fields of pattern recognition and machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. The SVM classifiers readily predict POP2 failures in an independent validation ensemble, and are subsequently used to determine the causes of the failures via a global sensitivity analysis. Four parameters related to ocean mixing and viscosity are identified as the major sources of POP2 failures. Our method can be used to improve the robustness of complex scientific models to parameter perturbations and to better steer UQ ensembles. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-569112).

  12. Predicting the Potential Distribution of Polygala tenuifolia Willd. under Climate Change in China.

    Directory of Open Access Journals (Sweden)

    Hongjun Jiang

    Full Text Available Global warming has created opportunities and challenges for the survival and development of species. Determining how climate change may impact multiple ecosystem levels and lead to various species adaptations is necessary for both biodiversity conservation and sustainable biological resource utilization. In this study, we employed Maxent to predict changes in the habitat range and altitude of Polygala tenuifolia Willd. under current and future climate scenarios in China. Four representative concentration pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8.5 were modeled for two time periods (2050 and 2070. The model inputs included 732 presence points and nine sets of environmental variables under the current conditions and the four RCPs in 2050 and 2070. The area under the receiver-operating characteristic (ROC curve (AUC was used to evaluate model performance. All of the AUCs were greater than 0.80, thereby placing these models in the "very good" category. Using a jackknife analysis, the precipitation in the warmest quarter, annual mean temperature, and altitude were found to be the top three variables that affect the range of P. tenuifolia. Additionally, we found that the predicted highly suitable habitat was in reasonable agreement with its actual distribution. Furthermore, the highly suitable habitat area was slowly reduced over time.

  13. Darcy’s law predicts widespread forest mortality under climate warming

    Science.gov (United States)

    McDowell, Nate G.; Allen, Craig D.

    2015-01-01

    Drought and heat-induced tree mortality is accelerating in many forest biomes as a consequence of a warming climate, resulting in a threat to global forests unlike any in recorded history. Forests store the majority of terrestrial carbon, thus their loss may have significant and sustained impacts on the global carbon cycle. We use a hydraulic corollary to Darcy’s law, a core principle of vascular plant physiology, to predict characteristics of plants that will survive and die during drought under warmer future climates. Plants that are tall with isohydric stomatal regulation, low hydraulic conductance, and high leaf area are most likely to die from future drought stress. Thus, tall trees of old-growth forests are at the greatest risk of loss, which has ominous implications for terrestrial carbon storage. This application of Darcy’s law indicates today’s forests generally should be replaced by shorter and more xeric plants, owing to future warmer droughts and associated wildfires and pest attacks. The Darcy’s corollary also provides a simple, robust framework for informing forest management interventions needed to promote the survival of current forests. Given the robustness of Darcy’s law for predictions of vascular plant function, we conclude with high certainty that today’s forests are going to be subject to continued increases in mortality rates that will result in substantial reorganization of their structure and carbon storage.

  14. Chasing a changing climate: Reproductive and dispersal traits predict how sessile species respond to global warming

    Science.gov (United States)

    Archambault, Jennifer M.; Cope, W. Gregory; Kwak, Thomas J.

    2018-01-01

    AimStudies of species' range shifts have become increasingly relevant for understanding ecology and biogeography in the face of accelerated global change. The combination of limited mobility and imperilled status places some species at a potentially greater risk of range loss, extirpation or extinction due to climate change. To assess the ability of organisms with limited movement and dispersal capabilities to track shifts associated with climate change, we evaluated reproductive and dispersal traits of freshwater mussels (Unionida), sessile invertebrates that require species‐specific fish for larval dispersal.LocationNorth American Atlantic Slope rivers.MethodsTo understand how unionid mussels may cope with and adapt to current and future warming trends, we identified mechanisms that facilitated their colonization of the northern Atlantic Slope river basins in North America after the Last Glacial Maximum. We compiled species occurrence and life history trait information for each of 55 species, and then selected life history traits for which ample data were available (larval brooding duration, host fish specificity, host infection strategy, and body size) and analysed whether the trait state for each was related to mussel distribution in Atlantic Slope rivers.ResultsBrooding duration (p  .10).Main conclusionsOur results are potentially applicable to many species for which life history traits have not been well‐documented, because reproductive and dispersal traits in unionid mussels typically follow phylogenetic relationships. These findings may help resource managers prioritize species according to climate change vulnerability and predict which species might become further imperilled with climate warming. Finally, we suggest that similar trait‐based decision support frameworks may be applicable for other movement limited taxa.

  15. Can crop-climate models be accurate and precise? A case study for wheat production in Denmark

    DEFF Research Database (Denmark)

    Montesino San Martin, Manuel; Olesen, Jørgen E.; Porter, John Roy

    2015-01-01

    Crop models, used to make projections of climate change impacts, differ greatly in structural detail. Complexity of model structure has generic effects on uncertainty and error propagation in climate change impact assessments. We applied Bayesian calibration to three distinctly different empirical....... Yields predicted by the mechanistic model were generally more accurate than the empirical models for extrapolated conditions. This trend does not hold for all extrapolations; mechanistic and empirical models responded differently due to their sensitivities to distinct weather features. However, higher...... suitable for generic model ensembles for near-term agricultural impact assessments of climate change....

  16. Climate

    International Nuclear Information System (INIS)

    Fellous, J.L.

    2005-02-01

    This book starts with a series of about 20 preconceived ideas about climate and climatic change and analyses each of them in the light of the present day knowledge. Using this approach, it makes a status of the reality of the climatic change, of its causes and of the measures to be implemented to limit its impacts and reduce its most harmful consequences. (J.S.)

  17. Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-10-17

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

  18. Predicting species distribution and abundance responses to climate change: why it is essential to include biotic interactions across trophic levels.

    Science.gov (United States)

    Van der Putten, Wim H; Macel, Mirka; Visser, Marcel E

    2010-07-12

    Current predictions on species responses to climate change strongly rely on projecting altered environmental conditions on species distributions. However, it is increasingly acknowledged that climate change also influences species interactions. We review and synthesize literature information on biotic interactions and use it to argue that the abundance of species and the direction of selection during climate change vary depending on how their trophic interactions become disrupted. Plant abundance can be controlled by aboveground and belowground multitrophic level interactions with herbivores, pathogens, symbionts and their enemies. We discuss how these interactions may alter during climate change and the resulting species range shifts. We suggest conceptual analogies between species responses to climate warming and exotic species introduced in new ranges. There are also important differences: the herbivores, pathogens and mutualistic symbionts of range-expanding species and their enemies may co-migrate, and the continuous gene flow under climate warming can make adaptation in the expansion zone of range expanders different from that of cross-continental exotic species. We conclude that under climate change, results of altered species interactions may vary, ranging from species becoming rare to disproportionately abundant. Taking these possibilities into account will provide a new perspective on predicting species distribution under climate change.

  19. Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.

    Science.gov (United States)

    Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C

    2016-01-01

    Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.

  20. Effects of lateral boundary condition resolution and update frequency on regional climate model predictions

    Science.gov (United States)

    Pankatz, Klaus; Kerkweg, Astrid

    2015-04-01

    The work presented is part of the joint project "DecReg" ("Regional decadal predictability") which is in turn part of the project "MiKlip" ("Decadal predictions"), an effort funded by the German Federal Ministry of Education and Research to improve decadal predictions on a global and regional scale. In MiKlip, one big question is if regional climate modeling shows "added value", i.e. to evaluate, if regional climate models (RCM) produce better results than the driving models. However, the scope of this study is to look more closely at the setup specific details of regional climate modeling. As regional models only simulate a small domain, they have to inherit information about the state of the atmosphere at their lateral boundaries from external data sets. There are many unresolved questions concerning the setup of lateral boundary conditions (LBC). External data sets come from global models or from global reanalysis data-sets. A temporal resolution of six hours is common for this kind of data. This is mainly due to the fact, that storage space is a limiting factor, especially for climate simulations. However, theoretically, the coupling frequency could be as high as the time step of the driving model. Meanwhile, it is unclear if a more frequent update of the LBCs has a significant effect on the climate in the domain of the RCM. The first study examines how the RCM reacts to a higher update frequency. The study is based on a 30 year time slice experiment for three update frequencies of the LBC, namely six hours, one hour and six minutes. The evaluation of means, standard deviations and statistics of the climate in the regional domain shows only small deviations, some statistically significant though, of 2m temperature, sea level pressure and precipitation. The second part of the first study assesses parameters linked to cyclone activity, which is affected by the LBC update frequency. Differences in track density and strength are found when comparing the simulations

  1. Climate-based models for pulsed resources improve predictability of consumer population dynamics: outbreaks of house mice in forest ecosystems.

    Directory of Open Access Journals (Sweden)

    E Penelope Holland

    Full Text Available Accurate predictions of the timing and magnitude of consumer responses to episodic seeding events (masts are important for understanding ecosystem dynamics and for managing outbreaks of invasive species generated by masts. While models relating consumer populations to resource fluctuations have been developed successfully for a range of natural and modified ecosystems, a critical gap that needs addressing is better prediction of resource pulses. A recent model used change in summer temperature from one year to the next (ΔT for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer-resource dynamics to predict invasive house mouse (Mus musculus outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ΔT method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ΔT on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year's advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer-resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events.

  2. Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates.

    Science.gov (United States)

    Mathewson, Paul D; Moyer-Horner, Lucas; Beever, Erik A; Briscoe, Natalie J; Kearney, Michael; Yahn, Jeremiah M; Porter, Warren P

    2017-03-01

    How climate constrains species' distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect

  3. Mechanistic variables can enhance predictive models of endotherm distributions: The American pika under current, past, and future climates

    Science.gov (United States)

    Mathewson, Paul; Moyer-Horner, Lucas; Beever, Erik; Briscoe, Natalie; Kearney, Michael T.; Yahn, Jeremiah; Porter, Warren P.

    2017-01-01

    How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect

  4. Integration of climate change in flood prediction: application to the Somme river (France)

    Science.gov (United States)

    Pinault, J.-L.; Amraoui, N.; Noyer, M.-L.

    2003-04-01

    Exceptional floods that have occurred for the last two years in western and central Europe were very unlikely. The concomitance of such rare events shows that they might be imputable to climate change. The statistical analysis of long rainfall series confirms that both the cumulated annual height and the temporal variability have increased for the last decade. This paper is devoted to the analysis of climate change impact on flood prediction applied to the Somme river. The exceptional pluviometry that occurred from October 2000 to April 2001, about the double of the mean value, entailed catastrophic flood between the high Somme and Abbeville. The flow reached a peak at the beginning of May 2001, involving damages in numerous habitations and communication routes, and economical activity of the region had been flood-bound for more than 2 months. The flood caught unaware the population and caused deep traumas in France since it was the first time such a sudden event was recognized as resulting from groundwater discharge. Mechanisms of flood generation were studied tightly in order to predict the behavior of the Somme catchment and other urbanized basins when the pluviometry is exceptional in winter or in spring, which occurs more and more frequently in the northern part of Europe. The contribution of groundwater in surface water flow was calculated by inverse modeling from piezometers that are representative of aquifers in valleys. They were found on the slopes and near the edge of plateaus in order to characterize the drainage processes of the watertable to the surface water network. For flood prediction, a stochastic process is used, consisting in the generation of both rainfall and PET time series. The precipitation generator uses Markov chain Monte Carlo and simulated annealing from the Hastings -- Metropolis algorithm. Coupling of rainfall and PET generators with transfer enables a new evaluation of the probability of occurrence of floods, taking into account

  5. Using Scaling to Understand, Model and Predict Global Scale Anthropogenic and Natural Climate Change

    Science.gov (United States)

    Lovejoy, S.; del Rio Amador, L.

    2014-12-01

    The atmosphere is variable over twenty orders of magnitude in time (≈10-3 to 1017 s) and almost all of the variance is in the spectral "background" which we show can be divided into five scaling regimes: weather, macroweather, climate, macroclimate and megaclimate. We illustrate this with instrumental and paleo data. Based the signs of the fluctuation exponent H, we argue that while the weather is "what you get" (H>0: fluctuations increasing with scale), that it is macroweather (Hdecreasing with scale) - not climate - "that you expect". The conventional framework that treats the background as close to white noise and focuses on quasi-periodic variability assumes a spectrum that is in error by a factor of a quadrillion (≈ 1015). Using this scaling framework, we can quantify the natural variability, distinguish it from anthropogenic variability, test various statistical hypotheses and make stochastic climate forecasts. For example, we estimate the probability that the warming is simply a giant century long natural fluctuation is less than 1%, most likely less than 0.1% and estimate return periods for natural warming events of different strengths and durations, including the slow down ("pause") in the warming since 1998. The return period for the pause was found to be 20-50 years i.e. not very unusual; however it immediately follows a 6 year "pre-pause" warming event of almost the same magnitude with a similar return period (30 - 40 years). To improve on these unconditional estimates, we can use scaling models to exploit the long range memory of the climate process to make accurate stochastic forecasts of the climate including the pause. We illustrate stochastic forecasts on monthly and annual scale series of global and northern hemisphere surface temperatures. We obtain forecast skill nearly as high as the theoretical (scaling) predictability limits allow: for example, using hindcasts we find that at 10 year forecast horizons we can still explain ≈ 15% of the

  6. From field to region yield predictions in response to pedo-climatic variations in Eastern Canada

    Science.gov (United States)

    JÉGO, G.; Pattey, E.; Liu, J.

    2013-12-01

    The increase in global population coupled with new pressures to produce energy and bioproducts from agricultural land requires an increase in crop productivity. However, the influence of climate and soil variations on crop production and environmental performance is not fully understood and accounted for to define more sustainable and economical management strategies. Regional crop modeling can be a great tool for understanding the impact of climate variations on crop production, for planning grain handling and for assessing the impact of agriculture on the environment, but it is often limited by the availability of input data. The STICS ("Simulateur mulTIdisciplinaire pour les Cultures Standard") crop model, developed by INRA (France) is a functional crop model which has a built-in module to optimize several input parameters by minimizing the difference between calculated and measured output variables, such as Leaf Area Index (LAI). STICS crop model was adapted to the short growing season of the Mixedwood Plains Ecozone using field experiments results, to predict biomass and yield of soybean, spring wheat and corn. To minimize the numbers of inference required for regional applications, 'generic' cultivars rather than specific ones have been calibrated in STICS. After the calibration of several model parameters, the root mean square error (RMSE) of yield and biomass predictions ranged from 10% to 30% for the three crops. A bit more scattering was obtained for LAI (20%prediction to climate variations. Using RS data to re-initialize input parameters that are not readily available (e.g. seeding date) is considered an effective way

  7. Predicting plant diversity patterns in Madagascar: understanding the effects of climate and land cover change in a biodiversity hotspot.

    Directory of Open Access Journals (Sweden)

    Kerry A Brown

    Full Text Available Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.

  8. An Object-Based Approach to Evaluation of Climate Variability Projections and Predictions

    Science.gov (United States)

    Ammann, C. M.; Brown, B.; Kalb, C. P.; Bullock, R.

    2017-12-01

    Evaluations of the performance of earth system model predictions and projections are of critical importance to enhance usefulness of these products. Such evaluations need to address specific concerns depending on the system and decisions of interest; hence, evaluation tools must be tailored to inform about specific issues. Traditional approaches that summarize grid-based comparisons of analyses and models, or between current and future climate, often do not reveal important information about the models' performance (e.g., spatial or temporal displacements; the reason behind a poor score) and are unable to accommodate these specific information needs. For example, summary statistics such as the correlation coefficient or the mean-squared error provide minimal information to developers, users, and decision makers regarding what is "right" and "wrong" with a model. New spatial and temporal-spatial object-based tools from the field of weather forecast verification (where comparisons typically focus on much finer temporal and spatial scales) have been adapted to more completely answer some of the important earth system model evaluation questions. In particular, the Method for Object-based Diagnostic Evaluation (MODE) tool and its temporal (three-dimensional) extension (MODE-TD) have been adapted for these evaluations. More specifically, these tools can be used to address spatial and temporal displacements in projections of El Nino-related precipitation and/or temperature anomalies, ITCZ-associated precipitation areas, atmospheric rivers, seasonal sea-ice extent, and other features of interest. Examples of several applications of these tools in a climate context will be presented, using output of the CESM large ensemble. In general, these tools provide diagnostic information about model performance - accounting for spatial, temporal, and intensity differences - that cannot be achieved using traditional (scalar) model comparison approaches. Thus, they can provide more

  9. Neonatal physiological correlates of near-term brain development on MRI and DTI in very-low-birth-weight preterm infants

    Directory of Open Access Journals (Sweden)

    Jessica Rose, PhD

    2014-01-01

    Results suggest that at near-term age, thalamus WM microstructure may be particularly vulnerable to certain neonatal risk factors. Interactions between albumin, bilirubin, phototherapy, and brain development warrant further investigation. Identification of physiological risk factors associated with selective vulnerability of certain brain regions at near-term age may clarify the etiology of neurodevelopmental impairment and inform neuroprotective treatment for VLBW preterm infants.

