Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Tamil Nadu

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Tamil Nadu is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Rajasthan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Andhra Pradesh

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Karnataka

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Maharashtra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Modelling memory colour region for preference colour reproduction

NASA Astrophysics Data System (ADS)

Zeng, Huanzhao; Luo, Ronnier

2010-01-01

Colour preference adjustment is an essential step for colour image enhancement and perceptual gamut mapping. In colour reproduction for pictorial images, properly shifting colours away from their colorimetric originals may produce more preferred colour reproduction result. Memory colours, as a portion of the colour regions for colour preference adjustment, are especially important for preference colour reproduction. Identifying memory colours or modelling the memory colour region is a basic step to study preferred memory colour enhancement. In this study, we first created gamut for each memory colour region represented as a convex hull, and then used the convex hull to guide mathematical modelling to formulate the colour region for colour enhancement.

Hydrogeologic Settings and Ground-Water Flow Simulations for Regional Studies of the Transport of Anthropogenic and Natural Contaminants to Public-Supply Wells - Studies Begun in 2001

USGS Publications Warehouse

Paschke, Suzanne S.

2007-01-01

This study of the Transport of Anthropogenic and Natural Contaminants to public-supply wells (TANC study) is being conducted as part of the U.S. Geological Survey National Water Quality Assessment (NAWQA) Program and was designed to increase understanding of the most important factors to consider in ground-water vulnerability assessments. The seven TANC studies that began in 2001 used retrospective data and ground-water flow models to evaluate hydrogeologic variables that affect aquifer susceptibility and vulnerability at a regional scale. Ground-water flow characteristics, regional water budgets, pumping-well information, and water-quality data were compiled from existing data and used to develop conceptual models of ground-water conditions for each study area. Steady-state regional ground-water flow models were used to represent the conceptual models, and advective particle-tracking simulations were used to compute areas contributing recharge and traveltimes from recharge to selected public-supply wells. Retrospective data and modeling results were tabulated into a relational database for future analysis. Seven study areas were selected to evaluate a range of hydrogeologic settings and management practices across the Nation: the Salt Lake Valley, Utah; the Eagle Valley and Spanish Springs Valley, Nevada; the San Joaquin Valley, California; the Northern Tampa Bay region, Florida; the Pomperaug River Basin, Connecticut; the Great Miami River Basin, Ohio; and the Eastern High Plains, Nebraska. This Professional Paper Chapter presents the hydrogeologic settings and documents the ground-water flow models for each of the NAWQA TANC regional study areas that began work in 2001. Methods used to compile retrospective data, determine contributing areas of public-supply wells, and characterize oxidation-reduction (redox) conditions also are presented. This Professional Paper Chapter provides the foundation for future susceptibility and vulnerability analyses in the TANC study areas and comparisons among regional aquifer systems. The report is organized in sections. In addition to the introductory section (Section 1) are seven sections that present the hydrogeologic characterization and ground-water flow model documentation for each TANC regional study area (Sections 2 through 8). Abstracts in Sections 2 through 8 provide summaries and major findings for each regional study area.

Effect of Mesoscale and Multiscale Modeling on the Performance of Kevlar Woven Fabric Subjected to Ballistic Impact: A Numerical Study

NASA Astrophysics Data System (ADS)

Jia, Xin; Huang, Zhengxiang; Zu, Xudong; Gu, Xiaohui; Xiao, Qiangqiang

2013-12-01

In this study, an optimal finite element model of Kevlar woven fabric that is more computational efficient compared with existing models was developed to simulate ballistic impact onto fabric. Kevlar woven fabric was modeled to yarn level architecture by using the hybrid elements analysis (HEA), which uses solid elements in modeling the yarns at the impact region and uses shell elements in modeling the yarns away from the impact region. Three HEA configurations were constructed, in which the solid element region was set as about one, two, and three times that of the projectile's diameter with impact velocities of 30 m/s (non-perforation case) and 200 m/s (perforation case) to determine the optimal ratio between the solid element region and the shell element region. To further reduce computational time and to maintain the necessary accuracy, three multiscale models were presented also. These multiscale models combine the local region with the yarn level architecture by using the HEA approach and the global region with homogenous level architecture. The effect of the varying ratios of the local and global area on the ballistic performance of fabric was discussed. The deformation and damage mechanisms of fabric were analyzed and compared among numerical models. Simulation results indicate that the multiscale model based on HEA accurately reproduces the baseline results and obviously decreases computational time.

Assessing the Impact of Climatic Variability and Change on Maize Production in the Midwestern USA

NASA Astrophysics Data System (ADS)

Andresen, J.; Jain, A. K.; Niyogi, D. S.; Alagarswamy, G.; Biehl, L.; Delamater, P.; Doering, O.; Elias, A.; Elmore, R.; Gramig, B.; Hart, C.; Kellner, O.; Liu, X.; Mohankumar, E.; Prokopy, L. S.; Song, C.; Todey, D.; Widhalm, M.

2013-12-01

Weather and climate remain among the most important uncontrollable factors in agricultural production systems. In this study, three process-based crop simulation models were used to identify the impacts of climate on the production of maize in the Midwestern U.S.A. during the past century. The 12-state region is a key global production area, responsible for more than 80% of U.S. domestic and 25% of total global production. The study is a part of the Useful to Useable (U2U) Project, a USDA NIFA-sponsored project seeking to improve the resilience and profitability of farming operations in the region amid climate variability and change. Three process-based crop simulation models were used in the study: CERES-Maize (DSSAT, Hoogenboom et al., 2012), the Hybrid-Maize model (Yang et al., 2004), and the Integrated Science Assessment Model (ISAM, Song et al., 2013). Model validation was carried out with individual plot and county observations. The models were run with 4 to 50 km spatial resolution gridded weather data for representative soils and cultivars, 1981-2012, to examine spatial and temporal yield variability within the region. We also examined the influence of different crop models and spatial scales on regional scale yield estimation, as well as a yield gap analysis between observed and attainable yields. An additional study was carried out with the CERES-Maize model at 18 individual site locations 1901-2012 to examine longer term historical trends. For all simulations, all input variables were held constant in order to isolate the impacts of climate. In general, the model estimates were in good agreement with observed yields, especially in central sections of the region. Regionally, low precipitation and soil moisture stress were chief limitations to simulated crop yields. The study suggests that at least part of the observed yield increases in the region during recent decades have occurred as the result of wetter, less stressful growing season weather conditions.

The gravity model of labor migration behavior

NASA Astrophysics Data System (ADS)

Alexandr, Tarasyev; Alexandr, Tarasyev

2017-07-01

In this article, we present a dynamic inter-regional model, that is based on the gravity approach to migration and describes in continuous time the labor force dynamics between a number of conjugate regions. Our modification of the gravity migration model allows to explain the migration processes and to display the impact of migration on the regional economic development both for regions of origin and attraction. The application of our model allows to trace the dependency between salaries levels, total workforce, the number of vacancies and the number unemployed people in simulated regions. Due to the gravity component in our model the accuracy of prediction for migration flows is limited by the distance range between analyzed regions, so this model is tested on a number of conjugate neighbor regions. Future studies will be aimed at development of a multi-level dynamic model, which allows to construct a forecast for unemployment and vacancies trends on the first modeling level and to use these identified parameters on the second level for describing dynamic trajectories of migration flows.

A generalized estimating equations approach for resting-state functional MRI group analysis.

PubMed

D'Angelo, Gina M; Lazar, Nicole A; Eddy, William F; Morris, John C; Sheline, Yvette I

2011-01-01

An Alzheimer's fMRI study has motivated us to evaluate inter-regional correlations between groups. The overall objective is to assess inter-regional correlations at a resting-state with no stimulus or task. We propose using a generalized estimating equation (GEE) transition model and a GEE marginal model to model the within-subject correlation for each region. Residuals calculated from the GEE models are used to correlate brain regions and assess between group differences. The standard pooling approach of group averages of the Fisher-z transformation assuming temporal independence is a typical approach used to compare group correlations. The GEE approaches and standard Fisher-z pooling approach are demonstrated with an Alzheimer's disease (AD) connectivity study in a population of AD subjects and healthy control subjects. We also compare these methods using simulation studies and show that the transition model may have better statistical properties.

Analysis of the Effect of Interior Nudging on Temperature and Precipitation Distributions of Multi-year Regional Climate Simulations

NASA Astrophysics Data System (ADS)

Nolte, C. G.; Otte, T. L.; Bowden, J. H.; Otte, M. J.

2010-12-01

There is disagreement in the regional climate modeling community as to the appropriateness of the use of internal nudging. Some investigators argue that the regional model should be minimally constrained and allowed to respond to regional-scale forcing, while others have noted that in the absence of interior nudging, significant large-scale discrepancies develop between the regional model solution and the driving coarse-scale fields. These discrepancies lead to reduced confidence in the ability of regional climate models to dynamically downscale global climate model simulations under climate change scenarios, and detract from the usability of the regional simulations for impact assessments. The advantages and limitations of interior nudging schemes for regional climate modeling are investigated in this study. Multi-year simulations using the WRF model driven by reanalysis data over the continental United States at 36km resolution are conducted using spectral nudging, grid point nudging, and for a base case without interior nudging. The means, distributions, and inter-annual variability of temperature and precipitation will be evaluated in comparison to regional analyses.

High-resolution regional climate model evaluation using variable-resolution CESM over California

NASA Astrophysics Data System (ADS)

Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

2015-12-01

Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine-scale processes. This assessment is also relevant for addressing the scale limitation of current RCMs or VRGCMs when next-generation model resolution increases to ~10km and beyond.

Evaluation of GCMs in the context of regional predictive climate impact studies.

NASA Astrophysics Data System (ADS)

Kokorev, Vasily; Anisimov, Oleg

2016-04-01

Significant improvements in the structure, complexity, and general performance of earth system models (ESMs) have been made in the recent decade. Despite these efforts, the range of uncertainty in predicting regional climate impacts remains large. The problem is two-fold. Firstly, there is an intrinsic conflict between the local and regional scales of climate impacts and adaptation strategies, on one hand, and larger scales, at which ESMs demonstrate better performance, on the other. Secondly, there is a growing understanding that majority of the impacts involve thresholds, and are thus driven by extreme climate events, whereas accent in climate projections is conventionally made on gradual changes in means. In this study we assess the uncertainty in projecting extreme climatic events within a region-specific and process-oriented context by examining the skills and ranking of ESMs. We developed a synthetic regionalization of Northern Eurasia that accounts for the spatial features of modern climatic changes and major environmental and socio-economical impacts. Elements of such fragmentation could be considered as natural focus regions that bridge the gap between the spatial scales adopted in climate-impacts studies and patterns of climate change simulated by ESMs. In each focus region we selected several target meteorological variables that govern the key regional impacts, and examined the ability of the models to replicate their seasonal and annual means and trends by testing them against observations. We performed a similar evaluation with regard to extremes and statistics of the target variables. And lastly, we used the results of these analyses to select sets of models that demonstrate the best performance at selected focus regions with regard to selected sets of target meteorological parameters. Ultimately, we ranked the models according to their skills, identified top-end models that "better than average" reproduce the behavior of climatic parameters, and eliminated the outliers. Since the criteria of selecting the "best" models are somewhat loose, we constructed several regional ensembles consisting of different number of high-ranked models and compared results from these optimized ensembles with observations and with the ensemble of all models. We tested our approach in specific regional application of the terrestrial Russian Arctic, considering permafrost and Artic biomes as key regional climate-dependent systems, and temperature and precipitation characteristics governing their state as target meteorological parameters. Results of this case study are deposited on the web portal www.permafrost.su/gcms

The contribution of CEOP data to the understanding and modeling of monsoon systems

NASA Technical Reports Server (NTRS)

Lau, William K. M.

2005-01-01

CEOP has contributed and will continue to provide integrated data sets from diverse platforms for better understanding of the water and energy cycles, and for validating models. In this talk, I will show examples of how CEOP has contributed to the formulation of a strategy for the study of the monsoon as a system. The CEOP data concept has led to the development of the CEOP Inter-Monsoon Studies (CIMS), which focuses on the identification of model bias, and improvement of model physics such as the diurnal and annual cycles. A multi-model validation project focusing on diurnal variability of the East Asian monsoon, and using CEOP reference site data, as well as CEOP integrated satellite data is now ongoing. Similar validation projects in other monsoon regions are being started. Preliminary studies show that climate models have difficulties in simulating the diurnal signals of total rainfall, rainfall intensity and frequency of occurrence, which have different peak hours, depending on locations. Further more model diurnal cycle of rainfall in monsoon regions tend to lead the observed by about 2-3 hours. These model bias offer insight into lack of, or poor representation of key components of the convective,and stratiform rainfall. The CEOP data also stimulated studies to compare and contrasts monsoon variability in different parts of the world. It was found that seasonal wind reversal, orographic effects, monsoon depressions, meso-scale convective complexes, SST and land surface land influences are common features in all monsoon regions. Strong intraseasonal variability is present in all monsoon regions. While there is a clear demarcation of onset, breaks and withdrawal in the Asian and Australian monsoon region associated with climatological intraseasonal variability, it is less clear in the American and Africa monsoon regions. The examination of satellite and reference site data in monsoon has led to preliminary model experiments to study the impact of aerosol on monsoon variability. I will show examples of how the study of the dynamics of aerosol-water cycle interactions in the monsoon region, can be best achieved using the CEOP data and modeling strategy.

A framework for process-based assessment of regional climate model experiments: applied to projections of southern African precipitation

NASA Astrophysics Data System (ADS)

James, Rachel; Washington, Richard; Jones, Richard

2015-04-01

There is a demand from adaptation planners for regional climate change projections, particularly the finer resolution data delivered by regional models. However, climate models are subject to important uncertainties, and their projections diverge substantially, particularly for precipitation. So how should decision makers know which futures to consider and which to disregard? Model evaluation is clearly a priority. The majority of studies seeking to assess the validity of projections are based on comparison of the models' twentieth century climatologies with observations or reanalysis. Whilst this work is very important, examination of the modelled mean state it is not sufficient to assess the credibility of modelled changes. Direct investigation of the mechanisms for change is also vital. In this study, a framework for process-based analysis of projections is presented, whereby circulation changes accompanying future responses are examined, and then compared to atmospheric dynamics during historical years in models and reanalyses. This framework has previously been applied to investigate a drying signal in West Africa, and will here be used to examine projected precipitation change in southern Africa. An ensemble of five global and regional model experiments will be employed, consisting of five perturbed versions of HadCM3 and five corresponding runs of HadRM3P (PRECIS), run over the CORDEX Africa domain. The global and regional model runs show contrasting future responses: there is a strong drying in the global models over southern Africa during the rainy season, but the regional models show drying over Madagascar and the south west Indian Ocean. Circulation changes associated with these projections will be presented as a first step towards understanding the mechanisms for change and the reasons for difference between the global and regional models. The interannual variability will also be examined and compared to reanalysis to explore how well the models represent the dipole between southern Africa and Madagascar in the twentieth century simulations. This analysis could shed light on the credibility of the projected changes, and the relative trustworthiness of the global and regional models. This research makes a valuable contribution to the understanding of mechanisms for change in southern Africa. It also has wider relevance for regional climate model studies, in highlighting the need to evaluate models on a case by case basis, and providing a framework for assessment which could be applied to other models and other regions.

The Target Model of Strategic Interaction of Kazan Federal University and the Region in the Field of Education

ERIC Educational Resources Information Center

Gabdulchakov, Valerian F.

2016-01-01

The subject of the study in the article is conceptual basis of construction of the target model of interaction between University and region. Hence the topic of the article "the Target model of strategic interaction between the University and the region in the field of education." The objective was to design a target model of this…

Multi-ensemble regional simulation of Indian monsoon during contrasting rainfall years: role of convective schemes and nested domain

NASA Astrophysics Data System (ADS)

Devanand, Anjana; Ghosh, Subimal; Paul, Supantha; Karmakar, Subhankar; Niyogi, Dev

2018-06-01

Regional simulations of the seasonal Indian summer monsoon rainfall (ISMR) require an understanding of the model sensitivities to physics and resolution, and its effect on the model uncertainties. It is also important to quantify the added value in the simulated sub-regional precipitation characteristics by a regional climate model (RCM), when compared to coarse resolution rainfall products. This study presents regional model simulations of ISMR at seasonal scale using the Weather Research and Forecasting (WRF) model with the synoptic scale forcing from ERA-interim reanalysis, for three contrasting monsoon seasons, 1994 (excess), 2002 (deficit) and 2010 (normal). Impact of four cumulus schemes, viz., Kain-Fritsch (KF), Betts-Janjić-Miller, Grell 3D and modified Kain-Fritsch (KFm), and two micro physical parameterization schemes, viz., WRF Single Moment Class 5 scheme and Lin et al. scheme (LIN), with eight different possible combinations are analyzed. The impact of spectral nudging on model sensitivity is also studied. In WRF simulations using spectral nudging, improvement in model rainfall appears to be consistent in regions with topographic variability such as Central Northeast and Konkan Western Ghat sub-regions. However the results are also dependent on choice of cumulus scheme used, with KF and KFm providing relatively good performance and the eight member ensemble mean showing better results for these sub-regions. There is no consistent improvement noted in Northeast and Peninsular Indian monsoon regions. Results indicate that the regional simulations using nested domains can provide some improvements on ISMR simulations. Spectral nudging is found to improve upon the model simulations in terms of reducing the intra ensemble spread and hence the uncertainty in the model simulated precipitation. The results provide important insights regarding the need for further improvements in the regional climate simulations of ISMR for various sub-regions and contribute to the understanding of the added value in seasonal simulations by RCMs.