  10. A Near-Term Concept for Trajectory Based Operations with Air/Ground Data Link Communication

    Science.gov (United States)

    McNally, David; Mueller, Eric; Thipphavong, David; Paielli, Russell; Cheng, Jinn-Hwei; Lee, Chuhan; Sahlman, Scott; Walton, Joe

    2010-01-01

    An operating concept and required system components for trajectory-based operations with air/ground data link for today's en route and transition airspace is proposed. Controllers are fully responsible for separation as they are today, and no new aircraft equipage is required. Trajectory automation computes integrated solutions to problems like metering, weather avoidance, traffic conflicts and the desire to find and fly more time/fuel efficient flight trajectories. A common ground-based system supports all levels of aircraft equipage and performance including those equipped and not equipped for data link. User interface functions for the radar controller's display make trajectory-based clearance advisories easy to visualize, modify if necessary, and implement. Laboratory simulations (without human operators) were conducted to test integrated operation of selected system components with uncertainty modeling. Results are based on 102 hours of Fort Worth Center traffic recordings involving over 37,000 individual flights. The presence of uncertainty had a marginal effect (5%) on minimum-delay conflict resolution performance, and windfavorable routes had no effect on detection and resolution metrics. Flight plan amendments and clearances were substantially reduced compared to today s operations. Top-of-descent prediction errors are the largest cause of failure indicating that better descent predictions are needed to reliably achieve fuel-efficient descent profiles in medium to heavy traffic. Improved conflict detections for climbing flights could enable substantially more continuous climbs to cruise altitude. Unlike today s Conflict Alert, tactical automation must alert when an altitude amendment is entered, but before the aircraft starts the maneuver. In every other failure case tactical automation prevented losses of separation. A real-time prototype trajectory trajectory-automation system is running now and could be made ready for operational testing at an en route

  11. Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

    International Nuclear Information System (INIS)

    Jafri, Y.Z.; Kamal, L.

    2007-01-01

    Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)

  12. Predicting optimum crop designs using crop models and seasonal climate forecasts.

    Science.gov (United States)

    Rodriguez, D; de Voil, P; Hudson, D; Brown, J N; Hayman, P; Marrou, H; Meinke, H

    2018-02-02

    Expected increases in food demand and the need to limit the incorporation of new lands into agriculture to curtail emissions, highlight the urgency to bridge productivity gaps, increase farmers profits and manage risks in dryland cropping. A way to bridge those gaps is to identify optimum combination of genetics (G), and agronomic managements (M) i.e. crop designs (GxM), for the prevailing and expected growing environment (E). Our understanding of crop stress physiology indicates that in hindsight, those optimum crop designs should be known, while the main problem is to predict relevant attributes of the E, at the time of sowing, so that optimum GxM combinations could be informed. Here we test our capacity to inform that "hindsight", by linking a tested crop model (APSIM) with a skillful seasonal climate forecasting system, to answer "What is the value of the skill in seasonal climate forecasting, to inform crop designs?" Results showed that the GCM POAMA-2 was reliable and skillful, and that when linked with APSIM, optimum crop designs could be informed. We conclude that reliable and skillful GCMs that are easily interfaced with crop simulation models, can be used to inform optimum crop designs, increase farmers profits and reduce risks.

  13. Calibration of the heat balance model for prediction of car climate

    Science.gov (United States)

    Pokorný, Jan; Fišer, Jan; Jícha, Miroslav

    2012-04-01

    In the paper, the authors refer to development a heat balance model to predict car climate and power heat load. Model is developed in Modelica language using Dymola as interpreter. It is a dynamical system, which describes a heat exchange between car cabin and ambient. Inside a car cabin, there is considered heat exchange between air zone, interior and air-conditioning system. It is considered 1D heat transfer with a heat accumulation and a relative movement Sun respect to the car cabin, whilst car is moving. Measurements of the real operating conditions of gave us data for model calibration. The model was calibrated for Škoda Felicia parking-summer scenarios.

  14. Calibration of the heat balance model for prediction of car climate

    Directory of Open Access Journals (Sweden)

    Jícha Miroslav

    2012-04-01

    Full Text Available In the paper, the authors refer to development a heat balance model to predict car climate and power heat load. Model is developed in Modelica language using Dymola as interpreter. It is a dynamical system, which describes a heat exchange between car cabin and ambient. Inside a car cabin, there is considered heat exchange between air zone, interior and air-conditioning system. It is considered 1D heat transfer with a heat accumulation and a relative movement Sun respect to the car cabin, whilst car is moving. Measurements of the real operating conditions of gave us data for model calibration. The model was calibrated for Škoda Felicia parking-summer scenarios.

  15. The value of model averaging and dynamical climate model predictions for improving statistical seasonal streamflow forecasts over Australia

    Science.gov (United States)

    Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.

    2013-10-01

    Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.

  16. Decadal climate predictability in the southern Indian Ocean captured by SINTEX-F using a simple SST-nudging scheme.

    Science.gov (United States)

    Morioka, Yushi; Doi, Takeshi; Behera, Swadhin K

    2018-01-26

    Decadal climate variability in the southern Indian Ocean has great influences on southern African climate through modulation of atmospheric circulation. Although many efforts have been made to understanding physical mechanisms, predictability of the decadal climate variability, in particular, the internally generated variability independent from external atmospheric forcing, remains poorly understood. This study investigates predictability of the decadal climate variability in the southern Indian Ocean using a coupled general circulation model, called SINTEX-F. The ensemble members of the decadal reforecast experiments were initialized with a simple sea surface temperature (SST) nudging scheme. The observed positive and negative peaks during late 1990s and late 2000s are well reproduced in the reforecast experiments initiated from 1994 and 1999, respectively. The experiments initiated from 1994 successfully capture warm SST and high sea level pressure anomalies propagating from the South Atlantic to the southern Indian Ocean. Also, the other experiments initiated from 1999 skillfully predict phase change from a positive to negative peak. These results suggest that the SST-nudging initialization has the essence to capture the predictability of the internally generated decadal climate variability in the southern Indian Ocean.

  17. Parametric decadal climate forecast recalibration (DeFoReSt 1.0

    Directory of Open Access Journals (Sweden)

    A. Pasternack

    2018-01-01

    Full Text Available Near-term climate predictions such as decadal climate forecasts are increasingly being used to guide adaptation measures. For near-term probabilistic predictions to be useful, systematic errors of the forecasting systems have to be corrected. While methods for the calibration of probabilistic forecasts are readily available, these have to be adapted to the specifics of decadal climate forecasts including the long time horizon of decadal climate forecasts, lead-time-dependent systematic errors (drift and the errors in the representation of long-term changes and variability. These features are compounded by small ensemble sizes to describe forecast uncertainty and a relatively short period for which typically pairs of reforecasts and observations are available to estimate calibration parameters. We introduce the Decadal Climate Forecast Recalibration Strategy (DeFoReSt, a parametric approach to recalibrate decadal ensemble forecasts that takes the above specifics into account. DeFoReSt optimizes forecast quality as measured by the continuous ranked probability score (CRPS. Using a toy model to generate synthetic forecast observation pairs, we demonstrate the positive effect on forecast quality in situations with pronounced and limited predictability. Finally, we apply DeFoReSt to decadal surface temperature forecasts from the MiKlip prototype system and find consistent, and sometimes considerable, improvements in forecast quality compared with a simple calibration of the lead-time-dependent systematic errors.

  18. Parametric decadal climate forecast recalibration (DeFoReSt 1.0)

    Science.gov (United States)

    Pasternack, Alexander; Bhend, Jonas; Liniger, Mark A.; Rust, Henning W.; Müller, Wolfgang A.; Ulbrich, Uwe

    2018-01-01

    Near-term climate predictions such as decadal climate forecasts are increasingly being used to guide adaptation measures. For near-term probabilistic predictions to be useful, systematic errors of the forecasting systems have to be corrected. While methods for the calibration of probabilistic forecasts are readily available, these have to be adapted to the specifics of decadal climate forecasts including the long time horizon of decadal climate forecasts, lead-time-dependent systematic errors (drift) and the errors in the representation of long-term changes and variability. These features are compounded by small ensemble sizes to describe forecast uncertainty and a relatively short period for which typically pairs of reforecasts and observations are available to estimate calibration parameters. We introduce the Decadal Climate Forecast Recalibration Strategy (DeFoReSt), a parametric approach to recalibrate decadal ensemble forecasts that takes the above specifics into account. DeFoReSt optimizes forecast quality as measured by the continuous ranked probability score (CRPS). Using a toy model to generate synthetic forecast observation pairs, we demonstrate the positive effect on forecast quality in situations with pronounced and limited predictability. Finally, we apply DeFoReSt to decadal surface temperature forecasts from the MiKlip prototype system and find consistent, and sometimes considerable, improvements in forecast quality compared with a simple calibration of the lead-time-dependent systematic errors.

  19. Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

    Energy Technology Data Exchange (ETDEWEB)

    Pattanaik, D.R. [India Meteorological Department (IMD), New Delhi (India); Kumar, Arun [Climate Prediction Center, National Centre for Environmental Prediction (NCEP)/NWS/NOAA, Camp Springs, MD (United States)

    2010-03-15

    The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction's (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS's hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50 E-110 E and 10 S-35 N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon

  20. Scaling of the Inertial Electrostatic Confinement (IEC) for near-term thrusters and future fusion propulsion

    International Nuclear Information System (INIS)

    Miley, G.; Bromley, B.; Jurczyk, B.; Stubbers, R.; DeMora, J.; Chacon, L.; Gu, Y.

    1998-01-01

    Inertial Electrostatic Confinement (IEC) is a unique approach to fusion and plasma energy systems that was conceptualized in the 1960s (Hirsch 1967) and has been the focus of recent development in the 1990s (Miley et al. 1995a). In the interests of space power and propulsion systems, conceptual rocket design studies (Bussard and Jameson 1994, Miley et al. 1995b) using the IEC have predicted excellent performance for a variety of space missions, since the power unit avoids the use of magnets and heavy drives resulting in a very high, specific impulse compared to other fusion systems. In their recent survey of prior conceptual design studies of fusion rockets, Williams and Borowski (1997) found that the Bussard IEC conceptual study (the open-quotes QEDclose quotes engine) offered a thrust-to-weight ratio of 10 milli-g close-quote s, a factor of five higher than conventional magnetic confinement concepts and even slightly above anti-proton micro fission/fusion designs. Thus there is considerable motivation to study IEC concepts for eventual space applications. However, the physics feasibility of the IEC still requires experimental demonstration, and an expanded data base is needed to insure that a power unit can in fact be built. copyright 1998 American Institute of Physics

  1. Scaling of the Inertial Electrostatic Confinement (IEC) for near-term thrusters and future fusion propulsion

    International Nuclear Information System (INIS)

    Miley, G.; Bromley, B.; Jurczyk, B.; Stubbers, R.; DeMora, J.; Chacon, L.; Gu, Y.

    1998-01-01

    Inertial Electrostatic Confinement (IEC) is a unique approach to fusion and plasma energy systems that was conceptualized in the 1960s (Hirsch 1967) and has been the focus of recent development in the 1990s (Miley et al. 1995a). In the interests of space power and propulsion systems, conceptual rocket design studies (Bussard and Jameson 1994, Miley et al. 1995b) using the IEC have predicted excellent performance for a variety of space missions, since the power unit avoids the use of magnets and heavy drives resulting in a very high, specific impulse compared to other fusion systems. In their recent survey of prior conceptual design studies of fusion rockets, Williams and Borowski (1997) found that the Bussard IEC conceptual study (the ''QED'' engine) offered a thrust-to-weight ratio of 10 milli-g's, a factor of five higher than conventional magnetic confinement concepts and even slightly above anti-proton micro fission/fusion designs. Thus there is considerable motivation to study IEC concepts for eventual space applications. However, the physics feasibility of the IEC still requires experimental demonstration, and an expanded data base is needed to insure that a power unit can in fact be built

  2. Final Technical Report for "Nuclear Technologies for Near Term Fusion Devices"

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, Paul P.H. [Univ. of Wisconsin, Madison, WI (United States); Sawan, Mohamed E. [Univ. of Wisconsin, Madison, WI (United States); Davis, Andrew [Univ. of Wisconsin, Madison, WI (United States); Bohm, Tim D. [Univ. of Wisconsin, Madison, WI (United States)

    2017-09-05

    Over approximately 18 years, this project evolved to focus on a number of related topics, all tied to the nuclear analysis of fusion energy systems. For the earliest years, the University of Wisconsin (UW)’s effort was in support of the Advanced Power Extraction (APEX) study to investigate high power density first wall and blanket systems. A variety of design concepts were studied before this study gave way to a design effort for a US Test Blanket Module (TBM) to be installed in ITER. Simultaneous to this TBM project, nuclear analysis supported the conceptual design of a number of fusion nuclear science facilities that might fill a role in the path to fusion energy. Beginning in approximately 2005, this project added a component focused on the development of novel radiation transport software capability in support of the above nuclear analysis needs. Specifically, a clear need was identified to support neutron and photon transport on the complex geometries associated with Computer-Aided Design (CAD). Following the initial development of the Direct Accelerated Geoemtry Monte Carlo (DAGMC) capability, additional features were added, including unstructured mesh tallies and multi-physics analysis such as the Rigorous 2-Step (R2S) methodology for Shutdown Dose Rate (SDR) prediction. Throughout the project, there were also smaller tasks in support of the fusion materials community and for the testing of changes to the nuclear data that is fundamental to this kind of nuclear analysis.

  3. Using isotopes to improve impact and hydrological predictions of land-surface schemes in global climate models

    International Nuclear Information System (INIS)

    McGuffie, K.; Henderson-Sellers, A.

    2002-01-01

    Global climate model (GCM) predictions of the impact of large-scale land-use change date back to 1984 as do the earliest isotopic studies of large-basin hydrology. Despite this coincidence in interest and geography, with both papers focussed on the Amazon, there have been few studies that have tried to exploit isotopic information with the goal of improving climate model simulations of the land-surface. In this paper we analyze isotopic results from the IAEA global data base specifically with the goal of identifying signatures of potential value for improving global and regional climate model simulations of the land-surface. Evaluation of climate model predictions of the impacts of deforestation of the Amazon has been shown to be of significance by recent results which indicate impacts occurring distant from the Amazon i.e. tele-connections causing climate change elsewhere around the globe. It is suggested that these could be similar in magnitude and extent to the global impacts of ENSO events. Validation of GCM predictions associated with Amazonian deforestation are increasingly urgently required because of the additional effects of other aspects of climate change, particularly synergies occurring between forest removal and greenhouse gas increases, especially CO 2 . Here we examine three decades distributions of deuterium excess across the Amazon and use the results to evaluate the relative importance of the fractionating (partial evaporation) and non-fractionating (transpiration) processes. These results illuminate GCM scenarios of importance to the regional climate and hydrology: (i) the possible impact of increased stomatal resistance in the rainforest caused by higher levels of atmospheric CO2 [4]; and (ii) the consequences of the combined effects of deforestation and global warming on the regions climate and hydrology

  4. Population differentiation in tree-ring growth response of white fir (Abies concolor) to climate: Implications for predicting forest responses to climate change

    Energy Technology Data Exchange (ETDEWEB)

    Jensen, Deborah Bowne [Univ. of California, Berkeley, CA (United States)

    1993-01-01

    Forest succession models and correlative models have predicted 200--650 kilometer shifts in the geographic range of temperate forests and forest species as one response to global climate change. Few studies have investigated whether population differences may effect the response of forest species to climate change. This study examines differences in tree-ring growth, and in the phenotypic plasticity of tree-ring growth in 16-year old white fir, Abies concolor, from ten populations grown in four common gardens in the Sierra Nevada of California. For each population, tree-ring growth was modelled as a function of precipitation and degree-day sums. Tree-ring growth under three scenarios of doubled CO2 climates was estimated.

  5. Can we expect to predict climate if we cannot shadow weather?

    Science.gov (United States)

    Smith, Leonard

    2010-05-01

    What limits our ability to predict (or project) useful statistics of future climate? And how might we quantify those limits? In the early 1960s, Ed Lorenz illustrated one constraint on point forecasts of the weather (chaos) while noting another (model imperfections). In the mid-sixties he went on to discuss climate prediction, noting that chaos, per se, need not limit accurate forecasts of averages and the distributions that define climate. In short, chaos might place draconian limits on what we can say about a particular summer day in 2010 (or 2040), but it need not limit our ability to make accurate and informative statements about the weather over this summer as a whole, or climate distributions of the 2040's. If not chaos, what limits our ability to produce decision relevant probability distribution functions (PDFs)? Is this just a question of technology (raw computer power) and uncertain boundary conditions (emission scenarios)? Arguably, current model simulations of the Earth's climate are limited by model inadequacy: not that the initial or boundary conditions are unknown but that state-of-the-art models would not yield decision-relevant probability distributions even if they were known. Or to place this statement in an empirically falsifiable format: that in 2100 when the boundary conditions are known and computer power is (hopefully) sufficient to allow exhaustive exploration of today's state-of-the-art models: we will find today's models do not admit a trajectory consistent with our knowledge of the state of the earth in 2009 which would prove of decision support relevance for, say, 25 km, hourly resolution. In short: today's models cannot shadow the weather of this century even after the fact. Restating this conjecture in a more positive frame: a 2100 historian of science will be able to determine the highest space and time scales on which 2009 models could have (i) produced trajectories plausibly consistent with the (by then) observed twenty

  6. Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

    Science.gov (United States)

    Lee, Donghoon; Ward, Philip; Block, Paul

    2018-02-01

    Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

  7. Climatic associations of British species distributions show good transferability in time but low predictive accuracy for range change.