Multi-ensemble regional simulation of Indian monsoon during contrasting rainfall years: role of convective schemes and nested domain

NASA Astrophysics Data System (ADS)

Devanand, Anjana; Ghosh, Subimal; Paul, Supantha; Karmakar, Subhankar; Niyogi, Dev

2017-08-01

Regional simulations of the seasonal Indian summer monsoon rainfall (ISMR) require an understanding of the model sensitivities to physics and resolution, and its effect on the model uncertainties. It is also important to quantify the added value in the simulated sub-regional precipitation characteristics by a regional climate model (RCM), when compared to coarse resolution rainfall products. This study presents regional model simulations of ISMR at seasonal scale using the Weather Research and Forecasting (WRF) model with the synoptic scale forcing from ERA-interim reanalysis, for three contrasting monsoon seasons, 1994 (excess), 2002 (deficit) and 2010 (normal). Impact of four cumulus schemes, viz., Kain-Fritsch (KF), Betts-Janjić-Miller, Grell 3D and modified Kain-Fritsch (KFm), and two micro physical parameterization schemes, viz., WRF Single Moment Class 5 scheme and Lin et al. scheme (LIN), with eight different possible combinations are analyzed. The impact of spectral nudging on model sensitivity is also studied. In WRF simulations using spectral nudging, improvement in model rainfall appears to be consistent in regions with topographic variability such as Central Northeast and Konkan Western Ghat sub-regions. However the results are also dependent on choice of cumulus scheme used, with KF and KFm providing relatively good performance and the eight member ensemble mean showing better results for these sub-regions. There is no consistent improvement noted in Northeast and Peninsular Indian monsoon regions. Results indicate that the regional simulations using nested domains can provide some improvements on ISMR simulations. Spectral nudging is found to improve upon the model simulations in terms of reducing the intra ensemble spread and hence the uncertainty in the model simulated precipitation. The results provide important insights regarding the need for further improvements in the regional climate simulations of ISMR for various sub-regions and contribute to the understanding of the added value in seasonal simulations by RCMs.

Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses.

PubMed

Chadsuthi, Sudarat; Modchang, Charin; Lenbury, Yongwimon; Iamsirithaworn, Sopon; Triampo, Wannapong

2012-07-01

To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors. Time series analysis was used to study the time variations in the number of leptospirosis cases. The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region of Thailand, while the temperature played a role in the northeastern region only. The use of multivariate ARIMA (ARIMAX) model showed that factoring in rainfall (with an 8 months lag) yields the best model for the northern region while the model, which factors in rainfall (with a 10 months lag) and temperature (with an 8 months lag) was the best for the northeastern region. The models are able to show the trend in leptospirosis cases and closely fit the recorded data in both regions. The models can also be used to predict the next seasonal peak quite accurately. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

Bifurcations in a discrete time model composed of Beverton-Holt function and Ricker function.

PubMed

Shang, Jin; Li, Bingtuan; Barnard, Michael R

2015-05-01

We provide rigorous analysis for a discrete-time model composed of the Ricker function and Beverton-Holt function. This model was proposed by Lewis and Li [Bull. Math. Biol. 74 (2012) 2383-2402] in the study of a population in which reproduction occurs at a discrete instant of time whereas death and competition take place continuously during the season. We show analytically that there exists a period-doubling bifurcation curve in the model. The bifurcation curve divides the parameter space into the region of stability and the region of instability. We demonstrate through numerical bifurcation diagrams that the regions of periodic cycles are intermixed with the regions of chaos. We also study the global stability of the model. Copyright © 2015 Elsevier Inc. All rights reserved.

Examining Interior Grid Nudging Techniques Using Two-Way Nesting in the WRF Model for Regional Climate Modeling

EPA Science Inventory

This study evaluates interior nudging techniques using the Weather Research and Forecasting (WRF) model for regional climate modeling over the conterminous United States (CONUS) using a two-way nested configuration. NCEP–Department of Energy Atmospheric Model Intercomparison Pro...

Clouds at Barbados are representative of clouds across the trade wind regions in observations and climate models.

PubMed

Medeiros, Brian; Nuijens, Louise

2016-05-31

Trade wind regions cover most of the tropical oceans, and the prevailing cloud type is shallow cumulus. These small clouds are parameterized by climate models, and changes in their radiative effects strongly and directly contribute to the spread in estimates of climate sensitivity. This study investigates the structure and variability of these clouds in observations and climate models. The study builds upon recent detailed model evaluations using observations from the island of Barbados. Using a dynamical regimes framework, satellite and reanalysis products are used to compare the Barbados region and the broader tropics. It is shown that clouds in the Barbados region are similar to those across the trade wind regions, implying that observational findings from the Barbados Cloud Observatory are relevant to clouds across the tropics. The same methods are applied to climate models to evaluate the simulated clouds. The models generally capture the cloud radiative effect, but underestimate cloud cover and show an array of cloud vertical structures. Some models show strong biases in the environment of the Barbados region in summer, weakening the connection between the regional biases and those across the tropics. Even bearing that limitation in mind, it is shown that covariations of cloud and environmental properties in the models are inconsistent with observations. The models tend to misrepresent sensitivity to moisture variations and inversion characteristics. These model errors are likely connected to cloud feedback in climate projections, and highlight the importance of the representation of shallow cumulus convection.

Clouds at Barbados are representative of clouds across the trade wind regions in observations and climate models

PubMed Central

Nuijens, Louise

2016-01-01

Trade wind regions cover most of the tropical oceans, and the prevailing cloud type is shallow cumulus. These small clouds are parameterized by climate models, and changes in their radiative effects strongly and directly contribute to the spread in estimates of climate sensitivity. This study investigates the structure and variability of these clouds in observations and climate models. The study builds upon recent detailed model evaluations using observations from the island of Barbados. Using a dynamical regimes framework, satellite and reanalysis products are used to compare the Barbados region and the broader tropics. It is shown that clouds in the Barbados region are similar to those across the trade wind regions, implying that observational findings from the Barbados Cloud Observatory are relevant to clouds across the tropics. The same methods are applied to climate models to evaluate the simulated clouds. The models generally capture the cloud radiative effect, but underestimate cloud cover and show an array of cloud vertical structures. Some models show strong biases in the environment of the Barbados region in summer, weakening the connection between the regional biases and those across the tropics. Even bearing that limitation in mind, it is shown that covariations of cloud and environmental properties in the models are inconsistent with observations. The models tend to misrepresent sensitivity to moisture variations and inversion characteristics. These model errors are likely connected to cloud feedback in climate projections, and highlight the importance of the representation of shallow cumulus convection. PMID:27185925

EVALUATION OF THE REAL-TIME AIR-QUALITY MODEL USING THE RAPS (REGIONAL AIR POLLUTION STUDY) DATA BASE. VOLUME 1. OVERVIEW

EPA Science Inventory

The theory and programming of statistical tests for evaluating the Real-Time Air-Quality Model (RAM) using the Regional Air Pollution Study (RAPS) data base are fully documented in four report volumes. Moreover, the tests are generally applicable to other model evaluation problem...

Hawaii Regional Sediment Management: Regional Sediment Budget for the Kekaha Region of Kauai, HI

DTIC Science & Technology

2013-06-01

Waimea River . Some sediment passes from the Waimea cell to the west and is deposited in the Kikiaola Harbor entrance channel and basin . Upland... study regions, have been developed by the University of Hawaii Coastal Geology Group (UH CGG) (Fletcher et al. 2012) for the US Geological Survey... Study (WIS) (Hubertz 1992) hindcast dataset were used as input to the model STeady WAVE (STWAVE) (Smith et al. 2001). The model output provides

Field Investigation and Modeling Development for Hydrological and Carbon Cycles in Southwest Karst Region of China

NASA Astrophysics Data System (ADS)

Hu, X. B.

2017-12-01

It is required to understanding water cycle and carbon cycle processes for water resource management and pollution prevention and global warming influence in southwest karst region of China. Lijiang river basin is selected as our study region. Interdisciplinary field and laboratory experiments with various technologies are conducted to characterize the karst aquifers in detail. Key processes in the karst water cycle and carbon cycle are determined. Based on the MODFLOW-CFP model, new watershed flow and carbon cycle models are developed coupled subsurface and surface water flow models. Our study focus on the karst springshed in Mao village, the mechanisms coupling carbon cycle and water cycle are explored. This study provides basic theory and simulation method for water resource management and groundwater pollution prevention in China karst region.

Modeling the Impacts of Global Climate and Regional Land Use Change on Regional Climate, Air Quality and Public Health in the New York Metropolitan Region

NASA Astrophysics Data System (ADS)

Rosenthal, J. E.; Knowlton, K. M.; Kinney, P. L.

2002-12-01

There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human exposures and responses to heat stress and air quality differ as a function of socio-economic status and race/ethnicity across the region? The model systems used for this study are the Goddard Institute for Space Studies (GISS) Global Atmosphere-Ocean Model; the Regional Atmospheric Modeling System (RAMS) and PennState/NCAR MM5 mesoscale meteorological models; the SLEUTH land use model; the Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE); the Community Multiscale Air Quality (CMAQ) and Comprehensive Air Quality Model with Extensions (CAMx) models for simulating regional air quality; and exposure-risk coefficients for assessing population health impacts based on exposure to extreme heat, fine particulates (PM2.5) and ozone. Two different IPCC global emission scenarios and two different regional land use growth scenarios are considered in the simulations, spanning a range of possible futures. In addition to base simulations for selected time periods in the decade 1990 - 2000, the integrated model is used to simulate future scenarios in the 2020s, 2050s, and 2080s. Predictions from both the meteorological models and the air quality models are compared against available observations for the simulations in the 1990s to establish baseline model performance. A series of sensitivity tests will address whether changes in meteorology due to global climate change, changes in regional land use, or changes in emissions have the largest impact on predicted ozone and particulate matter concentrations.

Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event.

PubMed

Knebl, M R; Yang, Z-L; Hutchison, K; Maidment, D R

2005-06-01

This paper develops a framework for regional scale flood modeling that integrates NEXRAD Level III rainfall, GIS, and a hydrological model (HEC-HMS/RAS). The San Antonio River Basin (about 4000 square miles, 10,000 km2) in Central Texas, USA, is the domain of the study because it is a region subject to frequent occurrences of severe flash flooding. A major flood in the summer of 2002 is chosen as a case to examine the modeling framework. The model consists of a rainfall-runoff model (HEC-HMS) that converts precipitation excess to overland flow and channel runoff, as well as a hydraulic model (HEC-RAS) that models unsteady state flow through the river channel network based on the HEC-HMS-derived hydrographs. HEC-HMS is run on a 4 x 4 km grid in the domain, a resolution consistent with the resolution of NEXRAD rainfall taken from the local river authority. Watershed parameters are calibrated manually to produce a good simulation of discharge at 12 subbasins. With the calibrated discharge, HEC-RAS is capable of producing floodplain polygons that are comparable to the satellite imagery. The modeling framework presented in this study incorporates a portion of the recently developed GIS tool named Map to Map that has been created on a local scale and extends it to a regional scale. The results of this research will benefit future modeling efforts by providing a tool for hydrological forecasts of flooding on a regional scale. While designed for the San Antonio River Basin, this regional scale model may be used as a prototype for model applications in other areas of the country.

Studying the Representation Accuracy of the Earth's Gravity Field in the Polar Regions Based on the Global Geopotential Models

NASA Astrophysics Data System (ADS)

Koneshov, V. N.; Nepoklonov, V. B.

2018-05-01

The development of studies on estimating the accuracy of the Earth's modern global gravity models in terms of the spherical harmonics of the geopotential in the problematic regions of the world is discussed. The comparative analysis of the results of reconstructing quasi-geoid heights and gravity anomalies from the different models is carried out for two polar regions selected within a radius of 1000 km from the North and South poles. The analysis covers nine recently developed models, including six high-resolution models and three lower order models, including the Russian GAOP2012 model. It is shown that the modern models determine the quasi-geoid heights and gravity anomalies in the polar regions with errors of 5 to 10 to a few dozen cm and from 3 to 5 to a few dozen mGal, respectively, depending on the resolution. The accuracy of the models in the Arctic is several times higher than in the Antarctic. This is associated with the peculiarities of gravity anomalies in every particular region and with the fact that the polar part of the Antarctic has been comparatively less explored by the gravity methods than the polar Arctic.

Application of ARC/INFO to regional scale hydrogeologic modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wurstner, S.K.; McWethy, G.; Devary, J.L.

1993-05-01

Geographic Information Systems (GIS) can be a useful tool in data preparation for groundwater flow modeling, especially when studying large regional systems. ARC/INFO is being used in conjunction with GRASS to support data preparation for input to the CFEST (Coupled Fluid, Energy, and Solute Transport) groundwater modeling code. Simulations will be performed with CFEST to model three-dimensional, regional, groundwater flow in the West Siberian Basin.

Using spatio-temporal modeling to predict long-term exposure to black smoke at fine spatial and temporal scale

NASA Astrophysics Data System (ADS)

Dadvand, Payam; Rushton, Stephen; Diggle, Peter J.; Goffe, Louis; Rankin, Judith; Pless-Mulloli, Tanja

2011-01-01

Whilst exposure to air pollution is linked to a wide range of adverse health outcomes, assessing levels of this exposure has remained a challenge. This study reports a modeling approach for the estimation of weekly levels of ambient black smoke (BS) at residential postcodes across Northeast England (2055 km 2) over a 12 year period (1985-1996). A two-stage modeling strategy was developed using monitoring data on BS together with a range of covariates including data on traffic, population density, industrial activity, land cover (remote sensing), and meteorology. The first stage separates the temporal trend in BS for the region as a whole from within-region spatial variation and the second stage is a linear model which predicts BS levels at all locations in the region using spatially referenced covariate data as predictors and the regional predicted temporal trend as an offset. Traffic and land cover predictors were included in the final model, which predicted 70% of the spatio-temporal variation in BS across the study region over the study period. This modeling approach appears to provide a robust way of estimating exposure to BS at an inter-urban scale.

A three-dimensional numerical model of predevelopment conditions in the Death Valley regional ground-water flow system, Nevada and California

USGS Publications Warehouse

D'Agnese, Frank A.; O'Brien, G. M.; Faunt, C.C.; Belcher, W.R.; San Juan, C.

2002-01-01

In the early 1990's, two numerical models of the Death Valley regional ground-water flow system were developed by the U.S. Department of Energy. In general, the two models were based on the same basic hydrogeologic data set. In 1998, the U.S. Department of Energy requested that the U.S. Geological Survey develop and maintain a ground-water flow model of the Death Valley region in support of U.S. Department of Energy programs at the Nevada Test Site. The purpose of developing this 'second-generation' regional model was to enhance the knowledge an understanding of the ground-water flow system as new information and tools are developed. The U.S. Geological Survey also was encouraged by the U.S. Department of Energy to cooperate to the fullest extent with other Federal, State, and local entities in the region to take advantage of the benefits of their knowledge and expertise. The short-term objective of the Death Valley regional ground-water flow system project was to develop a steady-state representation of the predevelopment conditions of the ground-water flow system utilizing the two geologic interpretations used to develop the previous numerical models. The long-term objective of this project was to construct and calibrate a transient model that simulates the ground-water conditions of the study area over the historical record that utilizes a newly interpreted hydrogeologic conceptual model. This report describes the result of the predevelopment steady-state model construction and calibration. The Death Valley regional ground-water flow system is situated within the southern Great Basin, a subprovince of the Basin and Range physiographic province, bounded by latitudes 35 degrees north and 38 degrees 15 minutes north and by longitudes 115 and 118 degrees west. Hydrology in the region is a result of both the arid climatic conditions and the complex geology. Ground-water flow generally can be described as dominated by interbasinal flow and may be conceptualized as having two main components: a series of relatively shallow and localized flow paths that are superimposed on deeper regional flow paths. A significant component of the regional ground-water flow is through a thick Paleozoic carbonate rock sequence. Throughout the flow system, ground water flows through zones of high transmissivity that have resulted from regional faulting and fracturing. The conceptual model of the Death Valley regional ground-water flow system used for this study is adapted from the two previous ground-water modeling studies. The three-dimensional digital hydrogeologic framework model developed for the region also contains elements of both of the hydrogeologic framework models used in the previous investigations. As dictated by project scope, very little reinterpretation and refinement were made where these two framework models disagree; therefore, limitations in the hydrogeologic representation of the flow system exist. Despite limitations, the framework model provides the best representation to date of the hydrogeologic units and structures that control regional ground-water flow and serves as an important information source used to construct and calibrate the predevelopment, steady-state flow model. In addition to the hydrogeologic framework, a complex array of mechanisms accounts for flow into, through, and out of the regional ground-water flow system. Natural discharges from the regional ground-water flow system occur by evapotranspiration, springs, and subsurface outflow. In this study, evapotranspiration rates were adapted from a related investigation that developed maps of evapotranspiration areas and computed rates from micrometeorological data collected within the local area over a multiyear period. In some cases, historical spring flow records were used to derive ground-water discharge rates for isolated regional springs. For this investigation, a process-based, numerical model was developed to estimat

Modeling of Oxygen Transport Across Tumor Multicellular Layers

PubMed Central

Braun, Rod D.; Beatty, Alexis L.

2007-01-01

Purpose Tumor oxygen level plays a major role in the response of tumors to different treatments. The purpose of this study was to develop a method of determining oxygen transport properties in a recently developed 3-D model of tumor parenchyma, the multicellular layer (MCL). Methods OCM-1 human choroidal melanoma cells were grown as 3-D MCL on collagen-coated culture plate inserts. A recessed-cathode oxygen microelectrode was used to measure oxygen tension (PO2) profiles across 8 different MCL from the free surface to the insert membrane. The profiles were fitted to four different one-dimensional diffusion models: 1-, 2-, and 3-region models with uniform oxygen consumption (q) in each region and a modified 3-region model with a central region where q=0 and PO2=0. Results Depending upon the presence of a central region of anoxia, the PO2 profiles were fitted best by either the two-region model or the modified 3-region model. Consumption of tumor cells near the insert membrane was higher than that of cells close to the free surface (33.1 ± 13.6 x 10−4 vs. 11.8 ± 6.7 x 10−4 mm Hg/μm2, respectively). Conclusions The model is useful for determining oxygenation and consumption in MCL, especially for cell lines that cannot be grown as spheroids. In the future, this model will permit the study of parameters important in tumor oxygenation in vitro. PMID:17196225

A Study of Tourism Dynamics in Three Italian Regions Using a Nonautonomous Integrable Lotka–Volterra Model

PubMed Central

Romano, Alessandro

2016-01-01

This article is a first application of an integrable nonautonomous Lotka–Volterra (LV) model to the study of tourism dynamics. In particular, we analyze the interaction in terms of touristic flows among three Italian regions. Confirming an hypothesis advanced by recent theoretical works, we find that these regions not only compete against each other, but at times they also proceed in mutualism. Moreover, the kind and the intensity of the interaction changes over time, suggesting that dynamic models can play a vital role in the study of touristic flows. PMID:27661615

An integrated geophysical study of north African and Mediterranean lithospheric structure

NASA Astrophysics Data System (ADS)

Dial, Paul Joseph

1998-07-01

This dissertation utilizes gravity and seismic waveform modeling techniques to: (1) determine models of lithospheric structure across northern African through gravity modeling and (2) determine lithospheric and crustal structure and seismic wave propagation characteristics across northern Africa and the Mediterranean region. The purpose of the gravity investigation was to construct models of lithospheric structure across northern Africa through the analysis of gravity data constrained by previous geological and geophysical studies. Three lithospheric models were constructed from Bouguer gravity data using computer modeling, and the gravity data was wavelength-filtered to investigate the relative depth and extent of the structures associated with the major anomalies. In the Atlas Mountains area, the resulting earth models showed slightly greater crustal thickness than those of previous studies if a low density mantle region is not included in the models. However, if a low density mantle region (density = 3.25 g/cm3) was included beneath the Atlas, the earth models showed little crustal thickening (38 km), in accord with previous seismic studies. The second portion of the research consisted of seismic waveform modeling of regional and teleseismic events to determine crustal and lithospheric structure across northern Africa and the Mediterranean. A total of 174 seismograms (145 at regional distances (200--1400 km) and 29 with epicentral distances exceeding 1900 km) were modeled using 1-D velocity models and a reflectivity code. At regional distances from four stations surrounding the western Mediterranean basin (MAL, TOL, PTO and AQU) and one station near the Red Sea (HLW), 1-D velocity models can satisfactorily model the relative amplitudes of both the Pnl and surface wave portions of the seismograms. Modeling of propagation paths greater than 1900 km was also conducted across northern Africa and the Mediterranean. The results indicate that the S-wave velocity model of Corchete et al. (1995) is more appropriate for the Iberian Peninsula, southwestern Mediterranean basin and northwest African coast than the other models tested. This model was better able to predict both the timing and amplitudes of the observed Sn and surface wave components on the observed seismograms. (Abstract shortened by UMI.)

Dynamic coupling of regional atmosphere to biosphere in the new generation regional climate system model REMO-iMOVE

NASA Astrophysics Data System (ADS)

Wilhelm, C.; Rechid, D.; Jacob, D.

2013-05-01

The main objective of this study is the coupling of the regional climate model REMO to a 3rd generation land surface scheme and the evaluation of the new model version of REMO, called REMO with interactive MOsaic-based VEgetation: REMO-iMOVE. Attention is paid to the documentation of the technical aspects of the new model constituents and the coupling mechanism. We compare simulation results of REMO-iMOVE and of the reference version REMO2009, to investigate the sensitivity of the regional model to the new land surface scheme. An 11 yr climate model run (1995-2005), forced with ECMWF ERA-Interim lateral boundary conditions, over Europe in 0.44° resolution of both model versions was carried out, to represent present day European climate. The result of these experiments are compared to multiple temperature, precipitation, heat flux and leaf area index observation data, to determine the differences in the model versions. The new model version has further the ability to model net primary productivity for the given plant functional types. This new feature is thoroughly evaluated by literature values of net primary productivity of different plant species in European climatic regions. The new model version REMO-iMOVE is able to model the European climate in the same quality as the parent model version REMO2009 does. The differences in the results of the two model versions stem from the differences in the dynamics of vegetation cover and density and can be distinct in some regions, due to the influences of these parameters to the surface heat and moisture fluxes. The modeled inter-annual variability in the phenology as well as the net primary productivity lays in the range of observations and literature values for most European regions. This study also reveals the need for a more sophisticated soil moisture representation in the newly developed model version REMO-iMOVE to be able to treat the differences in plant functional types. This gets especially important if the model will be used in dynamic vegetation studies.

EVALUATION OF THE REAL-TIME AIR-QUALITY MODEL USING THE RAPS (REGIONAL AIR POLLUTION STUDY) DATA BASE. VOLUME 3. PROGRAM USER'S GUIDE

EPA Science Inventory

The theory and programming of statistical tests for evaluating the Real-Time Air-Quality Model (RAM) using the Regional Air Pollution Study (RAPS) data base are fully documented in four volumes. Moreover, the tests are generally applicable to other model evaluation problems. Volu...

EVALUATION OF THE REAL-TIME AIR-QUALITY MODEL USING THE RAPS (REGIONAL AIR POLLUTION STUDY) DATA BASE. VOLUME 4. EVALUATION GUIDE

EPA Science Inventory

The theory and programming of statistical tests for evaluating the Real-Time Air-Quality Model (RAM) using the Regional Air Pollution Study (RAPS) data base are fully documented in four volumes. Moreover, the tests are generally applicable to other model evaluation problems. Volu...

Bayesian inference of stress release models applied to some Italian seismogenic zones

NASA Astrophysics Data System (ADS)

Rotondi, R.; Varini, E.

2007-04-01

In this paper, we evaluate the seismic hazard of a region in southern Italy by analysing stress release models from the Bayesian viewpoint; the data are drawn from the most recent version of the parametric catalogue of Italian earthquakes. For estimation we just use the events up to 1992, then we forecast the date of the next event through a stochastic simulation method and we compare the result with the really occurred shocks in the span 1993-2002. The original version of the stress release model, proposed by Vere-Jones in 1978, transposes Reid's elastic rebound theory in the framework of stochastic point processes. Since the nineties enriched versions of this model have appeared in the literature, applied to historical catalogues from China, Iran, Japan; they envisage the identification of independent or interacting tectonic subunits constituting the region under exam. It follows that the stress release models, designed for regional analyses, are evolving towards studies on fault segments, realizing some degree of convergence to those models that start from an individual fault and, considering the interactions with nearby segments, are driven to studies on regional scale. The optimal performance of the models we consider depends on a set of choices among which: the seismogenic region and possible subzones, the threshold magnitude, the length of the time period. In this paper, we focus our attention on the influence of the subdivision of the region under exam into tectonic units; in the light of the recent studies on the fault segmentation model of Italy we propose a partition of Sannio-Matese-Ofanto-Irpinia, one of the most seismically active region in southern Italy. The results show that the performance of the stress release models improves in terms of both fitting and forecasting when the region is split up into parts including new information about potential seismogenic sources.

Regional TEC model under quiet geomagnetic conditions and low-to-moderate solar activity based on CODE GIMs

NASA Astrophysics Data System (ADS)

Feng, Jiandi; Jiang, Weiping; Wang, Zhengtao; Zhao, Zhenzhen; Nie, Linjuan

2017-08-01

Global empirical total electron content (TEC) models based on TEC maps effectively describe the average behavior of the ionosphere. However, the accuracy of these global models for a certain region may not be ideal. Due to the number and distribution of the International GNSS Service (IGS) stations, the accuracy of TEC maps is geographically different. The modeling database derived from the global TEC maps with different accuracy is likely one of the main reasons that limits the accuracy of the new models. Moreover, many anomalies in the ionosphere are geographic or geomagnetic dependent, and as such the accuracy of global models can deteriorate if these anomalies are not fully incorporated into the modeling approach. For regional models built in small areas, these influences on modeling are immensely weakened. Thus, the regional TEC models may better reflect the temporal and spatial variations of TEC. In our previous work (Feng et al., 2016), a regional TEC model TECM-NEC is proposed for northeast China. However, this model is only directed against the typical region of Mid-latitude Summer Nighttime Anomaly (MSNA) occurrence, which is meaningless in other regions without MSNA. Following the technique of TECM-NEC model, this study proposes another regional empirical TEC model for other regions in mid-latitudes. Taking a small area BeiJing-TianJin-Tangshan (JJT) region (37.5°-42.5° N, 115°-120° E) in China as an example, a regional empirical TEC model (TECM-JJT) is proposed using the TEC grid data from January 1, 1999 to June 30, 2015 provided by the Center for Orbit Determination in Europe (CODE) under quiet geomagnetic conditions. The TECM-JJT model fits the input CODE TEC data with a bias of 0.11TECU and a root mean square error of 3.26TECU. Result shows that the regional model TECM-JJT is consistent with CODE TEC data and GPS-TEC data.

Generating High Resolution Climate Scenarios Through Regional Climate Modelling Over Southern Africa

NASA Astrophysics Data System (ADS)

Ndhlovu, G. Z.; Woyessa, Y. E.; Vijayaraghavan, S.

2017-12-01

limate change has impacted the global environment and the Continent of Africa, especially Southern Africa, regarded as one of the most vulnerable regions in Africa, has not been spared from these impacts. Global Climate Models (GCMs) with coarse horizontal resolutions of 150-300 km do not provide sufficient details at the local basin scale due to mismatch between the size of river basins and the grid cell of the GCM. This makes it difficult to apply the outputs of GCMs directly to impact studies such as hydrological modelling. This necessitates the use of regional climate modelling at high resolutions that provide detailed information at regional and local scales to study both climate change and its impacts. To this end, an experiment was set up and conducted with PRECIS, a regional climate model, to generate climate scenarios at a high resolution of 25km for the local region in Zambezi River basin of Southern Africa. The major input data used included lateral and surface boundary conditions based on the GCMs. The data is processed, analysed and compared with CORDEX climate change project data generated for Africa. This paper, highlights the major differences of the climate scenarios generated by PRECIS Model and CORDEX Project for Africa and further gives recommendations for further research on generation of climate scenarios. The climatic variables such as precipitation and temperatures have been analysed for flood and droughts in the region. The paper also describes the setting up and running of an experiment using a high-resolution PRECIS model. In addition, a description has been made in running the model and generating the output variables on a sub basin scale. Regional climate modelling which provides information on climate change impact may lead to enhanced understanding of adaptive water resources management. Understanding the regional climate modelling results on sub basin scale is the first step in analysing complex hydrological processes and a basis for designing of adaptation and mitigation strategies in the region. Key words: Climate change, regional climate modelling, hydrological processes, extremes, scenarios [1] Corresponding author: Email:gndhlovu@cut.ac.za Tel:+27 (0) 51 507 3072

Numerical Simulation of Regional Circulation in the Monterey Bay Region

NASA Technical Reports Server (NTRS)

Tseng, Y. H.; Dietrich, D. E.; Ferziger, J. H.

2003-01-01

The objective of this study is to produce a high-resolution numerical model of Mon- terey Bay area in which the dynamics are determined by the complex geometry of the coastline, steep bathymetry, and the in uence of the water masses that constitute the CCS. Our goal is to simulate the regional-scale ocean response with realistic dynamics (annual cycle), forcing, and domain. In particular, we focus on non-hydrostatic e ects (by comparing the results of hydrostatic and non-hydrostatic models) and the role of complex geometry, i.e. the bay and submarine canyon, on the nearshore circulation. To the best of our knowledge, the current study is the rst to simulate the regional circulation in the vicinity of Monterey Bay using a non-hydrostatic model. Section 2 introduces the high resolution Monterey Bay area regional model (MBARM). Section 3 provides the results and veri cation with mooring and satellite data. Section 4 compares the results of hydrostatic and non-hydrostatic models.

Ionospheric model-observation comparisons: E layer at Arecibo Incorporation of SDO-EVE solar irradiances

NASA Astrophysics Data System (ADS)

Sojka, Jan J.; Jensen, Joseph B.; David, Michael; Schunk, Robert W.; Woods, Tom; Eparvier, Frank; Sulzer, Michael P.; Gonzalez, Sixto A.; Eccles, J. Vincent

2014-05-01

This study evaluates how the new irradiance observations from the NASA Solar Dynamics Observatory (SDO) Extreme Ultraviolet Variability Experiment (EVE) can, with its high spectral resolution and 10 s cadence, improve the modeling of the E region. To demonstrate this a campaign combining EVE observations with that of the NSF Arecibo incoherent scatter radar (ISR) was conducted. The ISR provides E region electron density observations with high-altitude resolution, 300 m, and absolute densities using the plasma line technique. Two independent ionospheric models were used, the Utah State University Time-Dependent Ionospheric Model (TDIM) and Space Environment Corporation's Data-Driven D Region (DDDR) model. Each used the same EVE irradiance spectrum binned at 1 nm resolution from 0.1 to 106 nm. At the E region peak the modeled TDIM density is 20% lower and that of the DDDR is 6% higher than observed. These differences could correspond to a 36% lower (TDIM) and 12% higher (DDDR) production rate if the differences were entirely attributed to the solar irradiance source. The detailed profile shapes that included the E region altitude and that of the valley region were only qualitatively similar to observations. Differences on the order of a neutral-scale height were present. Neither model captured a distinct dawn to dusk tilt in the E region peak altitude. A model sensitivity study demonstrated how future improved spectral resolution of the 0.1 to 7 nm irradiance could account for some of these model shortcomings although other relevant processes are also poorly modeled.

Examining South Atlantic Subtropical Cyclone Anita using the Satellite-Enhanced Regional Downscaling for Applied Studies Hourly Outputs

NASA Astrophysics Data System (ADS)

Vaicberg, H.; Palmeira, A. C. P. A.; Nunes, A.

2017-12-01

Studies on South Atlantic cyclones are mainly compromised by scarcity of observations. Therefore, remote sensing and global (re) analysis products are usually employed in investigations of their evolution. However, the frequent use of global reanalysis might difficult the assessment of the characteristics of the cyclones found in South Atlantic. In that regard, studies on "subtropical" cyclones have been performed using the 25-km resolution, Satellite-enhanced Regional Downscaling for Applied Studies (SRDAS), a product developed at the Federal University of Rio de Janeiro in Brazil. In SRDAS, the Regional Spectral Model assimilates precipitation estimates from environmental satellites, while dynamically downscaling a global reanalysis using the spectral nudging technique to maintain the large-scale features in agreement with the regional model solution. The use of regional models in the downscaling of general circulation models provides more detailed information on weather and climate. As a way of illustrating the usefulness of SRDAS in the study of the subtropical South Atlantic cyclones, the subtropical cyclone Anita was selected because of its intensity. Anita developed near Brazilian south/southeast coast, with damages to local communities. Comparisons with available observations demonstrated the skill of SRDAS in simulating such an extreme event.

Wrong, but useful: regional species distribution models may not be improved by range-wide data under biased sampling.

PubMed

El-Gabbas, Ahmed; Dormann, Carsten F

2018-02-01

Species distribution modeling (SDM) is an essential method in ecology and conservation. SDMs are often calibrated within one country's borders, typically along a limited environmental gradient with biased and incomplete data, making the quality of these models questionable. In this study, we evaluated how adequate are national presence-only data for calibrating regional SDMs. We trained SDMs for Egyptian bat species at two different scales: only within Egypt and at a species-specific global extent. We used two modeling algorithms: Maxent and elastic net, both under the point-process modeling framework. For each modeling algorithm, we measured the congruence of the predictions of global and regional models for Egypt, assuming that the lower the congruence, the lower the appropriateness of the Egyptian dataset to describe the species' niche. We inspected the effect of incorporating predictions from global models as additional predictor ("prior") to regional models, and quantified the improvement in terms of AUC and the congruence between regional models run with and without priors. Moreover, we analyzed predictive performance improvements after correction for sampling bias at both scales. On average, predictions from global and regional models in Egypt only weakly concur. Collectively, the use of priors did not lead to much improvement: similar AUC and high congruence between regional models calibrated with and without priors. Correction for sampling bias led to higher model performance, whatever prior used, making the use of priors less pronounced. Under biased and incomplete sampling, the use of global bats data did not improve regional model performance. Without enough bias-free regional data, we cannot objectively identify the actual improvement of regional models after incorporating information from the global niche. However, we still believe in great potential for global model predictions to guide future surveys and improve regional sampling in data-poor regions.