    Directory of Open Access Journals (Sweden)

    Giovanni Rapacciuolo

    Full Text Available Conservation planners often wish to predict how species distributions will change in response to environmental changes. Species distribution models (SDMs are the primary tool for making such predictions. Many methods are widely used; however, they all make simplifying assumptions, and predictions can therefore be subject to high uncertainty. With global change well underway, field records of observed range shifts are increasingly being used for testing SDM transferability. We used an unprecedented distribution dataset documenting recent range changes of British vascular plants, birds, and butterflies to test whether correlative SDMs based on climate change provide useful approximations of potential distribution shifts. We modelled past species distributions from climate using nine single techniques and a consensus approach, and projected the geographical extent of these models to a more recent time period based on climate change; we then compared model predictions with recent observed distributions in order to estimate the temporal transferability and prediction accuracy of our models. We also evaluated the relative effect of methodological and taxonomic variation on the performance of SDMs. Models showed good transferability in time when assessed using widespread metrics of accuracy. However, models had low accuracy to predict where occupancy status changed between time periods, especially for declining species. Model performance varied greatly among species within major taxa, but there was also considerable variation among modelling frameworks. Past climatic associations of British species distributions retain a high explanatory power when transferred to recent time--due to their accuracy to predict large areas retained by species--but fail to capture relevant predictors of change. We strongly emphasize the need for caution when using SDMs to predict shifts in species distributions: high explanatory power on temporally-independent records

  8. Present Status and Near Term Activities for the ExoMars Trace Gas Orbiter.

    Science.gov (United States)

    Svedhem, H.; Vago, J. L.

    2017-12-01

    The ExoMars 2016 mission was launched on a Proton rocket from Baikonur, Kazakhstan, on 14 March 2016 and arrived at Mars on 19 October 2016. The spacecraft is now performing aerobraking to reduce its orbital period from initial post-insertion orbital period of one Sol to the final science orbit with a 2 hours period. The orbital inclination will be 74 degrees. During the aerobraking a wealth of data has been acquired on the state of the atmosphere along the tracks between 140km and the lowest altitude at about 105 km. These data are now being analysed and compared with existing models. In average TGO measures a lower atmospheric density than predicted, but the numbers lay within the expected variability. ExoMars is a joint programme of the European Space Agency (ESA) and Roscosmos, Russia. It consists of the ExoMars 2016 mission with the Trace Gas Orbiter, TGO, and the Entry Descent and Landing Demonstrator, EDM, named Schiaparelli, and the ExoMars 2020 mission, which carries a lander and a rover. The TGO scientific payload consists of four instruments: ACS and NOMAD, both infrared spectrometers for atmospheric measurements in solar occultation mode and in nadir mode, CASSIS, a multichannel camera with stereo imaging capability, and FREND, an epithermal neutron detector to search for subsurface hydrogen (as proxy for water ice and hydrated minerals). The launch mass of the TGO was 3700 kg, including fuel. In addition to its scientific measurements TGO will act as a relay orbiter for NASA's landers on Mars and as from 2021 for the ESA-Roscosmos Rover and Surface Station.

  9. Using Bayesian methods to predict climate impacts on groundwater availability and agricultural production in Punjab, India

    Science.gov (United States)

    Russo, T. A.; Devineni, N.; Lall, U.

    2015-12-01

    Lasting success of the Green Revolution in Punjab, India relies on continued availability of local water resources. Supplying primarily rice and wheat for the rest of India, Punjab supports crop irrigation with a canal system and groundwater, which is vastly over-exploited. The detailed data required to physically model future impacts on water supplies agricultural production is not readily available for this region, therefore we use Bayesian methods to estimate hydrologic properties and irrigation requirements for an under-constrained mass balance model. Using measured values of historical precipitation, total canal water delivery, crop yield, and water table elevation, we present a method using a Markov chain Monte Carlo (MCMC) algorithm to solve for a distribution of values for each unknown parameter in a conceptual mass balance model. Due to heterogeneity across the state, and the resolution of input data, we estimate model parameters at the district-scale using spatial pooling. The resulting model is used to predict the impact of precipitation change scenarios on groundwater availability under multiple cropping options. Predicted groundwater declines vary across the state, suggesting that crop selection and water management strategies should be determined at a local scale. This computational method can be applied in data-scarce regions across the world, where water resource management is required to resolve competition between food security and available resources in a changing climate.

  10. Nudging and predictability in regional climate modelling: investigation in a nested quasi-geostrophic model

    Science.gov (United States)

    Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas

    2010-05-01

    In this work, we consider the effect of indiscriminate and spectral nudging on the large and small scales of an idealized model simulation. The model is a two layer quasi-geostrophic model on the beta-plane driven at its boundaries by the « global » version with periodic boundary condition. This setup mimics the configuration used for regional climate modelling. The effect of large-scale nudging is studied by using the "perfect model" approach. Two sets of experiments are performed: (1) the effect of nudging is investigated with a « global » high resolution two layer quasi-geostrophic model driven by a low resolution two layer quasi-geostrophic model. (2) similar simulations are conducted with the two layer quasi-geostrophic Limited Area Model (LAM) where the size of the LAM domain comes into play in addition to the first set of simulations. The study shows that the indiscriminate nudging time that minimizes the error at both the large and small scales is reached for a nudging time close to the predictability time, for spectral nudging, the optimum nudging time should tend to zero since the best large scale dynamics is supposed to be given by the driving large-scale fields are generally given at much lower frequency than the model time step(e,g, 6-hourly analysis) with a basic interpolation between the fields, the optimum nudging time differs from zero, however remaining smaller than the predictability time.

  11. Effects of predicted climatic changes on distribution of organic contaminants in brackish water mesocosms.

    Science.gov (United States)

    Ripszam, M; Gallampois, C M J; Berglund, Å; Larsson, H; Andersson, A; Tysklind, M; Haglund, P

    2015-06-01

    Predicted consequences of future climate change in the northern Baltic Sea include increases in sea surface temperatures and terrestrial dissolved organic carbon (DOC) runoff. These changes are expected to alter environmental distribution of anthropogenic organic contaminants (OCs). To assess likely shifts in their distributions, outdoor mesocosms were employed to mimic pelagic ecosystems at two temperatures and two DOC concentrations, current: 15°C and 4 mg DOCL(-1) and, within ranges of predicted increases, 18°C and 6 mg DOCL(-1), respectively. Selected organic contaminants were added to the mesocosms to monitor changes in their distribution induced by the treatments. OC partitioning to particulate matter and sedimentation were enhanced at the higher DOC concentration, at both temperatures, while higher losses and lower partitioning of OCs to DOC were observed at the higher temperature. No combined effects of higher temperature and DOC on partitioning were observed, possibly because of the balancing nature of these processes. Therefore, changes in OCs' fates may largely depend on whether they are most sensitive to temperature or DOC concentration rises. Bromoanilines, phenanthrene, biphenyl and naphthalene were sensitive to the rise in DOC concentration, whereas organophosphates, chlorobenzenes (PCBz) and polychlorinated biphenyls (PCBs) were more sensitive to temperature. Mitotane and diflufenican were sensitive to both temperature and DOC concentration rises individually, but not in combination. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. On the Fielding of a High Gain, Shock-Ignited Target on the National Ignitiion Facility in the Near Term

    International Nuclear Information System (INIS)

    Perkins, L.J.; Betti, R.; Schurtz, G.P.; Craxton, R.S.; Dunne, A.M.; LaFortune, K.N.; Schmitt, A.J.; McKenty, P.W.; Bailey, D.S.; Lambert, M.A.; Ribeyre, X.; Theobald, W.R.; Strozzi, D.J.; Harding, D.R.; Casner, A.; Atzemi, S.; Erbert, G.V.; Andersen, K.S.; Murakami, M.; Comley, A.J.; Cook, R.C.; Stephens, R.B.

    2010-01-01

    Shock ignition, a new concept for igniting thermonuclear fuel, offers the possibility for a near-term (∼3-4 years) test of high gain inertial confinement fusion on the National Ignition Facility at less than 1MJ drive energy and without the need for new laser hardware. In shock ignition, compressed fusion fuel is separately ignited by a strong spherically converging shock and, because capsule implosion velocities are significantly lower than those required for conventional hotpot ignition, fusion energy gains of ∼60 may be achievable on NIF at laser drive energies around ∼0.5MJ. Because of the simple all-DT target design, its in-flight robustness, the potential need for only 1D SSD beam smoothing, minimal early time LPI preheat, and use of present (indirect drive) laser hardware, this target may be easier to field on NIF than a conventional (polar) direct drive hotspot ignition target. Like fast ignition, shock ignition has the potential for high fusion yields at low drive energy, but requires only a single laser with less demanding timing and spatial focusing requirements. Of course, conventional symmetry and stability constraints still apply. In this paper we present initial target performance simulations, delineate the critical issues and describe the immediate-term R and D program that must be performed in order to test the potential of a high gain shock ignition target on NIF in the near term.

  13. Near-term nuclear as the nemesis of the age of pollution: re-engineering the planet

    International Nuclear Information System (INIS)

    Miller, A.; Duffey, R.B.

    2004-01-01

    The world's carefree Age of Pollution is ending and energy technologies are scrambling for schemes that either capture their wastes or claim corresponding offsets with reductions elsewhere. Not before time. But the transition offers boundless opportunities for political and subsidies, fudges, and deceptions. Now is the time for nuclear fission, as the only technology already providing large-scale, pollution-free energy supplies, to claim proper recognition for its demonstrated pollution-free pedigree. Our industry knows that nuclear fission really is an intrinsically superior solution over those offered by the latter-day converts to sequestration and environmental cleanliness. Our singular strength is the availability of our technology. But we must inspire society with nuclear's capacity to provide a comprehensive and affordable route to secure energy supplies with vigorous growth in its deployment, starting immediately. We must include hydrogen fuelling for vehicles to make our solution comprehensive. This paper outlines the economics. We could, however, so easily dissipate the advantage of nuclear's availability. Programs to evolve advanced reactors should be a natural adjunct to a vigorous near-term program but it would be folly to compete for leadership in energy supply based on the promise of reactor designs that cannot be deployed until after 2020. What is needed is a transition strategy. Several countries with emerging economies are showing near-term leadership in commitment of new reactors but the developed world also needs much expanded deployment of nuclear. Without that, the transition to advanced designs after 2020 could be jeopardized. (authors)

  14. M2 priority screening system for near-term activities: Project documentation. Final report December 11, 1992--May 31, 1994

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1993-08-12

    From May through August, 1993, the M-2 Group within M Division at LANL conducted with the support of the LANL Integration and Coordination Office (ICO) and Applied Decision Analysis, Inc. (ADA), whose purpose was to develop a system for setting priorities among activities. This phase of the project concentrated on prioritizing near-tenn activities (i.e., activities that must be conducted in the next six months) necessary for setting up this new group. Potential future project phases will concentrate on developing a tool for setting priorities and developing annual budgets for the group`s operations. The priority screening system designed to address the near-term problem was developed, applied in a series of meeting with the group managers, and used as an aid in the assignment of tasks to group members. The model was intended and used as a practical tool for documenting and explaining decisions about near-term priorities, and not as a substitute for M-2 management judgment and decision-making processes.

  15. Prediction of Daily Global Solar Radiation by Daily Temperatures and Artificial Neural Networks in Different Climates

    Directory of Open Access Journals (Sweden)

    S. I Saedi

    2018-03-01

    Full Text Available Introduction Global solar radiation is the sum of direct, diffuse, and reflected solar radiation. Weather forecasts, agricultural practices, and solar equipment development are three major fields that need proper information about solar radiation. Furthermore, sun in regarded as a huge source of renewable and clean energy which can be used in numerous applications to get rid of environmental impacts of non-renewable fossil fuels. Therefore, easy and fast estimation of daily global solar radiation would play an effective role is these affairs. Materials and Methods This study aimed at predicting the daily global solar radiation by means of artificial neural network (ANN method, based on easy-to-gain weather data i.e. daily mean, minimum and maximum temperatures. Having a variety of climates with long-term valid weather data, Washington State, located at the northwestern part of USA was chosen for this purpose. It has a total number of 19 weather stations to cover all the State climates. First, a station with the largest number of valid historical weather data (Lind was chosen to develop, validate, and test different ANN models. Three training algorithms i.e. Levenberg – Marquardt (LM, Scaled Conjugate Gradient (SCG, and Bayesian regularization (BR were tested in one and two hidden layer networks each with up to 20 neurons to derive six best architectures. R, RMSE, MAPE, and scatter plots were considered to evaluate each network in all steps. In order to investigate the generalizability of the best six models, they were tested in other Washington State weather stations. The most accurate and general models was evaluated in an Iran sample weather station which was chosen to be Mashhad. Results and Discussion The variation of MSE for the three training functions in one hidden layer models for Lind station indicated that SCG converged weights and biases in shorter time than LM, and LM did that faster than BR. It means that SCG provided the fastest

  16. Multi-Annual Climate Predictions for Fisheries: An Assessment of Skill of Sea Surface Temperature Forecasts for Large Marine Ecosystems

    Directory of Open Access Journals (Sweden)

    Desiree Tommasi

    2017-06-01

    Full Text Available Decisions made by fishers and fisheries managers are informed by climate and fisheries observations that now often span more than 50 years. Multi-annual climate forecasts could further inform such decisions if they were skillful in predicting future conditions relative to the 50-year scope of past variability. We demonstrate that an existing multi-annual prediction system skillfully forecasts the probability of next year, the next 1–3 years, and the next 1–10 years being warmer or cooler than the 50-year average at the surface in coastal ecosystems. Probabilistic forecasts of upper and lower seas surface temperature (SST terciles over the next 3 or 10 years from the GFDL CM 2.1 10-member ensemble global prediction system showed significant improvements in skill over the use of a 50-year climatology for most Large Marine Ecosystems (LMEs in the North Atlantic, the western Pacific, and Indian oceans. Through a comparison of the forecast skill of initialized and uninitialized hindcasts, we demonstrate that this skill is largely due to the predictable signature of radiative forcing changes over the 50-year timescale rather than prediction of evolving modes of climate variability. North Atlantic LMEs stood out as the only coastal regions where initialization significantly contributed to SST prediction skill at the 1 to 10 year scale.

  17. Hydroregime prediction models for ephemeral groundwater-driven sinkhole wetlands: a planning tool for climate change and amphibian conservation

    Science.gov (United States)

    C. H. Greenberg; S. Goodrick; J. D. Austin; B. R. Parresol

    2015-01-01

    Hydroregimes of ephemeral wetlands affect reproductive success of many amphibian species and are sensitive to altered weather patterns associated with climate change.We used 17 years of weekly temperature, precipitation, and waterdepth measurements for eight small, ephemeral, groundwaterdriven sinkhole wetlands in Florida sandhills to develop a hydroregime predictive...

  18. Climate Prediction Center (CPC) NCEP-Global Forecast System (GFS) 0-10cm Soil-Moisture Forecast Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Forecast System (GFS) forecast 0-10cm soil-moisture data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near...

  19. Comparison of Regression Techniques to Predict Response of Oilseed Rape Yield to Variation in Climatic Conditions in Denmark

    DEFF Research Database (Denmark)

    Sharif, Behzad; Makowski, David; Plauborg, Finn

    2017-01-01

    Statistical regression models represent alternatives to process-based dynamic models for predicting the response of crop yields to variation in climatic conditions. Regression models can be used to quantify the effect of change in temperature and precipitation on yields. However, it is difficult ...

  20. Association of Climatic Variability, Vector Population and Malarial Disease in District of Visakhapatnam, India: A Modeling and Prediction Analysis.

    Science.gov (United States)

    Srimath-Tirumula-Peddinti, Ravi Chandra Pavan Kumar; Neelapu, Nageswara Rao Reddy; Sidagam, Naresh

    2015-01-01

    Malarial incidence, severity, dynamics and distribution of malaria are strongly determined by climatic factors, i.e., temperature, precipitation, and relative humidity. The objectives of the current study were to analyse and model the relationships among climate, vector and malaria disease in district of Visakhapatnam, India to understand malaria transmission mechanism (MTM). Epidemiological, vector and climate data were analysed for the years 2005 to 2011 in Visakhapatnam to understand the magnitude, trends and seasonal patterns of the malarial disease. Statistical software MINITAB ver. 14 was used for performing correlation, linear and multiple regression analysis. Perennial malaria disease incidence and mosquito population was observed in the district of Visakhapatnam with peaks in seasons. All the climatic variables have a significant influence on disease incidence as well as on mosquito populations. Correlation coefficient analysis, seasonal index and seasonal analysis demonstrated significant relationships among climatic factors, mosquito population and malaria disease incidence in the district of Visakhapatnam, India. Multiple regression and ARIMA (I) models are best suited models for modeling and prediction of disease incidences and mosquito population. Predicted values of average temperature, mosquito population and malarial cases increased along with the year. Developed MTM algorithm observed a major MTM cycle following the June to August rains and occurring between June to September and minor MTM cycles following March to April rains and occurring between March to April in the district of Visakhapatnam. Fluctuations in climatic factors favored an increase in mosquito populations and thereby increasing the number of malarial cases. Rainfall, temperatures (20°C to 33°C) and humidity (66% to 81%) maintained a warmer, wetter climate for mosquito growth, parasite development and malaria transmission. Changes in climatic factors influence malaria directly by

  1. On the use and potential use of seasonal to decadal climate predictions for decision-making in Europe

    Science.gov (United States)

    Soares, Marta Bruno; Dessai, Suraje

    2014-05-01

    The need for climate information to help inform decision-making in sectors susceptible to climate events and impacts is widely recognised. In Europe, developments in the science and models underpinning the study of climate variability and change have led to an increased interest in seasonal to decadal climate predictions (S2DCP). While seasonal climate forecasts are now routinely produced operationally by a number of centres around the world, decadal climate predictions are still in its infancy restricted to the realm of research. Contrary to other regions of the world, where the use of these types of forecasts, particularly at seasonal timescales, has been pursued in recent years due to higher levels of predictability, little is known about the uptake and climate information needs of end-users regarding S2DCP in Europe. To fill this gap we conducted in-depth interviews with experts and decision-makers across a range of European sectors, a workshop with European climate services providers, and a systematic literature review on the use of S2DCP in Europe. This study is part of the EUropean Provision Of Regional Impact Assessment on a Seasonal-to-decadal timescale (EUPORIAS) project which aims to develop semi-operational prototypes of impact prediction systems in Europe on seasonal to decadal timescales. We found that the emerging landscape of users and potential users of S2DCP in Europe is complex and heterogeneous. Differences in S2DCP information needs across and within organisations and sectors are largely underpinned by factors such as the institutional and regulatory context of the organisations, the plethora of activities and decision-making processes involved, the level of expertise and capacity of the users, and the availability of resources within the organisations. In addition, although the use of S2DCP across Europe is still fairly limited, particular sectors such as agriculture, health, energy, water, (re)insurance, and transport are taking the lead on

  2. Long-range weather prediction and prevention of climate catastrophes: a status report

    International Nuclear Information System (INIS)

    Caldeira, K; Caravan, G; Govindasamy, B; Grossman, A; Hyde, R; Ishikawa, M; Ledebuhr, A; Leith, C; Molenkamp, C; Teller, E; Wood, L

    1999-01-01

    As the human population of Earth continues to expand and to demand an ever-higher quality-of-life, requirements for ever-greater knowledge-and then control-of the future of the state of the terrestrial biosphere grow apace. Convenience of living-and, indeed, reliability of life itself-become ever more highly ''tuned'' to the future physical condition of the biosphere being knowable and not markedly different than the present one, Two years ago, we reported at a quantitative albeit conceptual level on technical ways-and-means of forestalling large-scale changes in the present climate, employing practical means of modulating insolation and/or the Earth's mean albedo. Last year, we reported on early work aimed at developing means for creating detailed, high-fidelity, all-Earth weather forecasts of two weeks duration, exploiting recent and anticipated advances in extremely high-performance digital computing and in atmosphere-observing Earth satellites bearing high-technology instrumentation. This year, we report on recent progress in both of these areas of endeavor. Preventing the commencement of large-scale changes in the current climate presently appears to be a considerably more interesting prospect than initially realized, as modest insolation reductions are model-predicted to offset the anticipated impacts of ''global warming'' surprisingly precisely, in both space and time. Also, continued study has not revealed any fundamental difficulties in any of the means proposed for insolation modulation and, indeed, applicability of some of these techniques to other planets in the inner Solar system seems promising. Implementation of the high-fidelity, long-range weather-forecasting capability presently appears substantially easier with respect to required populations of Earth satellites and atmospheric transponders and data-processing systems, and more complicated with respect to transponder lifetimes in the actual atmosphere; overall, the enterprise seems more

  3. Long-range Weather Prediction and Prevention of Climate Catastrophes: A Status Report

    Science.gov (United States)

    Caldeira, K.; Caravan, G.; Govindasamy, B.; Grossman, A.; Hyde, R.; Ishikawa, M.; Ledebuhr, A.; Leith, C.; Molenkamp, C.; Teller, E.; Wood, L.