Karst medium characterization and simulation of groundwater flow in Lijiang Riversed, China

NASA Astrophysics Data System (ADS)

Hu, B. X.

2015-12-01

It is important to study water and carbon cycle processes for water resource management, pollution prevention and global warming influence on southwest karst region of China. Lijiang river basin is selected as our study region. Interdisciplinary field and laboratory experiments with various technologies are conducted to characterize the karst aquifers in detail. Key processes in the karst water cycle and carbon cycle are determined. Based on the MODFLOW-CFP model, new watershed flow and carbon cycle models are developed coupled subsurface and surface water flow models, flow and chemical/biological models. Our study is focused on the karst springshed in Mao village. The mechanisms coupling carbon cycle and water cycle are explored. Parallel computing technology is used to construct the numerical model for the carbon cycle and water cycle in the small scale watershed, which are calibrated and verified by field observations. The developed coupling model for the small scale watershed is extended to a large scale watershed considering the scale effect of model parameters and proper model structure simplification. The large scale watershed model is used to study water cycle and carbon cycle in Lijiang rivershed, and to calculate the carbon flux and carbon sinks in the Lijiang river basin. The study results provide scientific methods for water resources management and environmental protection in southwest karst region corresponding to global climate change. This study could provide basic theory and simulation method for geological carbon sequestration in China karst region.

Simulation of groundwater flow and evaluation of carbon sink in Lijiang Rivershed, China

NASA Astrophysics Data System (ADS)

Hu, Bill X.; Cao, Jianhua; Tong, Juxiu; Gao, Bing

2016-04-01

It is important to study water and carbon cycle processes for water resource management, pollution prevention and global warming influence on southwest karst region of China. Lijiang river basin is selected as our study region. Interdisciplinary field and laboratory experiments with various technologies are conducted to characterize the karst aquifers in detail. Key processes in the karst water cycle and carbon cycle are determined. Based on the MODFLOW-CFP model, new watershed flow and carbon cycle models are developed coupled subsurface and surface water flow models, flow and chemical/biological models. Our study is focused on the karst springshed in Mao village. The mechanisms coupling carbon cycle and water cycle are explored. Parallel computing technology is used to construct the numerical model for the carbon cycle and water cycle in the small scale watershed, which are calibrated and verified by field observations. The developed coupling model for the small scale watershed is extended to a large scale watershed considering the scale effect of model parameters and proper model structure simplification. The large scale watershed model is used to study water cycle and carbon cycle in Lijiang rivershed, and to calculate the carbon flux and carbon sinks in the Lijiang river basin. The study results provide scientific methods for water resources management and environmental protection in southwest karst region corresponding to global climate change. This study could provide basic theory and simulation method for geological carbon sequestration in China karst region.

Global and Regional Modeling of Long-Range Transport and Intercontinental Source-Receptor Linkages

EPA Science Inventory

In this study, we compare air quality over North America simulated by the C-IFS global model and the CMAQ regional model driven by boundary conditions from C-IFS against surface and upper air observations. Results indicate substantial differences in model performance for surface ...

Assessment of the performance of CORDEX-South Asia experiments for monsoonal precipitation over the Himalayan region during present climate: part I

NASA Astrophysics Data System (ADS)

Ghimire, S.; Choudhary, A.; Dimri, A. P.

2018-04-01

Analysis of regional climate simulations to evaluate the ability of 11 Coordinated Regional Climate Downscaling Experiment in South Asia experiments (CORDEX-South Asia) along with their ensemble to produce precipitation from June to September (JJAS) over the Himalayan region have been carried out. These suite of 11 combinations come from 6 regional climate models (RCMs) driven with 10 initial and boundary conditions from different global climate models and are collectively referred here as 11 CORDEX South Asia experiments. All the RCMs use a similar domain and are having similar spatial resolution of 0.44° ( 50 km). The set of experiments are considered to study precipitation sensitivity associated with the Indian summer monsoon (ISM) over the study region. This effort is made as ISM plays a vital role in summertime precipitation over the Himalayan region which acts as driver for the sustenance of habitat, population, crop, glacier, hydrology etc. In addition, so far the summer monsoon precipitation climatology over the Himalayan region has not been studied with the help of CORDEX data. Thus this study is initiated to evaluate the ability of the experiments and their ensemble in reproducing the characteristics of summer monsoon precipitation over Himalayan region, for the present climate (1970-2005). The precipitation climatology, annual precipitation cycles and interannual variabilities from each simulation have been assessed against the gridded observational dataset: Asian Precipitation-Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources for the given time period. Further, after the selection of the better performing experiment the frequency distribution of precipitation was also studied. In this study, an approach has also been made to study the degree of agreement among individual experiments as a way to quantify the uncertainty among them. The experiments though show a wide variation among themselves and individually over time and space in simulating precipitation distribution over the study region, but noticeably along the foothills of the Himalayas all the simulations show dry precipitation bias against the corresponding observation. In addition, as we move towards higher elevation regions these experiments in general show wet bias. The experiment driven by EC-EARTH global climate model and downscaled using Rossby Center regional Atmospheric model version 4 developed by Swedish Meteorological and Hydrological Institute (SMHI-RCA4) simulate precipitation closely in correspondence with the observation. The ensemble outperforms the result of individual experiments. Correspondingly, different kinds of statistical analysis like spatial and temporal correlation, Taylor diagram, frequency distribution and scatter plot have been performed to compare the model output with observation and to explain the associated resemblance, robustness and dynamics statistically. Through the bias and ensemble spread analysis, an estimation of the uncertainty of the model fields and the degree of agreement among them has also been carried out in this study. Overview of the study suggests that these experiments facilitate precipitation evolution and structure over the Himalayan region with certain degree of uncertainty.

Hydrologic Modeling of Boreal Forest Ecosystems

NASA Technical Reports Server (NTRS)

Haddeland, I.; Lettenmaier, D. P.

1995-01-01

This study focused on the hydrologic response, including vegetation water use, of two test regions within the Boreal-Ecosystem-Atmosphere Study (BOREAS) region in the Canadian boreal forest, one north of Prince Albert, Saskatchewan, and the other near Thompson, Manitoba. Fluxes of moisture and heat were studied using a spatially distributed hydrology soil-vegetation-model (DHSVM).

Wolf Creek Research Basin Cold REgion Process Studies - 1992-2003

NASA Astrophysics Data System (ADS)

Janowicz, R.; Hedstrom, N.; Pomeroy, J.; Granger, R.; Carey, S.

2004-12-01

The development of hydrological models in northern regions are complicated by cold region processes. Sparse vegetation influences snowpack accumulation, redistribution and melt, frozen ground effects infiltration and runoff and cold soils in the summer effect evapotranspiration rates. Situated in the upper Yukon River watershed, the 195 km2 Wolf Creek Research Basin was instrumented in 1992 to calibrate hydrologic flow models, and has since evolved into a comprehensive study of cold region processes and linkages, contributing significantly to hydrological and climate change modelling. Studies include those of precipitation distribution, snowpack accumulation and redistribution, energy balance, snowmelt infiltration, and water balance. Studies of the spatial variability of hydrometeorological data demonstrate the importance of physical parameters on their distribution and control on runoff processes. Many studies have also identified the complex interaction of several of the physical parameters, including topography, vegetation and frozen ground (seasonal or permafrost) as important. They also show that there is a fundamental, underlying spatial structure to the watershed that must be adequately represented in parameterization schemes for scaling and watershed modelling. The specific results of numerous studies are presented.

Improved simulation of regional CO2 surface concentrations using GEOS-Chem and fluxes from VEGAS

NASA Astrophysics Data System (ADS)

Chen, Z. H.; Zhu, J.; Zeng, N.

2013-08-01

CO2 measurements have been combined with simulated CO2 distributions from a transport model in order to produce the optimal estimates of CO2 surface fluxes in inverse modeling. However, one persistent problem in using model-observation comparisons for this goal relates to the issue of compatibility. Observations at a single station reflect all underlying processes of various scales. These processes usually cannot be fully resolved by model simulations at the grid points nearest the station due to lack of spatial or temporal resolution or missing processes in the model. In this study the stations in one region were grouped based on the amplitude and phase of the seasonal cycle at each station. The regionally averaged CO2 at all stations in one region represents the regional CO2 concentration of this region. The regional CO2 concentrations from model simulations and observations were used to evaluate the regional model results. The difference of the regional CO2 concentration between observation and modeled results reflects the uncertainty of the large-scale flux in the region where the grouped stations are. We compared the regional CO2 concentrations between model results with biospheric fluxes from the Carnegie-Ames-Stanford Approach (CASA) and VEgetation-Global-Atmosphere-Soil (VEGAS) models, and used observations from GLOBALVIEW-CO2 to evaluate the regional model results. The results show the largest difference of the regionally averaged values between simulations with fluxes from VEGAS and observations is less than 5 ppm for North American boreal, North American temperate, Eurasian boreal, Eurasian temperate and Europe, which is smaller than the largest difference between CASA simulations and observations (more than 5 ppm). There is still a large difference between two model results and observations for the regional CO2 concentration in the North Atlantic, Indian Ocean, and South Pacific tropics. The regionally averaged CO2 concentrations will be helpful for comparing CO2 concentrations from modeled results and observations and evaluating regional surface fluxes from different methods.

A Probabilistic Tsunami Hazard Study of the Auckland Region, Part II: Inundation Modelling and Hazard Assessment

NASA Astrophysics Data System (ADS)

Lane, E. M.; Gillibrand, P. A.; Wang, X.; Power, W.

2013-09-01

Regional source tsunamis pose a potentially devastating hazard to communities and infrastructure on the New Zealand coast. But major events are very uncommon. This dichotomy of infrequent but potentially devastating hazards makes realistic assessment of the risk challenging. Here, we describe a method to determine a probabilistic assessment of the tsunami hazard by regional source tsunamis with an "Average Recurrence Interval" of 2,500-years. The method is applied to the east Auckland region of New Zealand. From an assessment of potential regional tsunamigenic events over 100,000 years, the inundation of the Auckland region from the worst 100 events is modelled using a hydrodynamic model and probabilistic inundation depths on a 2,500-year time scale were determined. Tidal effects on the potential inundation were included by coupling the predicted wave heights with the probability density function of tidal heights at the inundation site. Results show that the more exposed northern section of the east coast and outer islands in the Hauraki Gulf face the greatest hazard from regional tsunamis in the Auckland region. Incorporating tidal effects into predictions of inundation reduced the predicted hazard compared to modelling all the tsunamis arriving at high tide giving a more accurate hazard assessment on the specified time scale. This study presents the first probabilistic analysis of dynamic modelling of tsunami inundation for the New Zealand coast and as such provides the most comprehensive assessment of tsunami inundation of the Auckland region from regional source tsunamis available to date.

Integrating global socio-economic influences into a regional land use change model for China

NASA Astrophysics Data System (ADS)

Xu, Xia; Gao, Qiong; Peng, Changhui; Cui, Xuefeng; Liu, Yinghui; Jiang, Li

2014-03-01

With rapid economic development and urbanization, land use in China has experienced huge changes in recent years; and this will probably continue in the future. Land use problems in China are urgent and need further study. Rapid land-use change and economic development make China an ideal region for integrated land use change studies, particularly the examination of multiple factors and global-regional interactions in the context of global economic integration. This paper presents an integrated modeling approach to examine the impact of global socio-economic processes on land use changes at a regional scale. We develop an integrated model system by coupling a simple global socio-economic model (GLOBFOOD) and regional spatial allocation model (CLUE). The model system is illustrated with an application to land use in China. For a given climate change, population growth, and various socio-economic situations, a global socio-economic model simulates the impact of global market and economy on land use, and quantifies changes of different land use types. The land use spatial distribution model decides the type of land use most appropriate in each spatial grid by employing a weighted suitability index, derived from expert knowledge about the ecosystem state and site conditions. A series of model simulations will be conducted and analyzed to demonstrate the ability of the integrated model to link global socioeconomic factors with regional land use changes in China. The results allow an exploration of the future dynamics of land use and landscapes in China.

The Contribution of CEOP Data to the Understanding and Modeling of Monsoon Systems

NASA Technical Reports Server (NTRS)

Lau, William K. M.

2005-01-01

CEOP has contributed and will continue to provide integrated data sets from diverse platforms for better understanding of the water and energy cycles, and for validaintg models. In this talk, I will show examples of how CEOP has contributed to the formulation of a strategy for the study of the monsoon as a system. The CEOP data concept has led to the development of the CEOP Inter-Monsoon Studies (CIMS), which focuses on the identification of model bias, and improvement of model physics such as the diurnal and annual cycles. A multi-model validation project focusing on diurnal variability of the East Asian monsoon, and using CEOP reference site data, as well as CEOP integrated satellite data is now ongoing. Preliminary studies show that climate models have difficulties in simulating the diurnal signals of total rainfall, rainfall intensity and frequency of occurrence, which have different peak hours, depending on locations. Further more model diurnal cycle of rainfall in monsoon regions tend to lead the observed by about 2-3 hours. These model bias offer insight into lack of, or poor representation of, key components of the convective and stratiform rainfall. The CEOP data also stimulated studies to compare and contrasts monsoon variability in different parts of the world. It was found that seasonal wind reversal, orographic effects, monsoon depressions, meso-scale convective complexes, SST and land surface land influences are common features in all monsoon regions. Strong intraseasonal variability is present in all monsoon regions. While there is a clear demarcation of onset, breaks and withdrawal in the Asian and Australian monsoon region associated with climatological intraseasonal variabillity, it is less clear in the American and Africa monsoon regions. The examination of satellite and reference site data in monsoon has led to preliminary model experiments to study the impact of aerosol on monsoon variability. I will show examples of how the study of the dynamics of aerosol-water cycle interactions in the monsoon region, can be best achieved using the CEOP data and modeling strategy.

Regional Geoid Modeling Compared to Ocean Surface Observations

NASA Astrophysics Data System (ADS)

Roman, D. R.; Saleh, J.; Wang, Y. M.

2007-05-01

Aerogravity over a limited coastal region of the northern Gulf of Mexico enhanced and rectified the local gravity field signal. In turn, these data improved the derived geoid height model based on comparison with dynamic ocean topography (DOT) and tide gage information at eleven stations. Additionally, lidar observations were analyzed along nearly 50 profiles to estimate the reliability of these models into the offshore region. The overall comparison shows dm-level agreement between the various geoid and DOT models and ocean surface observations. An approximate 30 cm bias must still be explained; however, the results of this study point to the potential for further cooperative studies between oceanographers and geodesists.

What spatial scales are believable for climate model projections of sea surface temperature?

NASA Astrophysics Data System (ADS)

Kwiatkowski, Lester; Halloran, Paul R.; Mumby, Peter J.; Stephenson, David B.

2014-09-01

Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (<8°). Our findings suggest that output from current generation ESMs is not yet suitable for making sub-regional projections of change in coral bleaching frequency and other marine processes linked to SST warming.

BETR North America: A regionally segmented multimedia contaminant fate model for North America

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacLeod, M.; Woodfine, D.G.; Mackay, D.

We present the Berkeley-Trent North American contaminant fate model (BETR North America), a regionally segmented multimedia contaminant fate model based on the fugacity concept. The model is built on a framework that links contaminant fate models of individual regions, and is generally applicable to large, spatially heterogeneous areas. The North American environment is modeled as 24 ecological regions, within each region contaminant fate is described using a 7 compartment multimedia fugacity model including a vertically segmented atmosphere, freshwater, freshwater sediment, soil, coastal water and vegetation compartments. Inter-regional transport of contaminants in the atmosphere, freshwater and coastal water is described usingmore » a database of hydrological and meteorological data compiled with Geographical Information Systems (GIS) techniques. Steady-state and dynamic solutions to the 168 mass balance equations that make up the linked model for North America are discussed, and an illustrative case study of toxaphene transport from the southern United States to the Great Lakes Basin is presented. Regionally segmented models such as BETR North America can provide a critical link between evaluative models of long-range transport potential and contaminant concentrations observed in remote regions. The continent-scale mass balance calculated by the model provides a sound basis for evaluating long-range transport potential of organic pollutants, and formulation of continent scale management and regulatory strategies for chemicals.« less

Multi-objective optimization for evaluation of simulation fidelity for precipitation, cloudiness and insolation in regional climate models

NASA Astrophysics Data System (ADS)

Lee, H.