    1999-08-18

    As the human population of Earth continues to expand and to demand an ever-higher quality-of-life, requirements for ever-greater knowledge--and then control--of the future of the state of the terrestrial biosphere grow apace. Convenience of living--and, indeed, reliability of life itself--become ever more highly ''tuned'' to the future physical condition of the biosphere being knowable and not markedly different than the present one. Two years ago, we reported at a quantitative albeit conceptual level on technical ways-and-means of forestalling large-scale changes in the present climate, employing practical means of modulating insolation and/or the Earth's mean albedo. Last year, we reported on early work aimed at developing means for creating detailed, high-fidelity, all-Earth weather forecasts of two weeks duration, exploiting recent and anticipated advances in extremely high-performance digital computing and in atmosphere-observing Earth satellites bearing high-technology instrumentation. This year, we report on recent progress in both of these areas of endeavor. Preventing the commencement of large-scale changes in the current climate presently appears to be a considerably more interesting prospect than initially realized, as modest insolation reductions are model-predicted to offset the anticipated impacts of ''global warming'' surprisingly precisely, in both space and time. Also, continued study has not revealed any fundamental difficulties in any of the means proposed for insolation modulation and, indeed, applicability of some of these techniques to other planets in the inner Solar system seems promising. Implementation of the high-fidelity, long-range weather-forecasting capability presently appears substantially easier with respect to required populations of Earth satellites and atmospheric transponders and data-processing systems, and more complicated with respect to transponder lifetimes in the actual atmosphere; overall, the enterprise seems more

  4. Maxent modeling for predicting the potential geographical distribution of two peony species under climate change.

    Science.gov (United States)

    Zhang, Keliang; Yao, Linjun; Meng, Jiasong; Tao, Jun

    2018-09-01

    Paeonia (Paeoniaceae), an economically important plant genus, includes many popular ornamentals and medicinal plant species used in traditional Chinese medicine. Little is known about the properties of the habitat distribution and the important eco-environmental factors shaping the suitability. Based on high-resolution environmental data for current and future climate scenarios, we modeled the present and future suitable habitat for P. delavayi and P. rockii by Maxent, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. The results showed that the moderate and high suitable areas for P. delavayi and P. rockii encompassed ca. 4.46×10 5 km 2 and 1.89×10 5 km 2 , respectively. Temperature seasonality and isothermality were identified as the most critical factors shaping P. delavayi distribution, and UVB-4 and annual precipitation were identified as the most critical for shaping P. rockii distribution. Under the scenario with a low concentration of greenhouse gas emissions (RCP2.6), the range of both species increased as global warming intensified; however, under the scenario with higher concentrations of emissions (RCP8.5), the suitable habitat range of P. delavayi decreased while P. rockii increased. Overall, our prediction showed that a shift in distribution of suitable habitat to higher elevations would gradually become more significant. The information gained from this study should provide a useful reference for implementing long-term conservation and management strategies for these species. Copyright © 2018. Published by Elsevier B.V.

  5. Predicting Wetland Distribution Changes under Climate Change and Human Activities in a Mid- and High-Latitude Region

    Directory of Open Access Journals (Sweden)

    Dandan Zhao

    2018-03-01

    Full Text Available Wetlands in the mid- and high-latitudes are particularly vulnerable to environmental changes and have declined dramatically in recent decades. Climate change and human activities are arguably the most important factors driving wetland distribution changes which will have important implications for wetland ecological functions and services. We analyzed the importance of driving variables for wetland distribution and investigated the relative importance of climatic factors and human activity factors in driving historical wetland distribution changes. We predicted wetland distribution changes under climate change and human activities over the 21st century using the Random Forest model in a mid- and high-latitude region of Northeast China. Climate change scenarios included three Representative Concentration Pathways (RCPs based on five general circulation models (GCMs downloaded from the Coupled Model Intercomparison Project, Phase 5 (CMIP5. The three scenarios (RCP 2.6, RCP 4.5, and RCP 8.5 predicted radiative forcing to peak at 2.6, 4.5, and 8.5 W/m2 by the 2100s, respectively. Our results showed that the variables with high importance scores were agricultural population proportion, warmness index, distance to water body, coldness index, and annual mean precipitation; climatic variables were given higher importance scores than human activity variables on average. Average predicted wetland area among three emission scenarios were 340,000 ha, 123,000 ha, and 113,000 ha for the 2040s, 2070s, and 2100s, respectively. Average change percent in predicted wetland area among three periods was greatest under the RCP 8.5 emission scenario followed by RCP 4.5 and RCP 2.6 emission scenarios, which were 78%, 64%, and 55%, respectively. Losses in predicted wetland distribution were generally around agricultural lands and expanded continually from the north to the whole region over time, while the gains were mostly associated with grasslands and water in the

  6. Moving Toward Climate Budgeting : Policy Note

    OpenAIRE

    World Bank Group

    2014-01-01

    Climate change action by countries - both mitigation measures and adaptation measures requires planning over a long horizon in the face of uncertainty as well as, for many governments, costly financing in the near term. While flows of international climate finance have grown in recent years, it has become ever clearer that countries need to consider all policy instruments. Climate change i...

  7. Predicting the distributions of predator (snow leopard) and prey (blue sheep) under climate change in the Himalaya.

    Science.gov (United States)

    Aryal, Achyut; Shrestha, Uttam Babu; Ji, Weihong; Ale, Som B; Shrestha, Sujata; Ingty, Tenzing; Maraseni, Tek; Cockfield, Geoff; Raubenheimer, David

    2016-06-01

    Future climate change is likely to affect distributions of species, disrupt biotic interactions, and cause spatial incongruity of predator-prey habitats. Understanding the impacts of future climate change on species distribution will help in the formulation of conservation policies to reduce the risks of future biodiversity losses. Using a species distribution modeling approach by MaxEnt, we modeled current and future distributions of snow leopard (Panthera uncia) and its common prey, blue sheep (Pseudois nayaur), and observed the changes in niche overlap in the Nepal Himalaya. Annual mean temperature is the major climatic factor responsible for the snow leopard and blue sheep distributions in the energy-deficient environments of high altitudes. Currently, about 15.32% and 15.93% area of the Nepal Himalaya are suitable for snow leopard and blue sheep habitats, respectively. The bioclimatic models show that the current suitable habitats of both snow leopard and blue sheep will be reduced under future climate change. The predicted suitable habitat of the snow leopard is decreased when blue sheep habitats is incorporated in the model. Our climate-only model shows that only 11.64% (17,190 km(2)) area of Nepal is suitable for the snow leopard under current climate and the suitable habitat reduces to 5,435 km(2) (reduced by 24.02%) after incorporating the predicted distribution of blue sheep. The predicted distribution of snow leopard reduces by 14.57% in 2030 and by 21.57% in 2050 when the predicted distribution of blue sheep is included as compared to 1.98% reduction in 2030 and 3.80% reduction in 2050 based on the climate-only model. It is predicted that future climate may alter the predator-prey spatial interaction inducing a lower degree of overlap and a higher degree of mismatch between snow leopard and blue sheep niches. This suggests increased energetic costs of finding preferred prey for snow leopards - a species already facing energetic constraints due to the

  8. Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling

    OpenAIRE

    Koo, Kyung; Patten, Bernard; Madden, Marguerite

    2015-01-01

    Alpine, subalpine and boreal tree species, of low genetic diversity and adapted to low optimal temperatures, are vulnerable to the warming effects of global climate change. The accurate prediction of these species’ distributions in response to climate change is critical for effective planning and management. The goal of this research is to predict climate change effects on the distribution of red spruce (Picea rubens Sarg.) in the Great Smoky Mountains National Park (GSMNP), eastern USA. Clim...

  9. Age and area predict patterns of species richness in pumice rafts contingent on oceanic climatic zone encountered.

    Science.gov (United States)

    Velasquez, Eleanor; Bryan, Scott E; Ekins, Merrick; Cook, Alex G; Hurrey, Lucy; Firn, Jennifer

    2018-05-01

    The theory of island biogeography predicts that area and age explain species richness patterns (or alpha diversity) in insular habitats. Using a unique natural phenomenon, pumice rafting, we measured the influence of area, age, and oceanic climate on patterns of species richness. Pumice rafts are formed simultaneously when submarine volcanoes erupt, the pumice clasts breakup irregularly, forming irregularly shaped pumice stones which while floating through the ocean are colonized by marine biota. We analyze two eruption events and more than 5,000 pumice clasts collected from 29 sites and three climatic zones. Overall, the older and larger pumice clasts held more species. Pumice clasts arriving in tropical and subtropical climates showed this same trend, where in temperate locations species richness (alpha diversity) increased with area but decreased with age. Beta diversity analysis of the communities forming on pumice clasts that arrived in different climatic zones showed that tropical and subtropical clasts transported similar communities, while species composition on temperate clasts differed significantly from both tropical and subtropical arrivals. Using these thousands of insular habitats, we find strong evidence that area and age but also climatic conditions predict the fundamental dynamics of species richness colonizing pumice clasts.

  10. Fine-spatial scale predictions of understory species using climate- and LiDAR-derived terrain and canopy metrics

    Science.gov (United States)

    Nijland, Wiebe; Nielsen, Scott E.; Coops, Nicholas C.; Wulder, Michael A.; Stenhouse, Gordon B.

    2014-01-01

    Food and habitat resources are critical components of wildlife management and conservation efforts. The grizzly bear (Ursus arctos) has diverse diets and habitat requirements particularly for understory plant species, which are impacted by human developments and forest management activities. We use light detection and ranging (LiDAR) data to predict the occurrence of 14 understory plant species relevant to bear forage and compare our predictions with more conventional climate- and land cover-based models. We use boosted regression trees to model each of the 14 understory species across 4435 km2 using occurrence (presence-absence) data from 1941 field plots. Three sets of models were fitted: climate only, climate and basic land and forest covers from Landsat 30-m imagery, and a climate- and LiDAR-derived model describing both the terrain and forest canopy. Resulting model accuracies varied widely among species. Overall, 8 of 14 species models were improved by including the LiDAR-derived variables. For climate-only models, mean annual precipitation and frost-free periods were the most important variables. With inclusion of LiDAR-derived attributes, depth-to-water table, terrain-intercepted annual radiation, and elevation were most often selected. This suggests that fine-scale terrain conditions affect the distribution of the studied species more than canopy conditions.

  11. Climatic, Edaphic Factors and Cropping History Help Predict Click Beetle (Coleoptera: Elateridae) (Agriotes spp.) Abundance.

    Science.gov (United States)

    Kozina, A; Lemic, D; Bazok, R; Mikac, K M; Mclean, C M; Ivezić, M; Igrc Barčić, J

    2015-01-01

    It is assumed that the abundance of Agriotes wireworms (Coleoptera: Elateridae) is affected by agro-ecological factors such as climatic and edaphic factors and the crop/previous crop grown at the sites investigated. The aim of this study, conducted in three different geographic counties in Croatia from 2007 to 2009, was to determine the factors that influence the abundance of adult click beetle of the species Agriotes brevis Cand., Agriotes lineatus (L.), Agriotes obscurus (L.), Agriotes sputator (L.), and Agriotes ustulatus Schall. The mean annual air temperature, total rainfall, percentage of coarse and fine sand, coarse and fine silt and clay, the soil pH, and humus were investigated as potential factors that may influence abundance. Adult click beetle emergence was monitored using sex pheromone traps (YATLORf and VARb3). Exploratory data analysis was preformed via regression tree models and regional differences in Agriotes species' abundance were predicted based on the agro-ecological factors measured. It was found that the best overall predictor of A. brevis abundance was the previous crop grown. Conversely, the best predictor of A. lineatus abundance was the current crop being grown and the percentage of humus. The best predictor of A. obscurus abundance was soil pH in KCl. The best predictor of A. sputator abundance was rainfall. Finally, the best predictors of A. ustulatus abundance were soil pH in KCl and humus. These results may be useful in regional pest control programs or for predicting future outbreaks of these species. © The Author 2015. Published by Oxford University Press on behalf of the Entomological Society of America.

  12. Effects of predicted climatic changes on distribution of organic contaminants in brackish water mesocosms

    Energy Technology Data Exchange (ETDEWEB)

    Ripszam, M., E-mail: matyas.ripszam@chem.umu.se [Department of Chemistry, Umea University, 901 87 Umeå (Sweden); Gallampois, C.M.J. [Department of Chemistry, Umea University, 901 87 Umeå (Sweden); Berglund, Å. [Department of Ecology and Environmental Sciences, Umeå University, 901 87 Umeå (Sweden); Larsson, H. [Umeå Marine Sciences Centre, Umeå University, Norrbyn, 905 71 Hörnefors (Sweden); Andersson, A. [Department of Ecology and Environmental Sciences, Umeå University, 901 87 Umeå (Sweden); Tysklind, M.; Haglund, P. [Department of Chemistry, Umea University, 901 87 Umeå (Sweden)

    2015-06-01

    Predicted consequences of future climate change in the northern Baltic Sea include increases in sea surface temperatures and terrestrial dissolved organic carbon (DOC) runoff. These changes are expected to alter environmental distribution of anthropogenic organic contaminants (OCs). To assess likely shifts in their distributions, outdoor mesocosms were employed to mimic pelagic ecosystems at two temperatures and two DOC concentrations, current: 15 °C and 4 mg DOC L{sup −1} and, within ranges of predicted increases, 18 °C and 6 mg DOC L{sup −1}, respectively. Selected organic contaminants were added to the mesocosms to monitor changes in their distribution induced by the treatments. OC partitioning to particulate matter and sedimentation were enhanced at the higher DOC concentration, at both temperatures, while higher losses and lower partitioning of OCs to DOC were observed at the higher temperature. No combined effects of higher temperature and DOC on partitioning were observed, possibly because of the balancing nature of these processes. Therefore, changes in OCs' fates may largely depend on whether they are most sensitive to temperature or DOC concentration rises. Bromoanilines, phenanthrene, biphenyl and naphthalene were sensitive to the rise in DOC concentration, whereas organophosphates, chlorobenzenes (PCBz) and polychlorinated biphenyls (PCBs) were more sensitive to temperature. Mitotane and diflufenican were sensitive to both temperature and DOC concentration rises individually, but not in combination. - Highlights: • More contaminants remained in the ecosystem at higher organic carbon levels. • More contaminants were lost in the higher temperature treatments. • The combined effects are competitive with respect to contaminant cycling. • The individual properties of each contaminant determine their respective fate.

  13. Effects of predicted climatic changes on distribution of organic contaminants in brackish water mesocosms

    International Nuclear Information System (INIS)

    Ripszam, M.; Gallampois, C.M.J.; Berglund, Å.; Larsson, H.; Andersson, A.; Tysklind, M.; Haglund, P.

    2015-01-01

    Predicted consequences of future climate change in the northern Baltic Sea include increases in sea surface temperatures and terrestrial dissolved organic carbon (DOC) runoff. These changes are expected to alter environmental distribution of anthropogenic organic contaminants (OCs). To assess likely shifts in their distributions, outdoor mesocosms were employed to mimic pelagic ecosystems at two temperatures and two DOC concentrations, current: 15 °C and 4 mg DOC L −1 and, within ranges of predicted increases, 18 °C and 6 mg DOC L −1 , respectively. Selected organic contaminants were added to the mesocosms to monitor changes in their distribution induced by the treatments. OC partitioning to particulate matter and sedimentation were enhanced at the higher DOC concentration, at both temperatures, while higher losses and lower partitioning of OCs to DOC were observed at the higher temperature. No combined effects of higher temperature and DOC on partitioning were observed, possibly because of the balancing nature of these processes. Therefore, changes in OCs' fates may largely depend on whether they are most sensitive to temperature or DOC concentration rises. Bromoanilines, phenanthrene, biphenyl and naphthalene were sensitive to the rise in DOC concentration, whereas organophosphates, chlorobenzenes (PCBz) and polychlorinated biphenyls (PCBs) were more sensitive to temperature. Mitotane and diflufenican were sensitive to both temperature and DOC concentration rises individually, but not in combination. - Highlights: • More contaminants remained in the ecosystem at higher organic carbon levels. • More contaminants were lost in the higher temperature treatments. • The combined effects are competitive with respect to contaminant cycling. • The individual properties of each contaminant determine their respective fate

  14. Characterization of low-level waste from the industrial sector, and near-term projection of waste volumes and types

    International Nuclear Information System (INIS)

    MacKenzie, D.R.

    1988-01-01

    A telephone survey of low-level waste generators has been carried out in order to make useful estimates of the volume and nature of the waste which the generators will be shipping for disposal when the compacts and states begin operating new disposal facilities. Emphasis of the survey was on the industrial sector, since there has been little information available on characteristics of industrial LLW. Ten large industrial generators shipping to Richland, ten shipping to Barnwell, and two whose wastes had previously been characterized by BNL were contacted. The waste volume shipped by these generators accounted for about two-thirds to three-quarters of the total industrial volume. Results are given in terms of the categories of LLW represented and of the chemical characteristics of the different wastes. Estimates by the respondents of their near-term waste volume projections are presented

  15. Characterization of low-level waste from the industrial sector, and near-term projection of waste volumes and types

    International Nuclear Information System (INIS)

    MacKenzie, D.R.

    1988-01-01

    A telephone survey of low-level waste generators has been carried out in order to make useful estimates of the volume and nature of the waste which the generators are shipping for disposal when the compacts and states begin operating new disposal facilities. Emphasis of the survey was on the industrial sector, since there has been little information available on characteristics of industrial LLW. Ten large industrial generators shipping to Richland, ten shipping to Barnwell, and two whose wastes had previously been characterized by BNL were contacted. The waste volume shipped by these generators accounted for about two-thirds to three-quarters of the total industrial volume. Results are given in terms of the categories of LLW represented and of the chemical characteristics of the different wastes. Estimates by the respondents of their near-term waste volume projections are presented

  16. Pathogen-Host Associations and Predicted Range Shifts of Human Monkeypox in Response to Climate Change in Central Africa

    Science.gov (United States)

    Thomassen, Henri A.; Fuller, Trevon; Asefi-Najafabady, Salvi; Shiplacoff, Julia A. G.; Mulembakani, Prime M.; Blumberg, Seth; Johnston, Sara C.; Kisalu, Neville K.; Kinkela, Timothée L.; Fair, Joseph N.; Wolfe, Nathan D.; Shongo, Robert L.; LeBreton, Matthew; Meyer, Hermann; Wright, Linda L.; Muyembe, Jean-Jacques; Buermann, Wolfgang; Okitolonda, Emile; Hensley, Lisa E.; Lloyd-Smith, James O.; Smith, Thomas B.; Rimoin, Anne W.

    2013-01-01

    Climate change is predicted to result in changes in the geographic ranges and local prevalence of infectious diseases, either through direct effects on the pathogen, or indirectly through range shifts in vector and reservoir species. To better understand the occurrence of monkeypox virus (MPXV), an emerging Orthopoxvirus in humans, under contemporary and future climate conditions, we used ecological niche modeling techniques in conjunction with climate and remote-sensing variables. We first created spatially explicit probability distributions of its candidate reservoir species in Africa's Congo Basin. Reservoir species distributions were subsequently used to model current and projected future distributions of human monkeypox (MPX). Results indicate that forest clearing and climate are significant driving factors of the transmission of MPX from wildlife to humans under current climate conditions. Models under contemporary climate conditions performed well, as indicated by high values for the area under the receiver operator curve (AUC), and tests on spatially randomly and non-randomly omitted test data. Future projections were made on IPCC 4th Assessment climate change scenarios for 2050 and 2080, ranging from more conservative to more aggressive, and representing the potential variation within which range shifts can be expected to occur. Future projections showed range shifts into regions where MPX has not been recorded previously. Increased suitability for MPX was predicted in eastern Democratic Republic of Congo. Models developed here are useful for identifying areas where environmental conditions may become more suitable for human MPX; targeting candidate reservoir species for future screening efforts; and prioritizing regions for future MPX surveillance efforts. PMID:23935820

  17. Use of a Prototype Airborne Separation Assurance System for Resolving Near-Term Conflicts During Autonomous Aircraft Operations

    Science.gov (United States)

    Barhydt, Richard; Eischeid, Todd M.; Palmer, Michael T.; Wing, David J.

    2003-01-01

    NASA is currently investigating a new concept of operations for the National Airspace System, designed to improve capacity while maintaining or improving current levels of safety. This concept, known as Distributed Air/Ground Traffic Management (DAGTM), allows appropriately equipped autonomous aircraft to maneuver freely for flight optimization while resolving conflicts with other traffic and staying out of special use airspace and hazardous weather. In order to perform these tasks, pilots use prototype conflict detection, prevention, and resolution tools, collectively known as an Airborne Separation Assurance System (ASAS). While ASAS would normally allow pilots to resolve conflicts before they become hazardous, evaluation of system performance in sudden, near-term conflicts is needed in order to determine concept feasibility. An experiment was conducted in NASA Langley's Air Traffic Operations Lab to evaluate the prototype ASAS for enabling pilots to resolve near-term conflicts and examine possible operational effects associated with the use of lower separation minimums. Sixteen commercial airline pilots flew a total of 32 traffic scenarios that required them to use prototype ASAS tools to resolve close range pop-up conflicts. Required separation standards were set at either 3 or 5 NM lateral spacing, with 1000 ft vertical separation being used for both cases. Reducing the lateral separation from 5 to 3 NM did not appear to increase operational risk, as indicated by the proximity to the intruder aircraft. Pilots performed better when they followed tactical guidance cues provided by ASAS than when they didn't follow the guidance. In an effort to improve compliance rate, ASAS design changes are currently under consideration. Further studies will of evaluate these design changes and consider integration issues between ASAS and existing Airborne Collision Avoidance Systems (ACAS).

  18. Potential predictability and forecast skill in ensemble climate forecast: a skill-persistence rule

    Science.gov (United States)

    Jin, Yishuai; Rong, Xinyao; Liu, Zhengyu

    2017-12-01

    This study investigates the factors relationship between the forecast skills for the real world (actual skill) and perfect model (perfect skill) in ensemble climate model forecast with a series of fully coupled general circulation model forecast experiments. It is found that the actual skill for sea surface temperature (SST) in seasonal forecast is substantially higher than the perfect skill on a large part of the tropical oceans, especially the tropical Indian Ocean and the central-eastern Pacific Ocean. The higher actual skill is found to be related to the higher observational SST persistence, suggesting a skill-persistence rule: a higher SST persistence in the real world than in the model could overwhelm the model bias to produce a higher forecast skill for the real world than for the perfect model. The relation between forecast skill and persistence is further proved using a first-order autoregressive model (AR1) analytically for theoretical solutions and numerically for analogue experiments. The AR1 model study shows that the skill-persistence rule is strictly valid in the case of infinite ensemble size, but could be distorted by sampling errors and non-AR1 processes. This study suggests that the so called "perfect skill" is model dependent and cannot serve as an accurate estimate of the true upper limit of real world prediction skill, unless the model can capture at least the persistence property of the observation.

  19. Predicting Impacts of Future Climate Change on the Distribution of the Widespread Conifer Platycladus orientalis.

    Directory of Open Access Journals (Sweden)

    Xian-Ge Hu

    Full Text Available Chinese thuja (Platycladus orientalis has a wide but fragmented distribution in China. It is an important conifer tree in reforestation and plays important roles in ecological restoration in the arid mountains of northern China. Based on high-resolution environmental data for current and future scenarios, we modeled the present and future suitable habitat for P. orientalis, evaluated the importance of environmental factors in shaping the species' distribution, and identified regions of high risk under climate change scenarios. The niche models showed that P. orientalis has suitable habitat of ca. 4.2×106 km2 across most of eastern China and identified annual temperature, monthly minimum and maximum ultraviolet-B radiation and wet-day frequency as the critical factors shaping habitat availability for P. orientalis. Under the low concentration greenhouse gas emissions scenario, the range of the species may increase as global warming intensifies; however, under the higher concentrations of emissions scenario, we predicted a slight expansion followed by contraction in distribution. Overall, the range shift to higher latitudes and elevations would become gradually more significant. The information gained from this study should be an useful reference for implementing long-term conservation and management strategies for the species.

  20. Predicting organismal vulnerability to climate warming: roles of behaviour, physiology and adaptation

    Science.gov (United States)

    Huey, Raymond B.; Kearney, Michael R.; Krockenberger, Andrew; Holtum, Joseph A. M.; Jess, Mellissa; Williams, Stephen E.

    2012-01-01

    A recently developed integrative framework proposes that the vulnerability of a species to environmental change depends on the species' exposure and sensitivity to environmental change, its resilience to perturbations and its potential to adapt to change. These vulnerability criteria require behavioural, physiological and genetic data. With this information in hand, biologists can predict organisms most at risk from environmental change. Biologists and managers can then target organisms and habitats most at risk. Unfortunately, the required data (e.g. optimal physiological temperatures) are rarely available. Here, we evaluate the reliability of potential proxies (e.g. critical temperatures) that are often available for some groups. Several proxies for ectotherms are promising, but analogous ones for endotherms are lacking. We also develop a simple graphical model of how behavioural thermoregulation, acclimation and adaptation may interact to influence vulnerability over time. After considering this model together with the proxies available for physiological sensitivity to climate change, we conclude that ectotherms sharing vulnerability traits seem concentrated in lowland tropical forests. Their vulnerability may be exacerbated by negative biotic interactions. Whether tropical forest (or other) species can adapt to warming environments is unclear, as genetic and selective data are scant. Nevertheless, the prospects for tropical forest ectotherms appear grim. PMID:22566674

  1. Predicting Impacts of Climate Change on the Aboveground Carbon Sequestration Rate of a Temperate Forest in Northeastern China

    Science.gov (United States)

    Ma, Jun; Hu, Yuanman; Bu, Rencang; Chang, Yu; Deng, Huawei; Qin, Qin

    2014-01-01

    The aboveground carbon sequestration rate (ACSR) reflects the influence of climate change on forest dynamics. To reveal the long-term effects of climate change on forest succession and carbon sequestration, a forest landscape succession and disturbance model (LANDIS Pro7.0) was used to simulate the ACSR of a temperate forest at the community and species levels in northeastern China based on both current and predicted climatic data. On the community level, the ACSR of mixed Korean pine hardwood forests and mixed larch hardwood forests, fluctuated during the entire simulation, while a large decline of ACSR emerged in interim of simulation in spruce-fir forest and aspen-white birch forests, respectively. On the species level, the ACSR of all conifers declined greatly around 2070s except for Korean pine. The ACSR of dominant hardwoods in the Lesser Khingan Mountains area, such as Manchurian ash, Amur cork, black elm, and ribbed birch fluctuated with broad ranges, respectively. Pioneer species experienced a sharp decline around 2080s, and they would finally disappear in the simulation. The differences of the ACSR among various climates were mainly identified in mixed Korean pine hardwood forests, in all conifers, and in a few hardwoods in the last quarter of simulation. These results indicate that climate warming can influence the ACSR in the Lesser Khingan Mountains area, and the largest impact commonly emerged in the A2 scenario. The ACSR of coniferous species experienced higher impact by climate change than that of deciduous species. PMID:24763409

  2. Predicting impacts of climate change on the aboveground carbon sequestration rate of a temperate forest in northeastern China.

    Science.gov (United States)

    Ma, Jun; Hu, Yuanman; Bu, Rencang; Chang, Yu; Deng, Huawei; Qin, Qin

    2014-01-01

    The aboveground carbon sequestration rate (ACSR) reflects the influence of climate change on forest dynamics. To reveal the long-term effects of climate change on forest succession and carbon sequestration, a forest landscape succession and disturbance model (LANDIS Pro7.0) was used to simulate the ACSR of a temperate forest at the community and species levels in northeastern China based on both current and predicted climatic data. On the community level, the ACSR of mixed Korean pine hardwood forests and mixed larch hardwood forests, fluctuated during the entire simulation, while a large decline of ACSR emerged in interim of simulation in spruce-fir forest and aspen-white birch forests, respectively. On the species level, the ACSR of all conifers declined greatly around 2070s except for Korean pine. The ACSR of dominant hardwoods in the Lesser Khingan Mountains area, such as Manchurian ash, Amur cork, black elm, and ribbed birch fluctuated with broad ranges, respectively. Pioneer species experienced a sharp decline around 2080s, and they would finally disappear in the simulation. The differences of the ACSR among various climates were mainly identified in mixed Korean pine hardwood forests, in all conifers, and in a few hardwoods in the last quarter of simulation. These results indicate that climate warming can influence the ACSR in the Lesser Khingan Mountains area, and the largest impact commonly emerged in the A2 scenario. The ACSR of coniferous species experienced higher impact by climate change than that of deciduous species.

  3. Predicting impacts of climate change on the aboveground carbon sequestration rate of a temperate forest in northeastern China.

    Directory of Open Access Journals (Sweden)

    Jun Ma

    Full Text Available The aboveground carbon sequestration rate (ACSR reflects the influence of climate change on forest dynamics. To reveal the long-term effects of climate change on forest succession and carbon sequestration, a forest landscape succession and disturbance model (LANDIS Pro7.0 was used to simulate the ACSR of a temperate forest at the community and species levels in northeastern China based on both current and predicted climatic data. On the community level, the ACSR of mixed Korean pine hardwood forests and mixed larch hardwood forests, fluctuated during the entire simulation, while a large decline of ACSR emerged in interim of simulation in spruce-fir forest and aspen-white birch forests, respectively. On the species level, the ACSR of all conifers declined greatly around 2070s except for Korean pine. The ACSR of dominant hardwoods in the Lesser Khingan Mountains area, such as Manchurian ash, Amur cork, black elm, and ribbed birch fluctuated with broad ranges, respectively. Pioneer species experienced a sharp decline around 2080s, and they would finally disappear in the simulation. The differences of the ACSR among various climates were mainly identified in mixed Korean pine hardwood forests, in all conifers, and in a few hardwoods in the last quarter of simulation. These results indicate that climate warming can influence the ACSR in the Lesser Khingan Mountains area, and the largest impact commonly emerged in the A2 scenario. The ACSR of coniferous species experienced higher impact by climate change than that of deciduous species.

  4. Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system

    Science.gov (United States)

    Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.

    2018-04-01

    The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their

  5. Analysis and prediction of reference evapotranspiration with climate change in Xiangjiang River Basin, China

    Directory of Open Access Journals (Sweden)

    Xin-e Tao

    2015-10-01

    Full Text Available Reference evapotranspiration (ET0 is often used to estimate actual evapotranspiration in water balance studies. In this study, the present and future spatial distributions and temporal trends of ET0 in the Xiangjiang River Basin (XJRB in China were analyzed. ET0 during the period from 1961 to 2010 was calculated with historical meteorological data using the FAO Penman-Monteith (FAO P-M method, while ET0 during the period from 2011 to 2100 was downscaled from the Coupled Model Intercomparison Project Phase 5 (CMIP5 outputs under two emission scenarios, representative concentration pathway 4.5 and representative concentration pathway 8.5 (RCP45 and RCP85, using the statistical downscaling model (SDSM. The spatial distribution and temporal trend of ET0 were interpreted with the inverse distance weighted (IDW method and Mann-Kendall test method, respectively. Results show that: (1 the mean annual ET0 of the XJRB is 1 006.3 mm during the period from 1961 to 2010, and the lowest and highest values are found in the northeast and northwest parts due to the high latitude and spatial distribution of climatic factors, respectively; (2 the SDSM performs well in simulating the present ET0 and can be used to predict the future ET0 in the XJRB; and (3 CMIP5 predicts upward trends in annual ET0 under the RCP45 and RCP85 scenarios during the period from 2011 to 2100. Compared with the reference period (1961–1990, ET0 increases by 9.8%, 12.6%, and 15.6% under the RCP45 scenario and 10.2%, 19.1%, and 27.3% under the RCP85 scenario during the periods from 2011 to 2040, from 2041 to 2070, and from 2071 to 2100, respectively. The predicted increasing ET0 under the RCP85 scenario is greater than that under the RCP45 scenario during the period from 2011 to 2100.

  6. Predicting tree biomass growth in the temperate-boreal ecotone: is tree size, age, competition or climate response most important?

    Science.gov (United States)

    Foster, Jane R.; Finley, Andrew O.; D'Amato, Anthony W.; Bradford, John B.; Banerjee, Sudipto

    2016-01-01

    As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2and thereby slow rising CO2 concentrations. Forests’ ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals’ size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species likeAcer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92–95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth

  7. Predicting tree biomass growth in the temperate-boreal ecotone: Is tree size, age, competition, or climate response most important?