2016-12-01

Precipitation is one of the most important climate variables that are taken into account in studying regional climate. Nevertheless, how precipitation will respond to a changing climate and even its mean state in the current climate are not well represented in regional climate models (RCMs). Hence, comprehensive and mathematically rigorous methodologies to evaluate precipitation and related variables in multiple RCMs are required. The main objective of the current study is to evaluate the joint variability of climate variables related to model performance in simulating precipitation and condense multiple evaluation metrics into a single summary score. We use multi-objective optimization, a mathematical process that provides a set of optimal tradeoff solutions based on a range of evaluation metrics, to characterize the joint representation of precipitation, cloudiness and insolation in RCMs participating in the North American Regional Climate Change Assessment Program (NARCCAP) and Coordinated Regional Climate Downscaling Experiment-North America (CORDEX-NA). We also leverage ground observations, NASA satellite data and the Regional Climate Model Evaluation System (RCMES). Overall, the quantitative comparison of joint probability density functions between the three variables indicates that performance of each model differs markedly between sub-regions and also shows strong seasonal dependence. Because of the large variability across the models, it is important to evaluate models systematically and make future projections using only models showing relatively good performance. Our results indicate that the optimized multi-model ensemble always shows better performance than the arithmetic ensemble mean and may guide reliable future projections.

Sensitivity of WRF Regional Climate Simulations to Choice of Land Use Dataset

EPA Science Inventory

The goal of this study is to assess the sensitivity of regional climate simulations run with the Weather Research and Forecasting (WRF) model to the choice of datasets representing land use and land cover (LULC). Within a regional climate modeling application, an accurate repres...

Future Climate Change in the Baltic Sea Area

NASA Astrophysics Data System (ADS)

Bøssing Christensen, Ole; Kjellström, Erik; Zorita, Eduardo; Sonnenborg, Torben; Meier, Markus; Grinsted, Aslak

2015-04-01

Regional climate models have been used extensively since the first assessment of climate change in the Baltic Sea region published in 2008, not the least for studies of Europe (and including the Baltic Sea catchment area). Therefore, conclusions regarding climate model results have a better foundation than was the case for the first BACC report of 2008. This presentation will report model results regarding future climate. What is the state of understanding about future human-driven climate change? We will cover regional models, statistical downscaling, hydrological modelling, ocean modelling and sea-level change as it is projected for the Baltic Sea region. Collections of regional model simulations from the ENSEMBLES project for example, financed through the European 5th Framework Programme and the World Climate Research Programme Coordinated Regional Climate Downscaling Experiment, have made it possible to obtain an increasingly robust estimation of model uncertainty. While the first Baltic Sea assessment mainly used four simulations from the European 5th Framework Programme PRUDENCE project, an ensemble of 13 transient regional simulations with twice the horizontal resolution reaching the end of the 21st century has been available from the ENSEMBLES project; therefore it has been possible to obtain more quantitative assessments of model uncertainty. The literature about future climate change in the Baltic Sea region is largely built upon the ENSEMBLES project. Also within statistical downscaling, a considerable number of papers have been published, encompassing now the application of non-linear statistical models, projected changes in extremes and correction of climate model biases. The uncertainty of hydrological change has received increasing attention since the previous Baltic Sea assessment. Several studies on the propagation of uncertainties originating in GCMs, RCMs, and emission scenarios are presented. The number of studies on uncertainties related to downscaling and impact models is relatively small, but more are emerging. A large number of coupled climate-environmental scenario simulations for the Baltic Sea have been performed within the BONUS+ projects (ECOSUPPORT, INFLOW, AMBER and Baltic-C (2009-2011)), using various combinations of output from GCMs, RCMs, hydrological models and scenarios for load and emission of nutrients as forcing for Baltic Sea models. Such a large ensemble of scenario simulations for the Baltic Sea has never before been produced and enables for the first time an estimation of uncertainties.

Development and validation of a regional coupled forecasting system for S2S forecasts

NASA Astrophysics Data System (ADS)

Sun, R.; Subramanian, A. C.; Hoteit, I.; Miller, A. J.; Ralph, M.; Cornuelle, B. D.

2017-12-01

Accurate and efficient forecasting of oceanic and atmospheric circulation is essential for a wide variety of high-impact societal needs, including: weather extremes; environmental protection and coastal management; management of fisheries, marine conservation; water resources; and renewable energy. Effective forecasting relies on high model fidelity and accurate initialization of the models with observed state of the ocean-atmosphere-land coupled system. A regional coupled ocean-atmosphere model with the Weather Research and Forecasting (WRF) model and the MITGCM ocean model coupled using the ESMF (Earth System Modeling Framework) coupling framework is developed to resolve mesoscale air-sea feedbacks. The regional coupled model allows oceanic mixed layer heat and momentum to interact with the atmospheric boundary layer dynamics at the mesoscale and submesoscale spatiotemporal regimes, thus leading to feedbacks which are otherwise not resolved in coarse resolution global coupled forecasting systems or regional uncoupled forecasting systems. The model is tested in two scenarios in the mesoscale eddy rich Red Sea and Western Indian Ocean region as well as mesoscale eddies and fronts of the California Current System. Recent studies show evidence for air-sea interactions involving the oceanic mesoscale in these two regions which can enhance predictability on sub seasonal timescale. We will present results from this newly developed regional coupled ocean-atmosphere model for forecasts over the Red Sea region as well as the California Current region. The forecasts will be validated against insitu observations in the region as well as reanalysis fields.

The influence of spectral nudging on typhoon formation in regional climate models

NASA Astrophysics Data System (ADS)

Feser, Frauke; Barcikowska, Monika

2012-03-01

Regional climate models can successfully simulate tropical cyclones and typhoons. This has been shown and was evaluated for hindcast studies of the past few decades. But often global and regional weather phenomena are not simulated at the observed location, or occur too often or seldom even though the regional model is driven by global reanalysis data which constitute a near-realistic state of the global atmosphere. Therefore, several techniques have been developed in order to make the regional model follow the global state more closely. One is spectral nudging, which is applied for horizontal wind components with increasing strength for higher model levels in this study. The aim of this study is to show the influence that this method has on the formation of tropical cyclones (TC) in regional climate models. Two ensemble simulations (each with five simulations) were computed for Southeast Asia and the Northwestern Pacific for the typhoon season 2004, one with spectral nudging and one without. First of all, spectral nudging reduced the overall TC number by about a factor of 2. But the number of tracks which are similar to observed best track data (BTD) was greatly increased. Also, spatial track density patterns were found to be more similar when using spectral nudging. The tracks merge after a short time for the spectral nudging simulations and then follow the BTD closely; for the no nudge cases the similarity is greatly reduced. A comparison of seasonal precipitation, geopotential height, and temperature fields at several height levels with observations and reanalysis data showed overall a smaller ensemble spread, higher pattern correlations and reduced root mean square errors and biases for the spectral nudged simulations. Vertical temperature profiles for selected TCs indicate that spectral nudging is not inhibiting TC development at higher levels. Both the Madden-Julian Oscillation and monsoonal precipitation are reproduced realistically by the regional model, with results slightly closer to reanalysis data for the spectral nudged simulations. On the basis of this regional climate model hindcast study of a single typhoon season, spectral nudging seems to be favourable since it has mostly positive effects on typhoon formation, location and general circulation patterns in the generation areas of TCs.

Simulating Black Carbon and Dust and their Radiative Forcing in Seasonal Snow: A Case Study over North China with Field Campaign Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Chun; Hu, Zhiyuan; Qian, Yun

2014-10-30

A state-of-the-art regional model, WRF-Chem, is coupled with the SNICAR model that includes the sophisticated representation of snow metamorphism processes available for climate study. The coupled model is used to simulate the black carbon (BC) and dust concentrations and their radiative forcing in seasonal snow over North China in January-February of 2010, with extensive field measurements used to evaluate the model performance. In general, the model simulated spatial variability of BC and dust mass concentrations in the top snow layer (hereafter BCS and DSTS, respectively) are quantitatively or qualitatively consistent with observations. The model generally moderately underestimates BCS in themore » clean regions but significantly overestimates BCS in some polluted regions. Most model results fall into the uncertainty ranges of observations. The simulated BCS and DSTS are highest with >5000 ng g-1 and up to 5 mg g-1, respectively, over the source regions and reduce to <50 ng g-1 and <1 μg g-1, respectively, in the remote regions. BCS and DSTS introduce similar magnitude of radiative warming (~10 W m-2) in snowpack, which is comparable to the magnitude of surface radiative cooling due to BC and dust in the atmosphere. This study represents the first effort in using a regional modeling framework to simulate BC and dust and their direct radiative forcing in snow. Although a variety of observational datasets have been used to attribute model biases, some uncertainties in the results remain, which highlights the need for more observations, particularly concurrent measurements of atmospheric and snow aerosols and the deposition fluxes of aerosols, in future campaigns.« less

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C.

1993-01-01

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

Studying the location of SACs and DACs regions in the environment of hot emission stars

NASA Astrophysics Data System (ADS)

Antoniou, A.; Danezis, E.; Lyratzi, E.; Popović, L. Č.; Dimitrijević, M. S.; Theodossiou, E.

Hot emission stars (Oe and Be stars) present complex spectral line profiles, which are formed by a number of DACs and/or SACs. In order to explain and reproduce theoretically these complex line profiles we use the GR model (Gauss-Rotation model). This model presupposes that the regions, where the spectral lines are created, consist of a number of independent and successive absorbing or emitting density regions of matter. Here we are testing a new approach of the GR model, which supposes that the independent density regions are not successive. We use this new approach in the spectral lines of some Oe and Be stars and we compare the results of this method with the results deriving from the classical GR model that supposes successive regions.

Photo-chemical transport modelling of tropospheric ozone: A review

NASA Astrophysics Data System (ADS)

Sharma, Sumit; Sharma, Prateek; Khare, Mukesh

2017-06-01

Ground level ozone (GLO), a secondary pollutant having adverse impact on human health, ecology, and agricultural productivity, apart from being a major contributor to global warming, has been a subject matter of several studies. In order to identify appropriate strategies to control GLO levels, accurate assessment and prediction is essential, for which elaborate simulation and modelling is required. Several studies have been undertaken in the past to simulate GLO levels at different scales and for various applications. It is important to evaluate these studies, widely spread over in literature. This paper aims to critically review various studies that have been undertaken, especially in the past 15 years (2000-15) to model GLO. The review has been done of the studies that range over different spatial scales - urban to regional and continental to global. It also includes a review of performance evaluation and sensitivity analysis of photo-chemical transport models in order to assess the extent of application of these models and their predictive capability. The review indicates following major findings: (a) models tend to over-estimate the night-time GLO concentrations due to limited titration of GLO with NO within the model; (b) dominance of contribution from far-off regional sources to average ozone concentration in the urban region and higher contribution of local sources during days of high ozone episodes; requiring strategies for controlling precursor emissions at both regional and local scales; (c) greater influence of NOx over VOC in export of ozone from urban regions due to shifting of urban plumes from VOC-sensitive regime to NOx-sensitive as they move out from city centres to neighbouring rural regions; (d) models with finer resolution inputs perform better to a certain extent, however, further improvement in resolutions (beyond 10 km) did not show improvement always; (e) future projections show an increase in GLO concentrations mainly due to rise in temperatures and biogenic VOC emissions.

Inversion of Gravity Data to Define the Pre-Cenozoic Surface and Regional Structures Possibly Influencing Groundwater Flow in the Rainier Mesa Region, Nye County, Nevada.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas G. Hildenbrand; Geoffrey A. Phelps; Edward A. Mankinen

2006-09-21

A three-dimensional inversion of gravity data from the Rainier Mesa area and surrounding regions reveals a topographically complex pre-Cenozoic basement surface. This model of the depth to pre-Cenozoic basement rocks is intended for use in a 3D hydrogeologic model being constructed for the Rainier Mesa area. Prior to this study, our knowledge of the depth to pre-Cenozoic basement rocks was based on a regional model, applicable to general studies of the greater Nevada Test Site area but inappropriate for higher resolution modeling of ground-water flow across the Rainier Mesa area. The new model incorporates several changes that lead to significantmore » improvements over the previous regional view. First, the addition of constraining wells, encountering old volcanic rocks lying above but near pre-Cenozoic basement, prevents modeled basement from being too shallow. Second, an extensive literature and well data search has led to an increased understanding of the change of rock density with depth in the vicinity of Rainier Mesa. The third, and most important change, relates to the application of several depth-density relationships in the study area instead of a single generalized relationship, thereby improving the overall model fit. In general, the pre-Cenozoic basement surface deepens in the western part of the study area, delineating collapses within the Silent Canyon and Timber Mountain caldera complexes, and shallows in the east in the Eleana Range and Yucca Flat regions, where basement crops out. In the Rainier Mesa study area, basement is generally shallow (< 1 km). The new model identifies previously unrecognized structures within the pre-Cenozoic basement that may influence ground-water flow, such as a shallow basement ridge related to an inferred fault extending northward from Rainier Mesa into Kawich Valley.« less

Effects of lateral boundary condition resolution and update frequency on regional climate model predictions

NASA Astrophysics Data System (ADS)

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. Theoretically, regional down-scaling should act like a magnifying glass. It should reveal details on small scales which a global model cannot resolve, but it should not affect the large scale flow. As the development of the small scale features takes some time, it is important that the air stays long enough within the regional domain. The spin-up time of the small scale features is, of course, dependent on the resolution of the LBC and the resolution of the RCM. The second study examines the quality of decadal hind-casts over Europe of the decade 2001-2010 when the horizontal resolution of the driving model, namely 2.8°, 1.8°, 1.4°, 1.1°, from which the LBC are calculated, is altered. The study shows, that a smaller resolution gap between LBC resolution and RCM resolution might be beneficial.

Space, time, and the third dimension (model error)

USGS Publications Warehouse

Moss, Marshall E.

1979-01-01

The space-time tradeoff of hydrologic data collection (the ability to substitute spatial coverage for temporal extension of records or vice versa) is controlled jointly by the statistical properties of the phenomena that are being measured and by the model that is used to meld the information sources. The control exerted on the space-time tradeoff by the model and its accompanying errors has seldom been studied explicitly. The technique, known as Network Analyses for Regional Information (NARI), permits such a study of the regional regression model that is used to relate streamflow parameters to the physical and climatic characteristics of the drainage basin.The NARI technique shows that model improvement is a viable and sometimes necessary means of improving regional data collection systems. Model improvement provides an immediate increase in the accuracy of regional parameter estimation and also increases the information potential of future data collection. Model improvement, which can only be measured in a statistical sense, cannot be quantitatively estimated prior to its achievement; thus an attempt to upgrade a particular model entails a certain degree of risk on the part of the hydrologist.

Denitrogenation model for vacuum tank degasser

NASA Astrophysics Data System (ADS)

Gobinath, R.; Vetrivel Murugan, R.

2018-02-01

Nitrogen in steel is both beneficial and detrimental depending on grade of steel and its application. To get desired low nitrogen during vacuum degassing process, VD parameters namely vacuum level, argon flow rate and holding time has to optimized depending upon initial nitrogen level. In this work a mathematical model to simulate nitrogen removal in tank degasser is developed and how various VD parameters affects nitrogen removal is studied. Ladle water model studies with bottom purging have shown two distinct flow regions, namely the plume region and the outside plume region. The two regions are treated as two separate reactors exchanging mass between them and complete mixing is assumed in both the reactors. In the plume region, transfer of nitrogen to single bubble is simulated. At the gas-liquid metal interface (bubble interface) thermodynamic equilibrium is assumed and the transfer of nitrogen from bulk liquid metal in the plume region to the gas-metal interface is obtained using mass transport principles. The model predicts variation of Nitrogen content in both the reactors with time. The model is validated with industrial process and the predicted results were found to have fair agreement with the measured results.

Climate modeling for Yamal territory using supercomputer atmospheric circulation model ECHAM5-wiso

NASA Astrophysics Data System (ADS)

Denisova, N. Y.; Gribanov, K. G.; Werner, M.; Zakharov, V. I.

2015-11-01

Dependences of monthly means of regional averages of model atmospheric parameters on initial and boundary condition remoteness in the past are the subject of the study. We used atmospheric general circulation model ECHAM5-wiso for simulation of monthly means of regional averages of climate parameters for Yamal region and different periods of premodeling. Time interval was varied from several months to 12 years. We present dependences of model monthly means of regional averages of surface temperature, 2 m air temperature and humidity for December of 2000 on duration of premodeling. Comparison of these results with reanalysis data showed that best coincidence with true parameters could be reached if duration of pre-modelling is approximately 10 years.

Numerical simulation of mesoscale surface pressure features with trailing stratiform squall lines using WRF -ARW model over Gangetic West Bengal region

NASA Astrophysics Data System (ADS)

Dawn, Soma; Satyanarayana, A. N. V.

2018-01-01

In the present study, an attempt has been made to investigate the simulation of mesoscale surface pressure patterns like pre-squall mesolow, mesohigh and wake low associated with leading convective line-trailing stratiform (TS) squall lines over Gangetic West Bengal (GWB). For this purpose, a two way interactive triple nested domain with high resolution WRF model having2 km grid length in the innermost domain is used. The model simulated results are compared with the available in-situ observations obtained as a part of Severe Thunderstorm: Observations and Regional Modeling (STORM) programme, reflectivity products of Doppler Weather Radar (DWR) Kolkata and TRMM rainfall. Three TS squall lines (15 May 2009, 5 May 2010 and 7 May 2010) are chosen during pre-monsoon thunderstorm season for this study. The model simulated results of diurnal variation of temperature, relative humidity, wind speed and direction at the station Kharagpur in GWB region reveal a sudden fall in temperature, increase in the amount of relative humidity and sudden rise in wind speed during the arrival of the storms. Such results are well comparable with the observations though there are some leading or lagging of time in respect of actual occurrences of such events. The study indicates that the model is able to predict the occurrences of three typical surface pressure features namely: pre-squall mesolow, meso high and wake low. The predicted surface parameters like accumulated rainfall, maximum reflectivity and vertical profiles (temperature, relative humidity and winds) are well accorded with the observations. The convective and stratiform precipitation region of the TS squall lines are well represented by the model. A strong downdraft is observed to be a contributory factor for formation of mesohigh in the convective region of the squall line. Wake low is observed to reside in the stratiform rain region and the descending dry air at this place has triggered the wake low through adiabatic warming. This study has established the usefulness of the high resolution model in predicting trailing stratiform squall lines and its associated features over the study region.

Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

NASA Astrophysics Data System (ADS)

Zhang, Ying; Moges, Semu; Block, Paul

2018-01-01

Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

Development of Models for Regional Cardiac Surgery Centers

PubMed Central

Park, Choon Seon; Park, Nam Hee; Sim, Sung Bo; Yun, Sang Cheol; Ahn, Hye Mi; Kim, Myunghwa; Choi, Ji Suk; Kim, Myo Jeong; Kim, Hyunsu; Chee, Hyun Keun; Oh, Sanggi; Kang, Shinkwang; Lee, Sok-Goo; Shin, Jun Ho; Kim, Keonyeop; Lee, Kun Sei

2016-01-01

Background This study aimed to develop the models for regional cardiac surgery centers, which take regional characteristics into consideration, as a policy measure that could alleviate the concentration of cardiac surgery in the metropolitan area and enhance the accessibility for patients who reside in the regions. Methods To develop the models and set standards for the necessary personnel and facilities for the initial management plan, we held workshops, debates, and conference meetings with various experts. Results After partitioning the plan into two parts (the operational autonomy and the functional comprehensiveness), three models were developed: the ‘independent regional cardiac surgery center’ model, the ‘satellite cardiac surgery center within hospitals’ model, and the ‘extended cardiac surgery department within hospitals’ model. Proposals on personnel and facility management for each of the models were also presented. A regional cardiac surgery center model that could be applied to each treatment area was proposed, which was developed based on the anticipated demand for cardiac surgery. The independent model or the satellite model was proposed for Chungcheong, Jeolla, North Gyeongsang, and South Gyeongsang area, where more than 500 cardiac surgeries are performed annually. The extended model was proposed as most effective for the Gangwon and Jeju area, where more than 200 cardiac surgeries are performed annually. Conclusion The operation of regional cardiac surgery centers with high caliber professionals and quality resources such as optimal equipment and facility size, should enhance regional healthcare accessibility and the quality of cardiac surgery in South Korea. PMID:28035295

Has the Performance of Regional-Scale Photochemical Modelling Systems Changed over the Past Decade?

EPA Science Inventory

This study analyzed summertime ozone concentrations that have been simulated by various regional-scale photochemical modelling systems over the Eastern U.S. as part of more than ten independent studies. Results indicate that there has been a reduction of root mean square errors ...

Final Report: Closeout of the Award NO. DE-FG02-98ER62618 (M.S. Fox-Rabinovitz, P.I.)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fox-Rabinovitz, M. S.

The final report describes the study aimed at exploring the variable-resolution stretched-grid (SG) approach to decadal regional climate modeling using advanced numerical techniques. The obtained results have shown that variable-resolution SG-GCMs using stretched grids with fine resolution over the area(s) of interest, is a viable established approach to regional climate modeling. The developed SG-GCMs have been extensively used for regional climate experimentation. The SG-GCM simulations are aimed at studying the U.S. regional climate variability with an emphasis on studying anomalous summer climate events, the U.S. droughts and floods.

Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data

USGS Publications Warehouse

Yuan, Shuai; Zhou, Jiayu; Tan, Pang-Ning; Fergus, Emi; Wagner, Tyler; Sorrano, Patricia

2017-01-01

Predictive modeling of nested geospatial data is a challenging problem as the models must take into account potential interactions among variables defined at different spatial scales. These cross-scale interactions, as they are commonly known, are particularly important to understand relationships among ecological properties at macroscales. In this paper, we present a novel, multi-level multi-task learning framework for modeling nested geospatial data in the lake ecology domain. Specifically, we consider region-specific models to predict lake water quality from multi-scaled factors. Our framework enables distinct models to be developed for each region using both its local and regional information. The framework also allows information to be shared among the region-specific models through their common set of latent factors. Such information sharing helps to create more robust models especially for regions with limited or no training data. In addition, the framework can automatically determine cross-scale interactions between the regional variables and the local variables that are nested within them. Our experimental results show that the proposed framework outperforms all the baseline methods in at least 64% of the regions for 3 out of 4 lake water quality datasets evaluated in this study. Furthermore, the latent factors can be clustered to obtain a new set of regions that is more aligned with the response variables than the original regions that were defined a priori from the ecology domain.

Assessment of the performance of CORDEX-SA experiments in simulating seasonal mean temperature over the Himalayan region for the present climate: Part I

NASA Astrophysics Data System (ADS)

Nengker, T.; Choudhary, A.; Dimri, A. P.

2018-04-01

The ability of an ensemble of five regional climate models (hereafter RCMs) under Coordinated Regional Climate Downscaling Experiments-South Asia (hereafter, CORDEX-SA) in simulating the key features of present day near surface mean air temperature (Tmean) climatology (1970-2005) over the Himalayan region is studied. The purpose of this paper is to understand the consistency in the performance of models across the ensemble, space and seasons. For this a number of statistical measures like trend, correlation, variance, probability distribution function etc. are applied to evaluate the performance of models against observation and simultaneously the underlying uncertainties between them for four different seasons. The most evident finding from the study is the presence of a large cold bias (-6 to -8 °C) which is systematically seen across all the models and across space and time over the Himalayan region. However, these RCMs with its fine resolution perform extremely well in capturing the spatial distribution of the temperature features as indicated by a consistently high spatial correlation (greater than 0.9) with the observation in all seasons. In spite of underestimation in simulated temperature and general intensification of cold bias with increasing elevation the models show a greater rate of warming than the observation throughout entire altitudinal stretch of study region. During winter, the simulated rate of warming gets even higher at high altitudes. Moreover, a seasonal response of model performance and its spatial variability to elevation is found.

Diffusion impact on atmospheric moisture transport

NASA Astrophysics Data System (ADS)

Moseley, C.; Haerter, J.; Göttel, H.; Hagemann, S.; Jacob, D.

2009-04-01

To ensure numerical stability, many global and regional climate models employ numerical diffusion to dampen short wavelength modes. Terrain following sigma diffusion is known to cause unphysical effects near the surface in orographically structured regions. They can be reduced by applying z-diffusion on geopotential height levels. We investigate the effect of the diffusion scheme on atmospheric moisture transport and precipitation formation at different resolutions in the European region. With respect to a better understanding of diffusion in current and future grid-space global models, current day regional models may serve as the appropriate tool for studies of the impact of diffusion schemes: Results can easily be constrained to a small test region and checked against reliable observations, which often are unavailable on a global scale. Special attention is drawn to the Alps - a region of strong topographic gradients and good observational coverage. Our study is further motivated by the appearance of the "summer drying problem" in South Eastern Europe. This too warm and too dry simulation of climate is common to many regional climate models and also to some global climate models, and remains a permanent unsolved problem in the community. We perform a systematic comparison of the two diffusion-schemes with respect to the hydrological cycle. In particular, we investigate how local meteorological quantities - such as the atmospheric moisture in the region east of the Alps - depend on the spatial model resolution. Higher model resolution would lead to a more accurate representation of the topography and entail larger gradients in the Alps. This could lead to consecutively stronger transport of moisture along the slopes in the case of sigma-diffusion with subsequent orographic precipitation, whereas the effect could be qualitatively different in the case of z-diffusion. For our study, we analyse a sequence of simulations of the regional climate model REMO employing the different diffusion methods over Europe. For these simulations, REMO was forced at the lateral boundaries with ERA40 reanalysis data for a five year period. For our higher resolution simulations we employ the double nesting technique.

Evaluating land cover influences on model uncertainties—A case study of cropland carbon dynamics in the Mid-Continent Intensive Campaign region

USGS Publications Warehouse

Li, Zhengpeng; Liu, Shuguang; Zhang, Xuesong; West, Tristram O.; Ogle, Stephen M.; Zhou, Naijun

2016-01-01

Quantifying spatial and temporal patterns of carbon sources and sinks and their uncertainties across agriculture-dominated areas remains challenging for understanding regional carbon cycles. Characteristics of local land cover inputs could impact the regional carbon estimates but the effect has not been fully evaluated in the past. Within the North American Carbon Program Mid-Continent Intensive (MCI) Campaign, three models were developed to estimate carbon fluxes on croplands: an inventory-based model, the Environmental Policy Integrated Climate (EPIC) model, and the General Ensemble biogeochemical Modeling System (GEMS) model. They all provided estimates of three major carbon fluxes on cropland: net primary production (NPP), net ecosystem production (NEP), and soil organic carbon (SOC) change. Using data mining and spatial statistics, we studied the spatial distribution of the carbon fluxes uncertainties and the relationships between the uncertainties and the land cover characteristics. Results indicated that uncertainties for all three carbon fluxes were not randomly distributed, but instead formed multiple clusters within the MCI region. We investigated the impacts of three land cover characteristics on the fluxes uncertainties: cropland percentage, cropland richness and cropland diversity. The results indicated that cropland percentage significantly influenced the uncertainties of NPP and NEP, but not on the uncertainties of SOC change. Greater uncertainties of NPP and NEP were found in counties with small cropland percentage than the counties with large cropland percentage. Cropland species richness and diversity also showed negative correlations with the model uncertainties. Our study demonstrated that the land cover characteristics contributed to the uncertainties of regional carbon fluxes estimates. The approaches we used in this study can be applied to other ecosystem models to identify the areas with high uncertainties and where models can be improved to reduce overall uncertainties for regional carbon flux estimates.

Regional primitive equation modeling and analysis of the polymode data set

NASA Astrophysics Data System (ADS)

Spall, Michael A.

A regional, hybrid coordinate, primitive equation (PE) model is applied to a 60-day period of the POLYMODE data set. The initialization techniques and open boundary conditions introduced by Spall and Robinson are shown to produce stable, realistic, and reasonably accurate hindcasts for the 2-month data set. Comparisons with quasi-geostrophic (QG) modeling studies indicate that the PE model reproduced the jet formation that dominates the region more accurately than did the QG model. When the PE model used boundary conditions that were partially adjusted by the QG model, the resulting fields were very similar to the QG fields, indicating a rapid degradation of small-scale features near the boundaries in the QG calculation. A local term-by-term primitive equation energy and vorticity analysis package is also introduced. The full vorticity, horizontal divergence, kinetic energy, and available gravitational energy equations are solved diagnostically from the output of the regional PE model. Through the analysis of a time series of horizontal maps, the dominant processes in the flow are illustrated. The individual terms are also integrated over the region of jet formation to highlight the net balances as a function of time. The formation of the deep thermocline jet is shown to be due to horizontal advection through the boundary, baroclinic conversion in the deep thermocline and vertical pressure work, which exports the deep energy to the upper thermocline levels. It is concluded here that the PE model reproduces the observed jet formation better than the QG model because of the increased horizontal advection and stronger vertical pressure work. Although the PE model is shown to be superior to the QG model in this application, it is believed that both PE and QG models can play an important role in the regional study of mid-ocean mesoscale eddies.

NOAA Atmospheric Sciences Modeling Division support to the US Environmental Protection Agency

NASA Astrophysics Data System (ADS)

Poole-Kober, Evelyn M.; Viebrock, Herbert J.

1991-07-01

During FY-1990, the Atmospheric Sciences Modeling Division provided meteorological research and operational support to the U.S. Environmental Protection Agency. Basic meteorological operational support consisted of applying dispersion models and conducting dispersion studies and model evaluations. The primary research effort was the development and evaluation of air quality simulation models using numerical and physical techniques supported by field studies. Modeling emphasis was on the dispersion of photochemical oxidants and particulate matter on urban and regional scales, dispersion in complex terrain, and the transport, transformation, and deposition of acidic materials. Highlights included expansion of the Regional Acid Deposition Model/Engineering Model family to consist of the Tagged Species Engineering Model, the Non-Depleting Model, and the Sulfate Tracking Model; completion of the Acid-MODES field study; completion of the RADM2.1 evaluation; completion of the atmospheric processes section of the National Acid Precipitation Assessment Program 1990 Integrated Assessment; conduct of the first field study to examine the transport and entrainment processes of convective clouds; development of a Regional Oxidant Model-Urban Airshed Model interface program; conduct of an international sodar intercomparison experiment; incorporation of building wake dispersion in numerical models; conduct of wind-tunnel simulations of stack-tip downwash; and initiation of the publication of SCRAM NEWS.

Charecterisation and Modelling Urbanisation Pattern in Sillicon Valley of India

NASA Astrophysics Data System (ADS)

Aithal, B. H.

2015-12-01

Urbanisation and Urban sprawl has led to environmental problems and large losses of arable land in India. In this study, we characterise pattern of urban growth and model urban sprawl by means of a combination of remote sensing, geographical information system, spatial metrics and CA based modelling. This analysis uses time-series data to explore and derive the potential political-socio-economic- land based driving forces behind urbanisation and urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions and development. The study area applied is Greater Bangalore, for the period from 1973 to 2015. Further water bodies depletion, vegetation depletion, tree cover were also analysed to obtain specific region based results effecting global climate and regional balance. Agents were integrated successfully into modelling aspects to understand and foresee the landscape pattern change in urban morphology. The results reveal built-up paved surfaces has expanded towards the outskirts and have expanded into the buffer regions around the city. Population growth, economic, industrial developments in the city core and transportation development are still the main causes of urban sprawl in the region. Agent based model are considered to be to the traditional models. Agent Based modelling approach as seen in this paper clearly shown its effectiveness in capturing the micro dynamics and influence in its neighbourhood mapping. Greenhouse gas emission inventory has shown important aspects such as domestic sector to be one of the major impact categories in the region. Further tree cover reduced drastically and is evident from the statistics and determines that if city is in verge of creating a chaos in terms of human health and desertification. Study concludes that integration of remote sensing, GIS, and agent based modelling offers an excellent opportunity to explore the spatio-temporal variation and visulaisation of sprawling metropolitan region. This study give a complete overview of urbanisation and effects being caused due to urban sprawl in the region and help planners and city managers in understanding the future pockets and scenarios of urban growth.

Development of simplified ecosystem models for applications in Earth system studies: The Century experience

NASA Technical Reports Server (NTRS)

Parton, William J.; Ojima, Dennis S.; Schimel, David S.; Kittel, Timothy G. F.

1992-01-01

During the past decade, a growing need to conduct regional assessments of long-term trends of ecosystem behavior and the technology to meet this need have converged. The Century model is the product of research efforts initially intended to develop a general model of plant-soil ecosystem dynamics for the North American central grasslands. This model is now being used to simulate plant production, nutrient cycling, and soil organic matter dynamics for grassland, crop, forest, and shrub ecosystems in various regions of the world, including temperate and tropical ecosystems. This paper will focus on the philosophical approach used to develop the structure of Century. The steps included were model simplification, parameterization, and testing. In addition, the importance of acquiring regional data bases for model testing and the present regional application of Century in the Great Plains, which focus on regional ecosystem dynamics and the effect of altering environmental conditions, are discussed.

Modeling of Tracer Transport Delays for Improved Quantification of Regional Pulmonary 18F-FDG Kinetics, Vascular Transit Times, and Perfusion

PubMed Central

Wellman, Tyler J.; Winkler, Tilo; Vidal Melo, Marcos F.

2015-01-01

18F-FDG-PET is increasingly used to assess pulmonary inflammatory cell activity. However, current models of pulmonary 18F-FDG kinetics do not account for delays in 18F-FDG transport between the plasma sampling site and the lungs. We developed a three-compartment model of 18F-FDG kinetics that includes a delay between the right heart and the local capillary blood pool, and used this model to estimate regional pulmonary perfusion. We acquired dynamic 18F-FDG scans in 12 mechanically ventilated sheep divided into control and lung injury groups (n=6 each). The model was fit to tracer kinetics in three isogravitational regions-of-interest to estimate regional lung transport delays and regional perfusion. 13NN bolus infusion scans were acquired during a period of apnea to measure regional perfusion using an established reference method. The delayed input function model improved description of 18F-FDG kinetics (lower Akaike Information Criterion) in 98% of studied regions. Local transport delays ranged from 2.0–13.6s, averaging 6.4±2.9s, and were highest in non-dependent regions. Estimates of regional perfusion derived from model parameters were highly correlated with perfusion measurements based on 13NN-PET (R2=0.92, p<0.001). By incorporating local vascular transports delays, this model of pulmonary 18F-FDG kinetics allows for simultaneous assessment of regional lung perfusion, transit times, and inflammation. PMID:25940652

Applying an integrated model to the evaluation of travel demand management policies in the Sacramento Region : year two

DOT National Transportation Integrated Search

2001-09-01

In this study, the authors apply an integrated land use and transportation model, the Sacramento MEPLAN model, to evaluate transit investment alternatives combines with supportive land use policies and pricing policies in the Sacramento region. The c...