    Science.gov (United States)

    Foster, Jane R; Finley, Andrew O; D'Amato, Anthony W; Bradford, John B; Banerjee, Sudipto

    2016-06-01

    As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2 and thereby slow rising CO2 concentrations. Forests' ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals' size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species like Acer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92-95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses

  8. Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

    Energy Technology Data Exchange (ETDEWEB)

    Bhatt, Uma S. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Atmospheric Sciences; Wackerbauer, Renate [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Physics; Polyakov, Igor V. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Atmospheric Sciences; Newman, David E. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Physics; Sanchez, Raul E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Fusion Energy Division; Univ. Carlos III de Madrid (Spain)

    2015-11-13

    The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were applied to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.

  9. Understanding the dynamics in distribution of invasive alien plant species under predicted climate change in Western Himalaya.

    Science.gov (United States)

    Thapa, Sunil; Chitale, Vishwas; Rijal, Srijana Joshi; Bisht, Neha; Shrestha, Bharat Babu

    2018-01-01

    Invasive alien plant species (IAPS) can pose severe threats to biodiversity and stability of native ecosystems, therefore, predicting the distribution of the IAPS plays a crucial role in effective planning and management of ecosystems. In the present study, we use Maximum Entropy (MaxEnt) modelling approach to predict the potential of distribution of eleven IAPS under future climatic conditions under RCP 2.6 and RCP 8.5 in part of Kailash sacred landscape region in Western Himalaya. Based on the model predictions, distribution of most of these invasive plants is expected to expand under future climatic scenarios, which might pose a serious threat to the native ecosystems through competition for resources in the study area. Native scrublands and subtropical needle-leaved forests will be the most affected ecosystems by the expansion of these IAPS. The present study is first of its kind in the Kailash Sacred Landscape in the field of invasive plants and the predictions of potential distribution under future climatic conditions from our study could help decision makers in planning and managing these forest ecosystems effectively.

  10. Decadal Recruitment and Mortality of Ponderosa pine Predicted for the 21st Century Under five Downscaled Climate Change Scenarios

    Science.gov (United States)

    Ironside, K. E.; Cole, K. L.; Eischeid, J. K.; Garfin, G. M.; Shaw, J. D.; Cobb, N. S.

    2008-12-01

    Ponderosa pine (Pinus ponderosa var. scopulorum) is the dominant conifer in higher elevation regions of the southwestern United States. Because this species is so prominent, southwestern montane ecosystems will be significantly altered if this species is strongly affected by future climate changes. These changes could be highly challenging for land management agencies. In order to model the consequences of future climates, 20th Century recruitment events and mortality for ponderosa pine were characterized using measures of seasonal water balance (precipitation - potential evapotranspiration). These relationships, assuming they will remain unchanged, were then used to predict 21st Century changes in ponderosa pine occurrence in the southwest. Twenty-one AR4 IPCC General Circulation Model (GCM) A1B simulation results were ranked on their ability to simulate the later 20th Century (1950-2000 AD) precipitation seasonality, spatial patterns, and quantity in the western United States. Among the top ranked GCMs, five were selected for downscaling to a 4 km grid that represented a range in predictions in terms of changes in water balance. Predicted decadal changes in southwestern ponderosa pine for the 21st Century for these five climate change scenarios were calculated using a multiple quadratic logistic regression model. Similar models of other western tree species (Pinus edulis, Yucca brevifolia) predicted severe contractions, especially in the southern half of their ranges. However, the results for Ponderosa pine suggested future expansions throughout its range to both higher and lower elevations, as well as very significant expansions northward.

  11. Factors predicting team climate, and its relationship with quality of care in general practice

    Directory of Open Access Journals (Sweden)

    Eccles Martin P

    2009-08-01

    Full Text Available Abstract Background Quality of care in general practice may be affected by the team climate perceived by its health and non-health professionals. Better team working is thought to lead to higher effectiveness and quality of care. However, there is limited evidence available on what affects team functioning and its relationship with quality of care in general practice. This study aimed to explore individual and practice factors that were associated with team climate, and to explore the relationship between team climate and quality of care. Methods Cross sectional survey of a convenience sample of 14 general practices and their staff in South Tyneside in the northeast of England. Team climate was measured using the short version of Team Climate Inventory (TCI questionnaire. Practice characteristics were collected during a structured interview with practice managers. Quality was measured using the practice Quality and Outcome Framework (QOF scores. Results General Practitioners (GP had a higher team climate scores compared to other professionals. Individual's gender and tenure, and number of GPs in the practice were significantly predictors of a higher team climate. There was no significant correlation between mean practice team climate scores (or subscales with QOF scores. Conclusion The absence of a relationship between a measure of team climate and quality of care in this exploratory study may be due to a number of methodological problems. Further research is required to explore how to best measure team functioning and its relationship with quality of care.

  12. Factors predicting team climate, and its relationship with quality of care in general practice.

    Science.gov (United States)

    Goh, Teik T; Eccles, Martin P; Steen, Nick

    2009-08-04

    Quality of care in general practice may be affected by the team climate perceived by its health and non-health professionals. Better team working is thought to lead to higher effectiveness and quality of care. However, there is limited evidence available on what affects team functioning and its relationship with quality of care in general practice. This study aimed to explore individual and practice factors that were associated with team climate, and to explore the relationship between team climate and quality of care. Cross sectional survey of a convenience sample of 14 general practices and their staff in South Tyneside in the northeast of England. Team climate was measured using the short version of Team Climate Inventory (TCI) questionnaire. Practice characteristics were collected during a structured interview with practice managers. Quality was measured using the practice Quality and Outcome Framework (QOF) scores. General Practitioners (GP) had a higher team climate scores compared to other professionals. Individual's gender and tenure, and number of GPs in the practice were significantly predictors of a higher team climate. There was no significant correlation between mean practice team climate scores (or subscales) with QOF scores. The absence of a relationship between a measure of team climate and quality of care in this exploratory study may be due to a number of methodological problems. Further research is required to explore how to best measure team functioning and its relationship with quality of care.

  13. Modelling changes to electricity demand load duration curves as a consequence of predicted climate change for Australia

    International Nuclear Information System (INIS)

    Thatcher, Marcus J.

    2007-01-01

    In this paper, we describe a method for constructing regional electricity demand data sets at 30 min intervals, which are consistent with climate change scenarios. Specifically, we modify a commonly used linear regression model between regional electricity demand and climate to also describe intraday variability in demand so that regional load duration curves (LDCs) can be predicted. The model is evaluated for four different Australian states that are participants in the Australian National Electricity Market (NEM) and the resultant data sets are found to reproduce each state's LDCs with reasonable accuracy. We also apply the demand model to CSIRO's Mk 3 global climate model data sets that have been downscaled to 60 km resolution using CSIRO's conformal-cubic atmospheric model to estimate how LDCs change as a consequence of a 1 C increase in the average temperature of Australian state capital cities. These regional electricity demand data sets are then useful for economic modelling of electricity markets such as the NEM. (author)

  14. Formation of Valley Networks in a Cold and Icy Early Mars Climate: Predictions for Erosion Rates and Channel Morphology

    Science.gov (United States)

    Cassanelli, J.

    2017-12-01

    Mars is host to a diverse array of valley networks, systems of linear-to-sinuous depressions which are widely distributed across the surface and which exhibit branching patterns similar to the dendritic drainage patterns of terrestrial fluvial systems. Characteristics of the valley networks are indicative of an origin by fluvial activity, providing among the most compelling evidence for the past presence of flowing liquid water on the surface of Mars. Stratigraphic and crater age dating techniques suggest that the formation of the valley networks occurred predominantly during the early geologic history of Mars ( 3.7 Ga). However, whether the valley networks formed predominantly by rainfall in a relatively warm and wet early Mars climate, or by snowmelt and episodic rainfall in an ambient cold and icy climate, remains disputed. Understanding the formative environment of the valley networks will help distinguish between these warm and cold end-member early Mars climate models. Here we test a conceptual model for channel incision and evolution under cold and icy conditions with a substrate characterized by the presence of an ice-free dry active layer and subjacent ice-cemented regolith, similar to that found in the Antarctic McMurdo Dry Valleys. We implement numerical thermal models, quantitative erosion and transport estimates, and morphometric analyses in order to outline predictions for (1) the precise nature and structure of the substrate, (2) fluvial erosion/incision rates, and (3) channel morphology. Model predictions are compared against morphologic and morphometric observational data to evaluate consistency with the assumed cold climate scenario. In the cold climate scenario, the substrate is predicted to be characterized by a kilometers-thick globally-continuous cryosphere below a 50-100 meter thick desiccated ice-free zone. Initial results suggest that, with the predicted substrate structure, fluvial channel erosion and morphology in a cold early Mars

  15. 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.

  16. A universal model for predicting human migration under climate change: examining future sea level rise in Bangladesh

    Science.gov (United States)

    Frankel Davis, Kyle; Bhattachan, Abinash; D’Odorico, Paolo; Suweis, Samir

    2018-06-01

    Climate change is expected to impact the habitability of many places around the world in significant and unprecedented ways in the coming decades. While previous studies have provided estimates of populations potentially exposed to various climate impacts, little work has been done to assess the number of people that may actually be displaced or where they will choose to go. Here we modify a diffusion-based model of human mobility in combination with population, geographic, and climatic data to estimate the sources, destinations, and flux of potential migrants as driven by sea level rise (SLR) in Bangladesh in the years 2050 and 2100. Using only maps of population and elevation, we predict that 0.9 million people (by year 2050) to 2.1 million people (by year 2100) could be displaced by direct inundation and that almost all of this movement will occur locally within the southern half of the country. We also find that destination locations should anticipate substantial additional demands on jobs (594 000), housing (197 000), and food (783 × 109 calories) by mid-century as a result of those displaced by SLR. By linking the sources of migrants displaced by SLR with their likely destinations, we demonstrate an effective approach for predicting climate-driven migrant flows, especially in data-limited settings.

  17. Predicting unprecedented dengue outbreak using imported cases and climatic factors in Guangzhou, 2014.

    Directory of Open Access Journals (Sweden)

    Shaowei Sang

    2015-05-01

    Full Text Available Dengue is endemic in more than 100 countries, mainly in tropical and subtropical regions, and the incidence has increased 30-fold in the past 50 years. The situation of dengue in China has become more and more severe, with an unprecedented dengue outbreak hitting south China in 2014. Building a dengue early warning system is therefore urgent and necessary for timely and effective response.In the study we developed a time series Poisson multivariate regression model using imported dengue cases, local minimum temperature and accumulative precipitation to predict the dengue occurrence in four districts of Guangzhou, China. The time series data were decomposed into seasonal, trend and remainder components using a seasonal-trend decomposition procedure based on loess (STL. The time lag of climatic factors included in the model was chosen based on Spearman correlation analysis. Autocorrelation, seasonality and long-term trend were controlled in the model. A best model was selected and validated using Generalized Cross Validation (GCV score and residual test. The data from March 2006 to December 2012 were used to develop the model while the data from January 2013 to September 2014 were employed to validate the model. Time series Poisson model showed that imported cases in the previous month, minimum temperature in the previous month and accumulative precipitation with three month lags could project the dengue outbreaks occurred in 2013 and 2014 after controlling the autocorrelation, seasonality and long-term trend.Together with the sole transmission vector Aedes albopictus, imported cases, monthly minimum temperature and monthly accumulative precipitation may be used to develop a low-cost effective early warning system.

  18. Better predictions, better allocations: scientific advances and adaptation to climate change.

    Science.gov (United States)

    Freeman, Mark C; Groom, Ben; Zeckhauser, Richard J

    2015-11-28

    Climate science initially aspired to improve understanding of what the future would bring, and thereby produce appropriate public policies and effective international climate agreements. If that hope is dashed, as now seems probable, effective policies for adapting to climate change become critical. Climate science assumes new responsibilities by helping to foster more appropriate adaptation measures, which might include shifting modes or locales of production. This theoretical article focuses on two broader tools: consumption smoothing in response to the risk of future losses, and physical adaptation measures to reduce potential damages. It shows that informative signals on the effects of climate change facilitate better decisions on the use of each tool, thereby increasing social welfare. © 2015 The Author(s).

  19. Correlation of spatial climate/weather maps and the advantages of using the Mahalanobis metric in predictions

    OpenAIRE

    Stephenson, D. B.

    2011-01-01

    he skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the var...

  20. Decadal prediction skill in the ocean with surface nudging in the IPSL-CM5A-LR climate model

    OpenAIRE

    Mignot , Juliette; García-Serrano , Javier; Swingedouw , Didier; Germe , Agathe; Nguyen , Sébastien; Ortega , Pablo; Guilyardi , Éric; Ray , Sulagna

    2016-01-01

    International audience; Two decadal prediction ensembles, based on the same climate model (IPSL-CM5A-LR) and the same surface nudging initialization strategy are analyzed and compared with a focus on upper-ocean variables in different regions of the globe. One ensemble consists of 3-member hindcasts launched every year since 1961 while the other ensemble benefits from 9 members but with start dates only every 5 years. Analysis includes anomaly correlation coefficients and root mean square err...

  1. Using the Terrestrial Observation and Prediction System (TOPS) to Analyze Impacts of Climate Change on Ecosystems within Northern California Climate Regions

    Science.gov (United States)

    Pitts, K.; Little, M.; Loewenstein, M.; Iraci, L. T.; Milesi, C.; Schmidt, C.; Skiles, J. W.

    2011-12-01

    The projected impacts of climate change on Northern California ecosystems using model outputs from the Terrestrial Observation and Prediction System (TOPS) for the period 1950-2099 based on 1km downscaled climate data from the Geophysical Fluid Dynamics Laboratory (GFDL) model are analyzed in this study. The impacts are analyzed for the Special Report Emissions Scenarios (SRES) A1B and A2, both maintaining present levels of urbanization constant and under projected urban expansion. The analysis is in support of the Climate Adaptation Science Investigation at NASA Ames Research Center. A statistical analysis is completed for time series of temperature, precipitation, gross primary productivity (GPP), evapotranspiration, soil runoff, and vapor pressure deficit. Trends produced from this analysis show that increases in maximum and minimum temperatures lead to declines in peak GPP, length of growing seasons, and overall declines in runoff within the watershed. For Northern California, GPP is projected under the A2 scenario to decrease by 18-25% by the 2090 decade as compared to the 2000 decade. These trends indicate a higher risk to crop production and other ecosystem services, as conditions would be less hospitable to vegetation growth. The increase in dried out vegetation would then lead to a higher risk of wildfire and mudslides in the mountainous regions.

  2. Deficiencies and possibilities for long-lead coupled climate prediction of the Western North Pacific-East Asian summer monsoon

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Sun-Seon; Ha, Kyung-Ja [Pusan National University, Division of Earth Environmental System, Busan (Korea, Republic of); Lee, June-Yi; Wang, Bin [University of Hawaii, Department of Meteorology and International Pacific Research Center, Honolulu, HI (United States); Schemm, Jae Kyung E. [Climate Prediction Center/NCEP, Camp Springs, MD (United States)

    2011-03-15

    Long-lead prediction of waxing and waning of the Western North Pacific (WNP)-East Asian (EA) summer monsoon (WNP-EASM) precipitation is a major challenge in seasonal time-scale climate prediction. In this study, deficiencies and potential for predicting the WNP-EASM precipitation and circulation one or two seasons ahead were examined using retrospective forecast data for the 26-year period of 1981-2006 from two operational couple models which are the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) and the Bureau of Meteorology Research Center (BMRC) Predictive Ocean-Atmosphere Model for Australia (POAMA). While both coupled models have difficulty in predicting summer mean precipitation anomalies over the region of interest, even for a 0-month lead forecast, they are capable of predicting zonal wind anomalies at 850 hPa several months ahead and, consequently, satisfactorily predict summer monsoon circulation indices for the EA region (EASMI) and for the WNP region (WNPSMI). It should be noted that the two models' multi-model ensemble (MME) reaches 0.40 of the correlation skill for the EASMI with a January initial condition and 0.75 for the WNPSMI with a February initial condition. Further analysis indicates that prediction reliability of the EASMI is related not only to the preceding El Nino and Southern Oscillation (ENSO) but also to simultaneous local SST variability. On other hand, better prediction of the WNPSMI is accompanied by a more realistic simulation of lead-lag relationship between the index and ENSO. It should also be noted that current coupled models have difficulty in capturing the interannual variability component of the WNP-EASM system which is not correlated with typical ENSO variability. To improve the long-lead seasonal prediction of the WNP-EASM precipitation, a statistical postprocessing was developed based on the multiple linear regression method. The method utilizes the MME prediction of the EASMI and

  3. Near-term implications of a ban on new coal-fired power plants in the United States.

    Science.gov (United States)

    Newcomer, Adam; Apt, Jay

    2009-06-01

    Large numbers of proposed new coal power generators in the United States have been canceled, and some states have prohibited new coal power generators. We examine the effects on the U.S. electric power system of banning the construction of coal-fired electricity generators, which has been proposed as a means to reduce U.S. CO2 emissions. The model simulates load growth, resource planning, and economic dispatch of the Midwest Independent Transmission System Operator (ISO), Inc., Electric Reliability Council of Texas (ERCOT), and PJM under a ban on new coal generation and uses an economic dispatch model to calculate the resulting changes in dispatch order, CO2 emissions, and fuel use under three near-term (until 2030) future electric power sector scenarios. A national ban on new coal-fired power plants does not lead to CO2 reductions of the scale required under proposed federal legislation such as Lieberman-Warner but would greatly increase the fraction of time when natural gas sets the price of electricity, even with aggressive wind and demand response policies.

  4. Feasibility Study for a Near Term Demonstration of Laser-Sail Propulsion from the Ground to Low Earth Orbit

    Science.gov (United States)

    Montgomery, Edward E., IV; Johnson, Les; Thomas, Herbert D.