The AQMEII Two-Continent Regional Air Quality Model Evaluation Study: Fueling Ideas with Unprecedented Data

EPA Science Inventory

Although strong collaborations in the air pollution field have existed among the North American (NA) and European (EU) countries over the past five decades, regional-scale air quality model developments and model performance evaluations have been carried out independently unlike ...

Spatial econometric analysis of factors influencing regional energy efficiency in China.

PubMed

Song, Malin; Chen, Yu; An, Qingxian

2018-05-01

Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.

Energy balance in the solar transition region. II - Effects of pressure and energy input on hydrostatic models

NASA Technical Reports Server (NTRS)

Fontenla, J. M.; Avrett, E. H.; Loeser, R.

1991-01-01

The radiation of energy by hydrogen lines and continua in hydrostatic energy-balance models of the transition region between the solar chromosphere and corona is studied using models which assume that mechanical or magnetic energy is dissipated in the hot corona and is then transported toward the chromosphere down the steep temperature gradient of the transition region. These models explain the average quiet sun and also the entire range of variability of the Ly-alpha lines. The relations between the downward energy flux, the pressure of the transition region, and the different hydrogen emission are described.

3D MHD Models of Active Region Loops

NASA Technical Reports Server (NTRS)

Ofman, Leon

2004-01-01

Present imaging and spectroscopic observations of active region loops allow to determine many physical parameters of the coronal loops, such as the density, temperature, velocity of flows in loops, and the magnetic field. However, due to projection effects many of these parameters remain ambiguous. Three dimensional imaging in EUV by the STEREO spacecraft will help to resolve the projection ambiguities, and the observations could be used to setup 3D MHD models of active region loops to study the dynamics and stability of active regions. Here the results of 3D MHD models of active region loops are presented, and the progress towards more realistic 3D MHD models of active regions. In particular the effects of impulsive events on the excitation of active region loop oscillations, and the generation, propagations and reflection of EIT waves are shown. It is shown how 3D MHD models together with 3D EUV observations can be used as a diagnostic tool for active region loop physical parameters, and to advance the science of the sources of solar coronal activity.

A Regional Climate Model Evaluation System based on contemporary Satellite and other Observations for Assessing Regional Climate Model Fidelity

NASA Astrophysics Data System (ADS)

Waliser, D. E.; Kim, J.; Mattman, C.; Goodale, C.; Hart, A.; Zimdars, P.; Lean, P.

2011-12-01

Evaluation of climate models against observations is an essential part of assessing the impact of climate variations and change on regionally important sectors and improving climate models. Regional climate models (RCMs) are of a particular concern. RCMs provide fine-scale climate needed by the assessment community via downscaling global climate model projections such as those contributing to the Coupled Model Intercomparison Project (CMIP) that form one aspect of the quantitative basis of the IPCC Assessment Reports. The lack of reliable fine-resolution observational data and formal tools and metrics has represented a challenge in evaluating RCMs. Recent satellite observations are particularly useful as they provide a wealth of information and constraints on many different processes within the climate system. Due to their large volume and the difficulties associated with accessing and using contemporary observations, however, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL and UCLA have developed the Regional Climate Model Evaluation System (RCMES) to help make satellite observations, in conjunction with in-situ and reanalysis datasets, more readily accessible to the regional modeling community. The system includes a central database (Regional Climate Model Evaluation Database: RCMED) to store multiple datasets in a common format and codes for calculating and plotting statistical metrics to assess model performance (Regional Climate Model Evaluation Tool: RCMET). This allows the time taken to compare model data with satellite observations to be reduced from weeks to days. RCMES is a component of the recent ExArch project, an international effort for facilitating the archive and access of massive amounts data for users using cloud-based infrastructure, in this case as applied to the study of climate and climate change. This presentation will describe RCMES and demonstrate its utility using examples from RCMs applied to the southwest US as well as to Africa based on output from the CORDEX activity. Application of RCMES to the evaluation of multi-RCM hindcast for CORDEX-Africa will be presented in a companion paper in A41.

Evaluation of the CORDEX-Africa multi-RCM hindcast: systematic model errors

NASA Astrophysics Data System (ADS)

Kim, J.; Waliser, Duane E.; Mattmann, Chris A.; Goodale, Cameron E.; Hart, Andrew F.; Zimdars, Paul A.; Crichton, Daniel J.; Jones, Colin; Nikulin, Grigory; Hewitson, Bruce; Jack, Chris; Lennard, Christopher; Favre, Alice

2014-03-01

Monthly-mean precipitation, mean (TAVG), maximum (TMAX) and minimum (TMIN) surface air temperatures, and cloudiness from the CORDEX-Africa regional climate model (RCM) hindcast experiment are evaluated for model skill and systematic biases. All RCMs simulate basic climatological features of these variables reasonably, but systematic biases also occur across these models. All RCMs show higher fidelity in simulating precipitation for the west part of Africa than for the east part, and for the tropics than for northern Sahara. Interannual variation in the wet season rainfall is better simulated for the western Sahel than for the Ethiopian Highlands. RCM skill is higher for TAVG and TMAX than for TMIN, and regionally, for the subtropics than for the tropics. RCM skill in simulating cloudiness is generally lower than for precipitation or temperatures. For all variables, multi-model ensemble (ENS) generally outperforms individual models included in ENS. An overarching conclusion in this study is that some model biases vary systematically for regions, variables, and metrics, posing difficulties in defining a single representative index to measure model fidelity, especially for constructing ENS. This is an important concern in climate change impact assessment studies because most assessment models are run for specific regions/sectors with forcing data derived from model outputs. Thus, model evaluation and ENS construction must be performed separately for regions, variables, and metrics as required by specific analysis and/or assessments. Evaluations using multiple reference datasets reveal that cross-examination, quality control, and uncertainty estimates of reference data are crucial in model evaluations.

Effect of attractive interactions on the water-like anomalies of a core-softened model potential.

PubMed

Pant, Shashank; Gera, Tarun; Choudhury, Niharendu

2013-12-28

It is now well established that water-like anomalies can be reproduced by a spherically symmetric potential with two length scales, popularly known as core-softened potential. In the present study we aim to investigate the effect of attractive interactions among the particles in a model fluid interacting with core-softened potential on the existence and location of various water-like anomalies in the temperature-pressure plane. We employ extensive molecular dynamic simulations to study anomalous nature of various order parameters and properties under isothermal compression. Order map analyses have also been done for all the potentials. We observe that all the systems with varying depth of attractive wells show structural, dynamic, and thermodynamic anomalies. As many of the previous studies involving model water and a class of core softened potentials have concluded that the structural anomaly region encloses the diffusion anomaly region, which in turn, encloses the density anomaly region, the same pattern has also been observed in the present study for the systems with less depth of attractive well. For the systems with deeper attractive well, we observe that the diffusion anomaly region shifts toward higher densities and is not always enclosed by the structural anomaly region. Also, density anomaly region is not completely enclosed by diffusion anomaly region in this case.

A kinetic study of solar wind electrons in the transition region from collision dominated to collisionless flow

NASA Technical Reports Server (NTRS)

Lie-Svendsen, O.; Leer, E.

1995-01-01

We have studied the evolution of the velocity distribution function of a test population of electrons in the solar corona and inner solar wind region, using a recently developed kinetic model. The model solves the time dependent, linear transport equation, with a Fokker-Planck collision operator to describe Coulomb collisions between the 'test population' and a thermal background of charged particles, using a finite differencing scheme. The model provides information on how non-Maxwellian features develop in the distribution function in the transition region from collision dominated to collisionless flow. By taking moments of the distribution the evolution of higher order moments, such as the heat flow, can be studied.

A semi-Lagrangian advection scheme for radioactive tracers in a regional spectral model

NASA Astrophysics Data System (ADS)

Chang, E.-C.; Yoshimura, K.

2015-06-01

In this study, the non-iteration dimensional-split semi-Lagrangian (NDSL) advection scheme is applied to the National Centers for Environmental Prediction (NCEP) regional spectral model (RSM) to alleviate the Gibbs phenomenon. The Gibbs phenomenon is a problem wherein negative values of positive-definite quantities (e.g., moisture and tracers) are generated by the spectral space transformation in a spectral model system. To solve this problem, the spectral prognostic specific humidity and radioactive tracer advection scheme is replaced by the NDSL advection scheme, which considers advection of tracers in a grid system without spectral space transformations. A regional version of the NDSL is developed in this study and is applied to the RSM. Idealized experiments show that the regional version of the NDSL is successful. The model runs for an actual case study suggest that the NDSL can successfully advect radioactive tracers (iodine-131 and cesium-137) without noise from the Gibbs phenomenon. The NDSL can also remove negative specific humidity values produced in spectral calculations without losing detailed features.

The Modelled Raindrop Size Distribution of Skudai, Peninsular Malaysia, Using Exponential and Lognormal Distributions

PubMed Central

Yakubu, Mahadi Lawan; Yusop, Zulkifli; Yusof, Fadhilah

2014-01-01

This paper presents the modelled raindrop size parameters in Skudai region of the Johor Bahru, western Malaysia. Presently, there is no model to forecast the characteristics of DSD in Malaysia, and this has an underpinning implication on wet weather pollution predictions. The climate of Skudai exhibits local variability in regional scale. This study established five different parametric expressions describing the rain rate of Skudai; these models are idiosyncratic to the climate of the region. Sophisticated equipment that converts sound to a relevant raindrop diameter is often too expensive and its cost sometimes overrides its attractiveness. In this study, a physical low-cost method was used to record the DSD of the study area. The Kaplan-Meier method was used to test the aptness of the data to exponential and lognormal distributions, which were subsequently used to formulate the parameterisation of the distributions. This research abrogates the concept of exclusive occurrence of convective storm in tropical regions and presented a new insight into their concurrence appearance. PMID:25126597

Indian monsoon dominates runoff of southern Himalayas—taking Langtang region as an example

NASA Astrophysics Data System (ADS)

Yao, R.; Shi, J.; He, Y.; Hu, G.

2016-12-01

Abstract: Inland Glacier and Indian monsoon are the major source of water supply for human being in the Himalayas. It is vital to study the characteristics of runoff with glacier melting and Indian monsoon precipitation and the relationship between climate change and these processes overall. In this study, we have focused on the Langtang region in the southern slope of the Himalayas. We have used TRMM data to study the precipitation and MODIS data to study the temperature in the Himalayas and a distributed conceptual model has been applied to runoff modeling. The runoff from modeling based on precipitation and temperature can be validated with the in-situ observation in the Langtang region. The results show a decreasing trend of the runoff in the Langtang region which is similar to the decreasing trend of the TRMM precipitation data. It seems that precipitation is mainly controlling the runoff in the Langtang region and that the summer Indian monsoon rather than glacier melting is dominating the runoff in the Langtang region since the summer precipitation in the Southern slope of the Himalayas is mainly from the Indian summer monsoon.

NATIONAL AND REGIONAL AIR AND DEPOSITION MODELING OF STATIONARY AND MOBILE SOURCE EMISSIONS OF DIOXINS USING THE RELMAP MODELING SYSTEM

EPA Science Inventory

The purpose of this study is to estimate the atmospheric transport, fate and deposition flux of air releases of CDDs and CDFs from known sources within the continental United States using the Regional Lagrangian Model of Air Pollution (RELMAP). RELMAP is a Lagrangian air model th...

Evaluation of the multi-model CORDEX-Africa hindcast using RCMES

NASA Astrophysics Data System (ADS)

Kim, J.; Waliser, D. E.; Lean, P.; Mattmann, C. A.; Goodale, C. E.; Hart, A.; Zimdars, P.; Hewitson, B.; Jones, C.

2011-12-01

Recent global climate change studies have concluded with a high confidence level that the observed increasing trend in the global-mean surface air temperatures since mid-20th century is triggered by the emission of anthropogenic greenhouse gases (GHGs). The increase in the global-mean temperature due to anthropogenic emissions is nearly monotonic and may alter the climatological norms resulting in a new climate normal. In the presence of anthropogenic climate change, assessing regional impacts of the altered climate state and developing the plans for mitigating any adverse impacts are an important concern. Assessing future climate state and its impact remains a difficult task largely because of the uncertainties in future emissions and model errors. Uncertainties in climate projections propagates into impact assessment models and result in uncertainties in the impact assessments. In order to facilitate the evaluation of model data, a fundamental step for assessing model errors, the JPL Regional Climate Model Evaluation System (RCMES: Lean et al. 2010; Hart et al. 2011) has been developed through a joint effort of the investigators from UCLA and JPL. RCMES is also a regional climate component of a larger worldwide ExArch project. We will present the evaluation of the surface temperatures and precipitation from multiple RCMs participating in the African component of the Coordinated Regional Climate Downscaling Experiment (CORDEX) that has organized a suite of regional climate projection experiments in which multiple RCMs and GCMs are incorporated. As a part of the project, CORDEX organized a 20-year regional climate hindcast study in order to quantify and understand the uncertainties originating from model errors. Investigators from JPL, UCLA, and the CORDEX-Africa team collaborate to analyze the RCM hindcast data using RCMES. The analysis is focused on measuring the closeness between individual regional climate model outputs as well as their ensembles and observed data. The model evaluation is quantified in terms of widely used metrics. Details on the conceptual outline and architecture of RCMES is presented in two companion papers "The Regional climate model Evaluation System (RCMES) based on contemporary satellite and other observations for assessing regional climate model fidelity" and "A Reusable Framework for Regional Climate Model Evaluation" in GC07 and IN30, respectively.

Signal to noise quantification of regional climate projections

NASA Astrophysics Data System (ADS)

Li, S.; Rupp, D. E.; Mote, P.

2016-12-01

One of the biggest challenges in interpreting climate model outputs for impacts studies and adaptation planning is understanding the sources of disagreement among models (which is often used imperfectly as a stand-in for system uncertainty). Internal variability is a primary source of uncertainty in climate projections, especially for precipitation, for which models disagree about even the sign of changes in large areas like the continental US. Taking advantage of a large initial-condition ensemble of regional climate simulations, this study quantifies the magnitude of changes forced by increasing greenhouse gas concentrations relative to internal variability. Results come from a large initial-condition ensemble of regional climate model simulations generated by weather@home, a citizen science computing platform, where the western United States climate was simulated for the recent past (1985-2014) and future (2030-2059) using a 25-km horizontal resolution regional climate model (HadRM3P) nested in global atmospheric model (HadAM3P). We quantify grid point level signal-to-noise not just in temperature and precipitation responses, but also the energy and moisture flux terms that are related to temperature and precipitation responses, to provide important insights regarding uncertainty in climate change projections at local and regional scales. These results will aid modelers in determining appropriate ensemble sizes for different climate variables and help users of climate model output with interpreting climate model projections.

ILS Localizer Performance Study : Part I. Dallas/Fort Worth Regional Airport and Model Validation - Syracuse Hancock Airport

DOT National Transportation Integrated Search

1972-07-01

The TSC electromagnetic scattering model has been used to predict the course deviation indications (CDI) at the planned Dallas Fort Worth Regional Airport. The results show that the CDI due to scattering from the modeled airport structures are within...

Industrial Sector Energy Efficiency Modeling (ISEEM) Framework Documentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karali, Nihan; Xu, Tengfang; Sathaye, Jayant

2012-12-12

The goal of this study is to develop a new bottom-up industry sector energy-modeling framework with an agenda of addressing least cost regional and global carbon reduction strategies, improving the capabilities and limitations of the existing models that allows trading across regions and countries as an alternative.

A southern Africa harmonic spline core field model derived from CHAMP satellite data

NASA Astrophysics Data System (ADS)

Nahayo, E.; Kotzé, P. B.; McCreadie, H.

2015-02-01

The monitoring of the Earth's magnetic field time variation requires a continuous recording of geomagnetic data with a good spatial coverage over the area of study. In southern Africa, ground recording stations are limited and the use of satellite data is needed for the studies where high spatial resolution data is required. We show the fast time variation of the geomagnetic field in the southern Africa region by deriving an harmonic spline model from CHAMP satellite measurements recorded between 2001 and 2010. The derived core field model, the Southern Africa Regional Model (SARM), is compared with the global model GRIMM-2 and the ground based data recorded at Hermanus magnetic observatory (HER) in South Africa and Tsumeb magnetic observatory (TSU) in Namibia where the focus is mainly on the long term variation of the geomagnetic field. The results of this study suggest that the regional model derived from the satellite data alone can be used to study the small scale features of the time variation of the geomagnetic field where ground data is not available. In addition, these results also support the earlier findings of the occurrence of a 2007 magnetic jerk and rapid secular variation fluctuations of 2003 and 2004 in the region.

The Challenge of Simulating the Regional Climate over Florida

NASA Astrophysics Data System (ADS)

Misra, V.; Mishra, A. K.