    2016-01-01

    This paper adds to the body of research related to the concept of propellant-less in-space propulsion utilizing an external high energy laser (HEL) to provide momentum to an ultra-lightweight (gossamer) spacecraft. It has been suggested that the capabilities of Space Situational Awareness assets and the advanced analytical tools available for fine resolution orbit determination make it possible to investigate the practicalities of a ground to Low Earth Orbit (LEO) demonstration at delivered power levels that only illuminate a spacecraft without causing damage to it. The degree to which this can be expected to produce a measurable change in the orbit of a low ballistic coefficient spacecraft is investigated. Key system characteristics and estimated performance are derived for a near term mission opportunity involving the LightSail 2 spacecraft and laser power levels modest in comparison to those proposed previously by Forward, Landis, or Marx. [1,2,3] A more detailed investigation of accessing LightSail 2 from Santa Rosa Island on Eglin Air Force Base on the United States coast of the Gulf of Mexico is provided to show expected results in a specific case.

  5. HPS: A space fission power system suitable for near-term, low-cost lunar and planetary bases

    International Nuclear Information System (INIS)

    Houts, M.G.; Poston, D.I.; Ranken, W.A.

    1996-01-01

    Near-term, low-cost space fission power systems can enhance the feasibility and utility of lunar and planetary bases. One such system, the Heatpipe Power System (HPS), is described in this paper. The HPS draws on 40 yr of United States and international experience to enable a system that can be developed in <5 yr at a cost of <$100M. Total HPS mass is <600 kg at 5 kWe and <2000 kg at 50 kWe, assuming that thermoelectric power conversion is used. More advanced power conversion systems could reduce system mass significantly. System mass for planetary surface systems also may be reduced (1) if indigenous material is used for radiation shielding and (2) because of the positive effect of the gravitational field on heatpipe operation. The HPS is virtually non-radioactive at launch and is passively subcritical during all credible launch accidents. Full-system electrically heated testing is possible, and a ground nuclear power test is not needed for flight qualification. Fuel burnup limits are not reached for several decades, thus giving the system long-life potential

  6. Cryogenic distillation: a fuel enrichment system for near-term tokamak-type D-T fusion reactors

    International Nuclear Information System (INIS)

    Misra, B.; Davis, J.F.

    1980-02-01

    The successful operation and economic viability of deuterium-tritium- (D-T-) fueled tokamak-type commercial power fusion reactors will depend to a large extent on the development of reliable tritium-containment and fuel-recycle systems. Of the many operating steps in the fuel recycle scheme, separation or enrichment of the isotropic species of hydrogen by cryogenic distillation is one of the most important. A parametric investigation was carried out to study the effects of the various operating conditions and the composition of the spent fuel on the degree of separation. A computer program was developed for the design and analysis of a system of interconnected distillation columns for isotopic separation such that the requirements of near-term D-T-fueled reactors are met. The analytical results show that a distillation cascade consisting of four columns is capable of reprocessing spent fuel varying over a wide range of compositions to yield reinjection-grade fuel with essentially unlimited D/T ratio

  7. A Bayesian posterior predictive framework for weighting ensemble regional climate models

    Directory of Open Access Journals (Sweden)

    Y. Fan

    2017-06-01

    Full Text Available We present a novel Bayesian statistical approach to computing model weights in climate change projection ensembles in order to create probabilistic projections. The weight of each climate model is obtained by weighting the current day observed data under the posterior distribution admitted under competing climate models. We use a linear model to describe the model output and observations. The approach accounts for uncertainty in model bias, trend and internal variability, including error in the observations used. Our framework is general, requires very little problem-specific input, and works well with default priors. We carry out cross-validation checks that confirm that the method produces the correct coverage.

  8. Toward Process-resolving Synthesis and Prediction of Arctic Climate Change Using the Regional Arctic System Model

    Science.gov (United States)

    Maslowski, W.

    2017-12-01

    The Regional Arctic System Model (RASM) has been developed to better understand the operation of Arctic System at process scale and to improve prediction of its change at a spectrum of time scales. RASM is a pan-Arctic, fully coupled ice-ocean-atmosphere-land model with marine biogeochemistry extension to the ocean and sea ice models. The main goal of our research is to advance a system-level understanding of critical processes and feedbacks in the Arctic and their links with the Earth System. The secondary, an equally important objective, is to identify model needs for new or additional observations to better understand such processes and to help constrain models. Finally, RASM has been used to produce sea ice forecasts for September 2016 and 2017, in contribution to the Sea Ice Outlook of the Sea Ice Prediction Network. Future RASM forecasts, are likely to include increased resolution for model components and ecosystem predictions. Such research is in direct support of the US environmental assessment and prediction needs, including those of the U.S. Navy, Department of Defense, and the recent IARPC Arctic Research Plan 2017-2021. In addition to an overview of RASM technical details, selected model results are presented from a hierarchy of climate models together with available observations in the region to better understand potential oceanic contributions to polar amplification. RASM simulations are analyzed to evaluate model skill in representing seasonal climatology as well as interannual and multi-decadal climate variability and predictions. Selected physical processes and resulting feedbacks are discussed to emphasize the need for fully coupled climate model simulations, high model resolution and sensitivity of simulated sea ice states to scale dependent model parameterizations controlling ice dynamics, thermodynamics and coupling with the atmosphere and ocean.

  9. Monthly Total Precipitation Observation for Climate Prediction Center (CPC)Forecast Divisions

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This ASCII dataset contains monthly total precipitation for 102 Forecast Divisions within the conterminous U.S. It is derived from the monthly NCDC climate division...

  10. Are They Listening? Parental Social Coaching and Parenting Emotional Climate Predict Adolescent Receptivity.

    Science.gov (United States)

    Gregson, Kim D; Erath, Stephen A; Pettit, Gregory S; Tu, Kelly M

    2016-12-01

    Associations linking parenting emotional climate and quality of parental social coaching with young adolescents' receptivity to parental social coaching were examined (N = 80). Parenting emotional climate was assessed with adolescent-reported parental warmth and hostility. Quality of parental social coaching (i.e., prosocial advice, benign framing) was assessed via parent-report and behavioral observations during a parent-adolescent discussion about negative peer evaluation. An adolescent receptivity latent variable score was derived from observations of adolescents' behavior during the discussion, change in adolescents' peer response plan following the discussion, and adolescent-reported tendency to seek social advice from the parent. Parenting climate moderated associations between coaching and receptivity: Higher quality coaching was associated with greater receptivity in the context of a more positive climate. Analyses suggested a stronger association between coaching and receptivity among younger compared to older adolescents. © 2015 The Authors. Journal of Research on Adolescence © 2015 Society for Research on Adolescence.

  11. Monthly Mean Temperature Observation for Climate Prediction Center (CPC) Forecast Divisions

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This ASCII dataset contains monthly mean temperatures for 102 Forecast Divisions within the conterminous U.S. and is derived from the monthly NCDC climate division...

  12. Factors predicting team climate, and its relationship with quality of care in general practice

    OpenAIRE

    Goh, Teik T; Eccles, Martin P; Steen, Nick

    2009-01-01

    Abstract Background Quality of care in general practice may be affected by the team climate perceived by its health and non-health professionals. Better team working is thought to lead to higher effectiveness and quality of care. However, there is limited evidence available on what affects team functioning and its relationship with quality of care in general practice. This study aimed to explore individual and practice factors that were associated with team climate, and to explore the relatio...

  13. [Prediction of the suitable distribution and responses to climate change of Elaeagnus mollis in Shanxi Province, China].

    Science.gov (United States)

    Zhang, Yin Bo; Gao, Chen Hong; Qin, Hao

    2018-04-01

    Understanding the responses of the habitats of endangered species to climate change is of great significance for biodiversity conservation and the maintenance of the integrity of ecosystem function. In this study, the potential suitable distribution habitats of Elaeagnus mollis in Shanxi Province was simulated by the maximum entropy model, based on 73 occurrence field records and 35 environmental factors under the current climate condition. Moreover, with the Fifth Assessment Report of Intergovernmental Panel on Climate Change, the dynamics of distribution pattern was analyzed for E. mollis under different climate scenarios. The results showed that the area under the receiver operating characteristic curve (AUC) value was 0.987, indicating that the data fitted the model very well and that the prediction was highly reliable. Results from the Jackknife test showed that the main environmental variables affecting the E. mollis distribution were the precipitation seasonality, the range of annual temperature, annual mean temperature, isothermality, annual precipitation, and pH of topsoil, with the cumulative contribution reaching 94.8%. At present, the potential suitable habitats of E. mollis are mainly located in two regions, the southern of Lyuliang Mountain and Zhongtiao Mountain in Shanxi Province. Under different climate scenarios, the total suitable area of E. mollis would shrink in 2070s. In RCP 2.6 the suitable area would firstly increase and then decrease, while in RCP 4.5 and RCP 8.5 it would response sensitively and first decrease and then increase. Its spatial distribution in two suitable regions would show divergent responses to climate change. The distribution in southern Lyuliang Mountain would fluctuate slightly in latitudinal direction, while that in Zhongtiao Mountain would migrate along elevation.

  14. Statistical surrogate models for prediction of high-consequence climate change.

    Energy Technology Data Exchange (ETDEWEB)

    Constantine, Paul; Field, Richard V., Jr.; Boslough, Mark Bruce Elrick

    2011-09-01

    In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.

  15. Predicting pan-tropical climate change induced forest stock gains and losses-implications for REDD

    International Nuclear Information System (INIS)

    Gumpenberger, Marlies; Vohland, Katrin; Heyder, Ursula; Poulter, Benjamin; Rammig, Anja; Popp, Alexander; Cramer, Wolfgang; Macey, Kirsten

    2010-01-01

    Deforestation is a major threat to tropical forests worldwide, contributing up to one-fifth of global carbon emissions into the atmosphere. Despite protection efforts, deforestation of tropical forests has continued in recent years. Providing incentives to reducing deforestation has been proposed in the United Nations Framework Convention on Climate Change (UNFCCC) Bali negotiations in 2007 to decelerate emissions from deforestation (REDD-reduced emissions from deforestation and forest degradation). A number of methodological issues such as ensuring permanence, establishing reference emissions levels that do not reward business-as-usual and having a measuring, reporting and verification system in place are essential elements in implementing successful REDD schemes. To assess the combined impacts of climate and land-use change on tropical forest carbon stocks in the 21st century, we use a dynamic global vegetation model (LPJ DGVM) driven by five different climate change projections under a given greenhouse gas emission scenario (SRES A2) and two contrasting land-use change scenarios. We find that even under a complete stop of deforestation after the period of the Kyoto Protocol (post-2012) some countries may continue to lose carbon stocks due to climate change. Especially at risk is tropical Latin America, although the presence and magnitude of the risk depends on the climate change scenario. By contrast, strong protection of forests could increase carbon uptake in many tropical countries, due to CO 2 fertilization effects, even under altered climate regimes.

  16. Predicting species-specific responses of fungi to climatic variation using historical records.

    Science.gov (United States)

    Diez, Jeffrey M; James, Timothy Y; McMunn, Marshall; Ibáñez, Inés

    2013-10-01

    Although striking changes have been documented in plant and animal phenology over the past century, less is known about how the fungal kingdom's phenology has been changing. A few recent studies have documented changes in fungal fruiting in Europe in the last few decades, but the geographic and taxonomic extent of these changes, the mechanisms behind these changes, and their relationships to climate are not well understood. Here, we analyzed herbarium data of 274 species of fungi from Michigan to test the hypotheses that fruiting times of fungi depend on annual climate and that responses depend on taxonomic and functional groups. We show that the fungal community overall fruits later in warmer and drier years, which has led to a shift toward later fruiting dates for autumn-fruiting species, consistent with existing evidence. However, we also show that these effects are highly variable among species and are partly explained by basic life-history characteristics. Resulting differences in climate sensitivities are expected to affect community structure as climate changes. This study provides a unique picture of the climate dependence of fungal phenology in North America and an approach for quantifying how individual species and broader fungal communities will respond to ongoing climate change. © 2013 John Wiley & Sons Ltd.

  17. Towards a Seamless Framework for Drought Analysis and Prediction from Seasonal to Climate Change Time Scales (Plinius Medal Lecture)

    Science.gov (United States)

    Sheffield, Justin

    2013-04-01

    Droughts arguably cause the most impacts of all natural hazards in terms of the number of people affected and the long-term economic costs and ecosystem stresses. Recent droughts worldwide have caused humanitarian and economic problems such as food insecurity across the Horn of Africa, agricultural economic losses across the central US and loss of livelihoods in rural western India. The prospect of future increases in drought severity and duration driven by projected changes in precipitation patterns and increasing temperatures is worrisome. Some evidence for climate change impacts on drought is already being seen for some regions, such as the Mediterranean and east Africa. Mitigation of the impacts of drought requires advance warning of developing conditions and enactment of drought plans to reduce vulnerability. A key element of this is a drought early warning system that at its heart is the capability to monitor evolving hydrological conditions and water resources storage, and provide reliable and robust predictions out to several months, as well as the capacity to act on this information. At longer time scales, planning and policy-making need to consider the potential impacts of climate change and its impact on drought risk, and do this within the context of natural climate variability, which is likely to dominate any climate change signal over the next few decades. There are several challenges that need to be met to advance our capability to provide both early warning at seasonal time scales and risk assessment under climate change, regionally and globally. Advancing our understanding of drought predictability and risk requires knowledge of drought at all time scales. This includes understanding of past drought occurrence, from the paleoclimate record to the recent past, and understanding of drought mechanisms, from initiation, through persistence to recovery and translation of this understanding to predictive models. Current approaches to monitoring and

  18. Climate Kids

    Science.gov (United States)

    ... What Is Permafrost? How Do We Predict Future Climate? Green Career: Earth Scientist 10 Things About Ecosystems ... study Earth? What can trees tell us about climate change? Why does NASA care about food? Games ...

  19. Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

    Science.gov (United States)

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

    2017-12-01

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

  20. Future climate change is predicted to shift long-term persistence zones in the cold-temperate kelp Laminaria hyperborea.

    Science.gov (United States)

    Assis, Jorge; Lucas, Ana Vaz; Bárbara, Ignacio; Serrão, Ester Álvares

    2016-02-01

    Global climate change is shifting species distributions worldwide. At rear edges (warmer, low latitude range margins), the consequences of small variations in environmental conditions can be magnified, producing large negative effects on species ranges. A major outcome of shifts in distributions that only recently received attention is the potential to reduce the levels of intra-specific diversity and consequently the global evolutionary and adaptive capacity of species to face novel disturbances. This is particularly important for low dispersal marine species, such as kelps, that generally retain high and unique genetic diversity at rear ranges resulting from long-term persistence, while ranges shifts during climatic glacial/interglacial cycles. Using ecological niche modelling, we (1) infer the major environmental forces shaping the distribution of a cold-temperate kelp, Laminaria hyperborea (Gunnerus) Foslie, and we (2) predict the effect of past climate changes in shaping regions of long-term persistence (i.e., climatic refugia), where this species might hypothetically harbour higher genetic diversity given the absence of bottlenecks and local extinctions over the long term. We further (3) assessed the consequences of future climate for the fate of L. hyperborea using different scenarios of greenhouse gas emissions (RCP 2.6 and RCP 8.5). Results show NW Iberia, SW Ireland and W English Channel, Faroe Islands and S Iceland, as regions where L. hyperborea may have persisted during past climate extremes until present day. All predictions for the future showed expansions to northern territories coupled with the significant loss of suitable habitats at low latitude range margins, where long-term persistence was inferred (e.g., NW Iberia). This pattern was particularly evident in the most agressive scenario of climate change (RCP 8.5), likely driving major biodiversity loss, changes in ecosystem functioning and the impoverishment of the global gene pool of L

  1. Challenges in predicting climate and environmental effects on vector-borne disease episystems in a changing world.

    Science.gov (United States)

    Tabachnick, W J

    2010-03-15

    Vector-borne pathogens cause enormous suffering to humans and animals. Many are expanding their range into new areas. Dengue, West Nile and Chikungunya have recently caused substantial human epidemics. Arthropod-borne animal diseases like Bluetongue, Rift Valley fever and African horse sickness pose substantial threats to livestock economies around the world. Climate change can impact the vector-borne disease epidemiology. Changes in climate will influence arthropod vectors, their life cycles and life histories, resulting in changes in both vector and pathogen distribution and changes in the ability of arthropods to transmit pathogens. Climate can affect the way pathogens interact with both the arthropod vector and the human or animal host. Predicting and mitigating the effects of future changes in the environment like climate change on the complex arthropod-pathogen-host epidemiological cycle requires understanding of a variety of complex mechanisms from the molecular to the population level. Although there has been substantial progress on many fronts the challenges to effectively understand and mitigate the impact of potential changes in the environment on vector-borne pathogens are formidable and at an early stage of development. The challenges will be explored using several arthropod-borne pathogen systems as illustration, and potential avenues to meet the challenges will be presented.

  2. Numerical climate modeling and verification of selected areas for heat waves of Pakistan using ensemble prediction system

    International Nuclear Information System (INIS)

    Amna, S; Samreen, N; Khalid, B; Shamim, A

    2013-01-01

    Depending upon the topography, there is an extreme variation in the temperature of Pakistan. Heat waves are the Weather-related events, having significant impact on the humans, including all socioeconomic activities and health issues as well which changes according to the climatic conditions of the area. The forecasting climate is of prime importance for being aware of future climatic changes, in order to mitigate them. The study used the Ensemble Prediction System (EPS) for the purpose of modeling seasonal weather hind-cast of three selected areas i.e., Islamabad, Jhelum and Muzaffarabad. This research was purposely carried out in order to suggest the most suitable climate model for Pakistan. Real time and simulated data of five General Circulation Models i.e., ECMWF, ERA-40, MPI, Meteo France and UKMO for selected areas was acquired from Pakistan Meteorological Department. Data incorporated constituted the statistical temperature records of 32 years for the months of June, July and August. This study was based on EPS to calculate probabilistic forecasts produced by single ensembles. Verification was done out to assess the quality of the forecast t by using standard probabilistic measures of Brier Score, Brier Skill Score, Cross Validation and Relative Operating Characteristic curve. The results showed ECMWF the most suitable model for Islamabad and Jhelum; and Meteo France for Muzaffarabad. Other models have significant results by omitting particular initial conditions.

  3. Contrasting responses of leaf stomatal characteristics to climate change: a considerable challenge to predict carbon and water cycles.

    Science.gov (United States)

    Yan, Weiming; Zhong, Yangquanwei; Shangguan, Zhouping

    2017-09-01

    Stomata control the cycling of water and carbon between plants and the atmosphere; however, no consistent conclusions have been drawn regarding the response of stomatal frequency to climate change. Here, we conducted a meta-analysis of 1854 globally obtained data series to determine the response of stomatal frequency to climate change, which including four plant life forms (over 900 species), at altitudes ranging from 0 to 4500 m and over a time span of more than one hundred thousand years. Stomatal frequency decreased with increasing CO 2 concentration and increased with elevated temperature and drought stress; it was also dependent on the species and experimental conditions. The response of stomatal frequency to climate change showed a trade-off between stomatal control strategies and environmental factors, such as the CO 2 concentration, temperature, and soil water availability. Moreover, threshold effects of elevated CO 2 and temperature on stomatal frequency were detected, indicating that the response of stomatal density to increasing CO 2 concentration will decrease over the next few years. The results also suggested that the stomatal index may be more reliable than stomatal density for determination of the historic CO 2 concentration. Our findings indicate that the contrasting responses of stomata to climate change bring a considerable challenge in predicting future water and carbon cycles. © 2017 John Wiley & Sons Ltd.

  4. A Technology Development Roadmap for a Near-Term Probe-Class X-ray Astrophysics Mission

    Science.gov (United States)

    Daelemans, Gerard J.; Petre, Robert; Bookbinder, Jay; Ptak, Andrew; Smith, Randall

    2013-01-01

    funded through the NASA Physics of the Cosmos (PCOS) Strategic Astrophysics Technology (SAT) program; some through the end of FY13, others though FY14. These technology needs are those identified as critical for a near-term mission and briefly described in the 2012 NASA X-ray Mission Concepts Study. This Technology Development Roadmap (TDR) provides a more complete description of each, updates the status, and describes the steps to mature them. For each technology, a roadmap is presented for attaining TRL-6 by 2020 at the latest, and 2018 for most. The funding required for each technology to attain TRL-5 and TRL-6 is presented and justified through a description of the steps needing completion. The total funding required for these technologies to reach TRL-6 is relatively modest, and is consistent with the planned PCOS SAT funding over the next several years. The approximate annual cost through 2018 is $8M. The total cost for all technologies to be matured is $62M (including funding already awarded for FY13 and FY14). This can be contrasted to the $180M recommended by NWNH for technology development for IXO, primarily for the maturation of the mirror technology. The technology described in Section 3 of this document is exclusively that needed for a near-term Probe-class mission, to start in 2017, or for a mission that can be recommended by the next Decadal survey committee for an immediate start. It is important to note that there are other critical X-ray instrumentation technologies under development that are less mature than the ones discussed here, but are essential for a major X-ray mission that might start in the late 2020s. These technologies, described briefly in Section 4, are more appropriately funded through the Astronomy and Physics Research and Analysis (APRA) program.

  5. Uncertainty in model predictions of Vibrio vulnificus response to climate variability and change: a Chesapeake Bay case study.

    Directory of Open Access Journals (Sweden)

    Erin A Urquhart

    Full Text Available The effect that climate change and variability will have on waterborne bacteria is a topic of increasing concern for coastal ecosystems, including the Chesapeake Bay. Surface water temperature trends in the Bay indicate a warming pattern of roughly 0.3-0.4°C per decade over the past 30 years. It is unclear what impact future warming will have on pathogens currently found in the Bay, including Vibrio spp. Using historical environmental data, combined with three different statistical models of Vibrio vulnificus probability, we explore the relationship between environmental change and predicted Vibrio vulnificus presence in the upper Chesapeake Bay. We find that the predicted response of V. vulnificus probability to high temperatures in the Bay differs systematically between models of differing structure. As existing publicly available datasets are inadequate to determine which model structure is most appropriate, the impact of climatic change on the probability of V. vulnificus presence in the Chesapeake Bay remains uncertain. This result points to the challenge of characterizing climate sensitivity of ecological systems in which data are sparse and only statistical models of ecological sensitivity exist.

  6. Model and scenario variations in predicted number of generations of Spodoptera litura Fab. on peanut during future climate change scenario.

    Directory of Open Access Journals (Sweden)

    Mathukumalli Srinivasa Rao

    Full Text Available The present study features the estimation of number of generations of tobacco caterpillar, Spodoptera litura. Fab. on peanut crop at six locations in India using MarkSim, which provides General Circulation Model (GCM of future data on daily maximum (T.max, minimum (T.min air temperatures from six models viz., BCCR-BCM2.0, CNRM-CM3, CSIRO-Mk3.5, ECHams5, INCM-CM3.0 and MIROC3.2 along with an ensemble of the six from three emission scenarios (A2, A1B and B1. This data was used to predict the future pest scenarios following the growing degree days approach in four different climate periods viz., Baseline-1975, Near future (NF -2020, Distant future (DF-2050 and Very Distant future (VDF-2080. It is predicted that more generations would occur during the three future climate periods with significant variation among scenarios and models. Among the seven models, 1-2 additional generations were predicted during DF and VDF due to higher future temperatures in CNRM-CM3, ECHams5 & CSIRO-Mk3.5 models. The temperature projections of these models indicated that the generation time would decrease by 18-22% over baseline. Analysis of variance (ANOVA was used to partition the variation in the predicted number of generations and generation time of S. litura on peanut during crop season. Geographical location explained 34% of the total variation in number of generations, followed by time period (26%, model (1.74% and scenario (0.74%. The remaining 14% of the variation was explained by interactions. Increased number of generations and reduction of generation time across the six peanut growing locations of India suggest that the incidence of S. litura may increase due to projected increase in temperatures in future climate change periods.

  7. Combining public participatory surveillance and occupancy modelling to predict the distributional response of Ixodes scapularis to climate change.

    Science.gov (United States)

    Lieske, David J; Lloyd, Vett K

    2018-03-01

    Ixodes scapularis, a known vector of Borrelia burgdorferi sensu stricto (Bbss), is undergoing range expansion in many parts of Canada. The province of New Brunswick, which borders jurisdictions with established populations of I. scapularis, constitutes a range expansion zone for this species. To better understand the current and potential future distribution of this tick under climate change projections, this study applied occupancy modelling to distributional records of adult ticks that successfully overwintered, obtained through passive surveillance. This study indicates that I. scapularis occurs throughout the southern-most portion of the province, in close proximity to coastlines and major waterways. Milder winter conditions, as indicated by the number of degree days model with a predictive accuracy of 0.845 (range: 0.828-0.893). Both RCP 4.5 and RCP 8.5 climate projections predict that a significant proportion of the province (roughly a quarter to a third) will be highly suitable for I. scapularis by the 2080s. Comparison with cases of canine infection show good spatial agreement with baseline model predictions, but the presence of canine Borrelia infections beyond the climate envelope, defined by the highest probabilities of tick occurrence, suggest the presence of Bbss-carrying ticks distributed by long-range dispersal events. This research demonstrates that predictive statistical modelling of multi-year surveillance information is an efficient way to identify areas where I. scapularis is most likely to occur, and can be used to guide subsequent active sampling efforts in order to better understand fine scale species distributional patterns. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

  8. Correlation of spatial climate/weather maps and the advantages of using the Mahalanobis metric in predictions

    Science.gov (United States)

    Stephenson, D. B.

    1997-10-01

    The skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the variance of the correlation distribution can vary from unity up to the number of grid points depending on the choice of weighting metric. The (pseudo-) inverse of the sample covariance matrix acts as a special choice for the metric in that it gives a correlation distribution which has minimal kurtosis and maximum dimension. Minimal kurtosis suggests that the average predictive skill might be improved due to the rarer occurrence of troublesome outlier patterns far from the mean state. Maximum dimension has a disadvantage for analogue prediction schemes in that it gives the minimum number of analogue states. This metric also has an advantage in that it allows one to powerfully test the null hypothesis of multinormality by examining the second and third moments of the correlation coefficient which were introduced by Mardia as invariant measures of multivariate kurtosis and skewness. For these reasons, it is suggested that this metric could be usefully employed in the prediction of weather/climate and in fingerprinting anthropogenic climate change. The ideas are illustrated using the bivariate example of the observed monthly mean sea-level pressures at Darwin and Tahitifrom 1866 1995.

  9. SU-E-J-143: Short- and Near-Term Effects of Proton Therapy On Cerebral White Matter

    Energy Technology Data Exchange (ETDEWEB)

    Uh, J; Merchant, T; Ogg, R; Sabin, N; Hua, C [St. Jude Children' s Research Hospital, Memphis, TN (United States); Indelicato, D [University of Florida Proton Therapy Institute, Jacksonville, FL (United States)

    2014-06-01

    Purpose: To assess early effects of proton therapy on the structural integrity of cerebral white matter in relation to the subsequent near-term development of such effects. Methods: Sixteen children (aged 2–19 years) with craniopharyngioma underwent proton therapy of 54 Cobalt Gray Equivalent (CGE) in a prospective therapeutic trial. Diffusion tensor imaging (DTI) was performed at baseline before proton therapy and every 3 months thereafter. Tract-based spatial statics analysis of DTI data was performed to derive the fractional anisotropy (FA) and radial diffusivity (RD) in 26 volumes of interest (VOIs). The dose distributions were spatially normalized to identify VOIs prone to high doses. The longitudinal percentage changes of the FA and RD in these VOIs at 3 and 12 months from the baseline were calculated, and their relationships were evaluated. Results: The average dose was highest to the cerebral peduncle (CP), corticospinal tract (CST) in the pons, pontine crossing tract (PCT), anterior/posterior limbs of the internal capsule (ALIC/PLIC), and genu of the corpus callosum (GCC). It ranged from 33.3 GCE (GCC) to 49.7 GCE (CP). A mild but statistically significant (P<0.05) decline of FA was observed 3 months after proton therapy in all VOIs except the PLIC and ranged from −1.7% (ALIC) to −2.8% (PCT). A significant increase of RD was found in the CP (3.5%) and ALIC (2.1%). The average longitudinal change from the baseline was reduced at 12 months for most VOIs. However, the standard deviation increased, indicating that the temporal pattern varied individually. The follow-up measurements at 3 and 12 months correlated for the CP, CST, PCT, and GCC (P < 0.04). Conclusion: DTI data suggest early (3 months) effects of proton therapy on microstructures in the white matter. The subsequent follow-up indicated individual variation of the changes, which was partly implied by the early effects.

  10. A melodic contour repeatedly experienced by human near-term fetuses elicits a profound cardiac reaction one month after birth.

    Science.gov (United States)

    Granier-Deferre, Carolyn; Bassereau, Sophie; Ribeiro, Aurélie; Jacquet, Anne-Yvonne; Decasper, Anthony J

    2011-02-23

    Human hearing develops progressively during the last trimester of gestation. Near-term fetuses can discriminate acoustic features, such as frequencies and spectra, and process complex auditory streams. Fetal and neonatal studies show that they can remember frequently recurring sounds. However, existing data can only show retention intervals up to several days after birth. Here we show that auditory memories can last at least six weeks. Experimental fetuses were given precisely controlled exposure to a descending piano melody twice daily during the 35(th), 36(th), and 37(th) weeks of gestation. Six weeks later we assessed the cardiac responses of 25 exposed infants and 25 naive control infants, while in quiet sleep, to the descending melody and to an ascending control piano melody. The melodies had precisely inverse contours, but similar spectra, identical duration, tempo and rhythm, thus, almost identical amplitude envelopes. All infants displayed a significant heart rate change. In exposed infants, the descending melody evoked a cardiac deceleration that was twice larger than the decelerations elicited by the ascending melody and by both melodies in control infants. Thus, 3-weeks of prenatal exposure to a specific melodic contour affects infants 'auditory processing' or perception, i.e., impacts the autonomic nervous system at least six weeks later, when infants are 1-month old. Our results extend the retention interval over which a prenatally acquired memory of a specific sound stream can be observed from 3-4 days to six weeks. The long-term memory for the descending melody is interpreted in terms of enduring neurophysiological tuning and its significance for the developmental psychobiology of attention and perception, including early speech perception, is discussed.

  11. Follow-up into young adulthood after cardiopulmonary resuscitation in term and near-term newborn infants. II. Neuropsychological consequences.

    Science.gov (United States)

    Viggedal, G; Lundälv, E; Carlsson, G; Kjellmer, I

    2002-01-01

    Brain injury after neonatal cardiopulmonary resuscitation in the term baby is often described as an all-or-nothing phenomenon, but little is known about possible late cognitive consequences. The aim of this study was therefore to investigate whether children who needed cardiopulmonary resuscitation because of presumed mild and moderate intra-partum asphyxia with no evidence of neurological impairments at 18 mo of age may display neuropsychological impairments later in life. A long-term follow-up of young adults was carried out. A blinded comprehensive neuropsychological assessment of the main aspects of cognitive functions was made. The subjects who were resuscitated were divided into two groups according to the clinical course: 20 cases with mild asphyxia and 11 cases with moderate asphyxia, all followed prospectively and compared with 18 healthy controls. The 31 subjects were born at term or near-term and selected randomly from 59 infants born in 1969-1978 at Sahlgren's Hospital, Göteborg. All infants with early neurological impairments were excluded. No major differences could be established between the two clinical groups and normal controls in any aspects of cognitive function or intelligence. All the groups performed within the normal range in all tests. A tendency toward minor deficits in verbal ability in the mild group compared to the controls was found. Only one subject had a clear, defined memory deficit. Infants who underwent cardiopulmonary resuscitatation at birth without neurological deficits at 18 mo of age did not show any cognitive deficits or neuropsychological impairments in adulthood even though inferior performance on some verbal subtests was observed compared to the control group.

  12. A melodic contour repeatedly experienced by human near-term fetuses elicits a profound cardiac reaction one month after birth.

    Directory of Open Access Journals (Sweden)

    Carolyn Granier-Deferre

    2011-02-01

    Full Text Available Human hearing develops progressively during the last trimester of gestation. Near-term fetuses can discriminate acoustic features, such as frequencies and spectra, and process complex auditory streams. Fetal and neonatal studies show that they can remember frequently recurring sounds. However, existing data can only show retention intervals up to several days after birth.Here we show that auditory memories can last at least six weeks. Experimental fetuses were given precisely controlled exposure to a descending piano melody twice daily during the 35(th, 36(th, and 37(th weeks of gestation. Six weeks later we assessed the cardiac responses of 25 exposed infants and 25 naive control infants, while in quiet sleep, to the descending melody and to an ascending control piano melody. The melodies had precisely inverse contours, but similar spectra, identical duration, tempo and rhythm, thus, almost identical amplitude envelopes. All infants displayed a significant heart rate change. In exposed infants, the descending melody evoked a cardiac deceleration that was twice larger than the decelerations elicited by the ascending melody and by both melodies in control infants.Thus, 3-weeks of prenatal exposure to a specific melodic contour affects infants 'auditory processing' or perception, i.e., impacts the autonomic nervous system at least six weeks later, when infants are 1-month old. Our results extend the retention interval over which a prenatally acquired memory of a specific sound stream can be observed from 3-4 days to six weeks. The long-term memory for the descending melody is interpreted in terms of enduring neurophysiological tuning and its significance for the developmental psychobiology of attention and perception, including early speech perception, is discussed.

  13. The effect of oxygen content during an initial sustained inflation on heart rate in asphyxiated near-term lambs.

    Science.gov (United States)

    Sobotka, K S; Ong, T; Polglase, G R; Crossley, K J; Moss, T J M; Hooper, S B

    2015-07-01

    At birth, an initial sustained inflation (SI) uniformly aerates the lungs, increases arterial oxygenation and rapidly improves circulatory recovery in asphyxiated newborns. We hypothesised that lung aeration, in the absence of an increase in arterial oxygenation, can increase heart rate (HR) in asphyxiated near-term lambs. Lambs were delivered and instrumented at 139±2 days of gestation. Asphyxia was induced by umbilical cord clamping and then delaying the onset of ventilation until mean carotid arterial pressures (CAPs) had decreased <20 mm Hg. Lambs then received a single 30-s SI using nitrogen (N2; n=6), 5% oxygen (O2; n=6), 21% O2 (n=6) or 100% O2 (n=6) followed by ventilation in air for 30 min. HR, CAP and pulmonary blood flow (PBF) were continuously recorded. HR and PBF increased more quickly in lambs resuscitated with 100% and 21% O2 than with 5% O2 or N2. HR and PBF recovery in the 5% O2 group was delayed relative to all other oxygen SI groups. HR in 5%, 21% and 100% O2 groups reached 100 bpm before the SI was complete. HR and PBF in the N2 group did not increase until 10 s after the SI was completed and ventilation was initiated with air. CAP tended to increase quicker in all O2 groups than in N2 group. Oxygen content during an SI is important for circulatory recovery in asphyxiated lambs. This increase in HR is likely driven by the increase in PBF and venous return to the heart. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.