2015-12-01

In this study we show that the unique geography of the peninsular Florida with close proximity to strong mesoscale surface ocean currents among other factors warrants the use of relatively high resolution climate models to project Florida's hydroclimate. In the absence of such high resolution climate models we highlight the deficiencies of two relatively coarse spatial resolution CMIP5 models with respect to the warm western boundary current of the Gulf Stream. As a consequence it affects the coastal SST and the land-ocean contrast, affecting the rainy summer seasonal precipitation accumulation over peninsular Florida. We also show this through two sensitivity studies conducted with a regional coupled ocean atmosphere model with different bathymetries that dislocate and modulate the strength of the Gulf Stream that locally affects the SST in the two simulations. These studies show that a stronger and more easterly displaced Gulf Stream produces warmer coastal SST's along the Atlantic coast of Florida that enhances the precipitation over peninsular Florida relative to the other regional climate model simulation. However the regional model simulations indicate that variability of wet season rainfall variability in peninsular Florida becomes less dependent on the land-ocean contrast with a stronger Gulf Stream current.

Research on investment decisions model of trans-regional transmission network based on the theory of NPV

NASA Astrophysics Data System (ADS)

Zai, Wenjiao; Wang, Bo; Liu, Jichun; Shi, Haobo; Zeng, Pingliang

2018-02-01

The investment decision model of trans-regional transmission network in the context of Global Energy Internet was studied in this paper. The key factors affecting the trans-regional transmission network investment income: the income tax rate, the loan interest rate, the expected return on investment of the investment subject, the per capita GDP and so on were considered in the transmission network investment income model. First, according to the principle of system dynamics, the causality diagram of key factors was constructed. Then, the dynamic model of transmission investment decision was established. A case study of the power transmission network between China and Mongolia, through the simulation of the system dynamic model, the influence of the above key factors on the investment returns was analyzed, and the feasibility and effectiveness of the model was proved.

Climate change projections for Greek viticulture as simulated by a regional climate model

NASA Astrophysics Data System (ADS)

Lazoglou, Georgia; Anagnostopoulou, Christina; Koundouras, Stefanos

2017-07-01

Viticulture represents an important economic activity for Greek agriculture. Winegrapes are cultivated in many areas covering the whole Greek territory, due to the favorable soil and climatic conditions. Given the dependence of viticulture on climate, the vitivinicultural sector is expected to be affected by possible climatic changes. The present study is set out to investigate the impacts of climatic change in Greek viticulture, using nine bioclimatic indices for the period 1981-2100. For this purpose, reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and data from the regional climatic model Regional Climate Model Version 3 (RegCM3) are used. It was found that the examined regional climate model estimates satisfactorily these bioclimatic indices. The results of the study show that the increasing trend of temperature and drought will affect all wine-producing regions in Greece. In vineyards in mountainous regions, the impact is positive, while in islands and coastal regions, it is negative. Overall, it should be highlighted that for the first time that Greece is classified into common climatic characteristic categories, according to the international Geoviticulture Multicriteria Climatic Classification System (MCC system). According to the proposed classification, Greek viticulture regions are estimated to have similar climatic characteristics with the warmer wine-producing regions of the world up to the end of twenty-first century. Wine growers and winemakers should take the findings of the study under consideration in order to take measures for Greek wine sector adaptation and the continuation of high-quality wine production.

Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids.

PubMed

Bonnafous, Fanny; Fievet, Ghislain; Blanchet, Nicolas; Boniface, Marie-Claude; Carrère, Sébastien; Gouzy, Jérôme; Legrand, Ludovic; Marage, Gwenola; Bret-Mestries, Emmanuelle; Munos, Stéphane; Pouilly, Nicolas; Vincourt, Patrick; Langlade, Nicolas; Mangin, Brigitte

2018-02-01

This study compares five models of GWAS, to show the added value of non-additive modeling of allelic effects to identify genomic regions controlling flowering time of sunflower hybrids. Genome-wide association studies are a powerful and widely used tool to decipher the genetic control of complex traits. One of the main challenges for hybrid crops, such as maize or sunflower, is to model the hybrid vigor in the linear mixed models, considering the relatedness between individuals. Here, we compared two additive and three non-additive association models for their ability to identify genomic regions associated with flowering time in sunflower hybrids. A panel of 452 sunflower hybrids, corresponding to incomplete crossing between 36 male lines and 36 female lines, was phenotyped in five environments and genotyped for 2,204,423 SNPs. Intra-locus effects were estimated in multi-locus models to detect genomic regions associated with flowering time using the different models. Thirteen quantitative trait loci were identified in total, two with both model categories and one with only non-additive models. A quantitative trait loci on LG09, detected by both the additive and non-additive models, is located near a GAI homolog and is presented in detail. Overall, this study shows the added value of non-additive modeling of allelic effects for identifying genomic regions that control traits of interest and that could participate in the heterosis observed in hybrids.

The added value of dynamical downscaling in a climate change scenario simulation:A case study for European Alps and East Asia

NASA Astrophysics Data System (ADS)

Im, Eun-Soon; Coppola, Erika; Giorgi, Filippo

2010-05-01

Since anthropogenic climate change is a rather important factor for the future human life all over the planet and its effects are not globally uniform, climate information at regional or local scales become more and more important for an accurate assessment of the potential impact of climate change on societies and ecosystems. High resolution information with suitably fine-scale for resolving complex geographical features could be a critical factor for successful linkage between climate models and impact assessment studies. However, scale mismatch between them still remains major problem. One method for overcoming the resolution limitations of global climate models and for adding regional details to coarse-grid global projections is to use dynamical downscaling by means of a regional climate model. In this study, the ECHAM5/MPI-OM (1.875 degree) A1B scenario simulation has been dynamically downscaled by using two different approaches within the framework of RegCM3 modeling system. First, a mosaic-type parameterization of subgrid-scale topography and land use (Sub-BATS) is applied over the European Alpine region. The Sub-BATS system is composed of 15 km coarse-grid cell and 3 km sub-grid cell. Second, we developed the RegCM3 one-way double-nested system, with the mother domain encompassing the eastern regions of Asia at 60 km grid spacing and the nested domain covering the Korean Peninsula at 20 km grid spacing. By comparing the regional climate model output and the driving global model ECHAM5/MPI-OM output, it is possible to estimate the added value of physically-based dynamical downscaling when for example impact studies at hydrological scale are performed.

SERA Scenarios of Early Market Fuel Cell Electric Vehicle Introductions: Modeling Framework, Regional Markets, and Station Clustering; NREL (National Renewable Energy Laboratory)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Melaina, M.

This presentation provides an overview of the Scenario Evaluation and Regionalization Analysis (SERA) model, describes the methodology for developing scenarios for hydrogen infrastructure development, outlines an example "Hydrogen Success" scenario, and discusses detailed scenario metrics for a particular case study region, the Northeast Corridor.

Representative Agricultural Pathways and Climate Impact Assessment for Pacific Northwest Agricultural Systems

NASA Astrophysics Data System (ADS)

MU, J.; Antle, J. M.; Zhang, H.; Capalbo, S. M.; Eigenbrode, S.; Kruger, C.; Stockle, C.; Wolfhorst, J. D.

2013-12-01

Representative Agricultural Pathways (RAPs) are projections of plausible future biophysical and socio-economic conditions used to carry out climate impact assessments for agriculture. The development of RAPs iss motivated by the fact that the various global and regional models used for agricultural climate change impact assessment have been implemented with individualized scenarios using various data and model structures, often without transparent documentation or public availability. These practices have hampered attempts at model inter-comparison, improvement, and synthesis of model results across studies. This paper aims to (1) present RAPs developed for the principal wheat-producing region of the Pacific Northwest, and to (2) combine these RAPs with downscaled climate data, crop model simulations and economic model simulations to assess climate change impacts on winter wheat production and farm income. This research was carried out as part of a project funded by the USDA known as the Regional Approaches to Climate Change in the Pacific Northwest (REACCH). The REACCH study region encompasses the major winter wheat production area in Pacific Northwest and preliminary research shows that farmers producing winter wheat could benefit from future climate change. However, the future world is uncertain in many dimensions, including commodity and input prices, production technology, and policies, as well as increased probability of disturbances (pests and diseases) associated with a changing climate. Many of these factors cannot be modeled, so they are represented in the regional RAPS. The regional RAPS are linked to global agricultural and shared social-economic pathways, and used along with climate change projections to simulate future outcomes for the wheat-based farms in the REACCH region.

Three-dimensional hydrogeologic framework model for use with a steady-state numerical ground-water flow model of the Death Valley regional flow system, Nevada and California

USGS Publications Warehouse

Belcher, Wayne R.; Faunt, Claudia C.; D'Agnese, Frank A.

2002-01-01

The U.S. Geological Survey, in cooperation with the Department of Energy and other Federal, State, and local agencies, is evaluating the hydrogeologic characteristics of the Death Valley regional ground-water flow system. The ground-water flow system covers an area of about 100,000 square kilometers from latitude 35? to 38?15' North to longitude 115? to 118? West, with the flow system proper comprising about 45,000 square kilometers. The Death Valley regional ground-water flow system is one of the larger flow systems within the Southwestern United States and includes in its boundaries the Nevada Test Site, Yucca Mountain, and much of Death Valley. Part of this study includes the construction of a three-dimensional hydrogeologic framework model to serve as the foundation for the development of a steady-state regional ground-water flow model. The digital framework model provides a computer-based description of the geometry and composition of the hydrogeologic units that control regional flow. The framework model of the region was constructed by merging two previous framework models constructed for the Yucca Mountain Project and the Environmental Restoration Program Underground Test Area studies at the Nevada Test Site. The hydrologic characteristics of the region result from a currently arid climate and complex geology. Interbasinal regional ground-water flow occurs through a thick carbonate-rock sequence of Paleozoic age, a locally thick volcanic-rock sequence of Tertiary age, and basin-fill alluvium of Tertiary and Quaternary age. Throughout the system, deep and shallow ground-water flow may be controlled by extensive and pervasive regional and local faults and fractures. The framework model was constructed using data from several sources to define the geometry of the regional hydrogeologic units. These data sources include (1) a 1:250,000-scale hydrogeologic-map compilation of the region; (2) regional-scale geologic cross sections; (3) borehole information, and (4) gridded surfaces from a previous three-dimensional geologic model. In addition, digital elevation model data were used in conjunction with these data to define ground-surface altitudes. These data, properly oriented in three dimensions by using geographic information systems, were combined and gridded to produce the upper surfaces of the hydrogeologic units used in the flow model. The final geometry of the framework model is constructed as a volumetric model by incorporating the intersections of these gridded surfaces and by applying fault truncation rules to structural features from the geologic map and cross sections. The cells defining the geometry of the hydrogeologic framework model can be assigned several attributes such as lithology, hydrogeologic unit, thickness, and top and bottom altitudes.

Evaluating lateral boundary conditions in MATCH using retrieved observations from satellites

NASA Astrophysics Data System (ADS)

Andersson, Emma; Kahnert, Michael; Simpson, David; Devasthale, Abhay

2015-04-01

The role of hemispheric transport has gained large attention in regional chemical transport models due to its impact on both climate, air quality and visibility. The hemispheric transport in regional models are represented by the lateral boundary conditions (LBCs), where the inflow boundary specifies the domain beyond the model region and the outflow region will impact the stability of the advective transport solution. This study focuses on evaluating and implement LBCs from global chemical transport models for two important atmospheric tracers: carbon monoxide (CO) and ozone (O3). LBCs are derived from the hemispheric European Monitoring and Evaluation Programme (EMEP) model and the Model for Ozone and Related chemical Tracers (MOZART-4) over the time periods 2006-2012 and 2011-2012 respectively. Evaluation is done with observational data retrieved from the satellite sensors Measurements Of the Pollution In The Troposphere (MOPITT) and the Ozone Monitoring Instrument (OMI). The implementation of the LBCs is done in the regional chemical transport model Multiple scale atmospheric transport and chemistry (MATCH), developed by the Swedish Meteorological and Hydrological Institute (SMHI). The MATCH model is mostly used in simulations of the air quality over Europe on both on regional and local scales. In this study the model the domain is set over Europe. The LBC evaluation is done for the tropospheric column by smoothing the LBCs using satellite averaging kernels and a priori information. By retrieving the average profile for each month and lateral boundary, possible biases and also what global model that might be better suited for the LBCs in MATCH. The implementation will show how these biases proliferate through the MATCH model, and it will possibly be compared to satellite retrieved data from the sensor Atmospheric InfraRed Sounder (AIRS) inboard the satellite Aqua.

Inter-sectoral comparison of model uncertainty of climate change impacts in Africa

NASA Astrophysics Data System (ADS)

van Griensven, Ann; Vetter, Tobias; Piontek, Franzisca; Gosling, Simon N.; Kamali, Bahareh; Reinhardt, Julia; Dinkneh, Aklilu; Yang, Hong; Alemayehu, Tadesse

2016-04-01

We present the model results and their uncertainties of an inter-sectoral impact model inter-comparison initiative (ISI-MIP) for climate change impacts in Africa. The study includes results on hydrological, crop and health aspects. The impact models used ensemble inputs consisting of 20 time series of daily rainfall and temperature data obtained from 5 Global Circulation Models (GCMs) and 4 Representative concentration pathway (RCP). In this study, we analysed model uncertainty for the Regional Hydrological Models, Global Hydrological Models, Malaria models and Crop models. For the regional hydrological models, we used 2 African test cases: the Blue Nile in Eastern Africa and the Niger in Western Africa. For both basins, the main sources of uncertainty are originating from the GCM and RCPs, while the uncertainty of the regional hydrological models is relatively low. The hydrological model uncertainty becomes more important when predicting changes on low flows compared to mean or high flows. For the other sectors, the impact models have the largest share of uncertainty compared to GCM and RCP, especially for Malaria and crop modelling. The overall conclusion of the ISI-MIP is that it is strongly advised to use ensemble modeling approach for climate change impact studies throughout the whole modelling chain.

Evaluation of climatic changes in South-Asia

NASA Astrophysics Data System (ADS)

Kjellstrom, Erik; Rana, Arun; Grigory, Nikulin; Renate, Wilcke; Hansson, Ulf; Kolax, Michael

2016-04-01

Literature has sufficient evidences of climate change impact all over the world and its impact on various sectors. In light of new advancements made in climate modeling, availability of several climate downscaling approaches, the more robust bias correction methods with varying complexities and strengths, in the present study we performed a systematic evaluation of climate change impact over South-Asia region. We have used different Regional Climate Models (RCMs) (from CORDEX domain), (Global Climate Models GCMs) and gridded observations for the study area to evaluate the models in historical/control period (1980-2010) and changes in future period (2010-2099). Firstly, GCMs and RCMs are evaluated against the Gridded observational datasets in the area using precipitation and temperature as indicative variables. Observational dataset are also evaluated against the reliable set of observational dataset, as pointed in literature. Bias, Correlation, and changes (among other statistical measures) are calculated for the entire region and both the variables. Eventually, the region was sub-divided into various smaller domains based on homogenous precipitation zones to evaluate the average changes over time period. Spatial and temporal changes for the region are then finally calculated to evaluate the future changes in the region. Future changes are calculated for 2 Representative Concentration Pathways (RCPs), the middle emission (RCP4.5) and high emission (RCP8.5) and for both climatic variables, precipitation and temperature. Lastly, Evaluation of Extremes is performed based on precipitation and temperature based indices for whole region in future dataset. Results have indicated that the whole study region is under extreme stress in future climate scenarios for both climatic variables i.e. precipitation and temperature. Precipitation variability is dependent on the location in the area leading to droughts and floods in various regions in future. Temperature is hinting towards a constant increase throughout the region regardless of location.

Agriculture Impacts of Regional Nuclear Conflict

NASA Astrophysics Data System (ADS)

Xia, Lili; Robock, Alan; Mills, Michael; Toon, Owen Brian

2013-04-01

One of the major consequences of nuclear war would be climate change due to massive smoke injection into the atmosphere. Smoke from burning cities can be lofted into the stratosphere where it will have an e-folding lifetime more than 5 years. The climate changes include significant cooling, reduction of solar radiation, and reduction of precipitation. Each of these changes can affect agricultural productivity. To investigate the response from a regional nuclear war between India and Pakistan, we used the Decision Support System for Agrotechnology Transfer agricultural simulation model. We first evaluated the model by forcing it with daily weather data and management practices in China and the USA for rice, maize, wheat, and soybeans. Then we perturbed observed weather data using monthly climate anomalies for a 10-year period due to a simulated 5 Tg soot injection that could result from a regional nuclear war between India and Pakistan, using a total of 100 15 kt atomic bombs, much less than 1% of the current global nuclear arsenal. We computed anomalies using the NASA Goddard Institute for Space Studies ModelE and NCAR's Whole Atmosphere Community Climate Model (WACCM). We perturbed each year of the observations with anomalies from each year of the 10-year nuclear war simulations. We found that different regions respond differently to a regional nuclear war; southern regions show slight increases of crop yields while in northern regions crop yields drop significantly. Sensitivity tests show that temperature changes due to nuclear war are more important than precipitation and solar radiation changes in affecting crop yields in the regions we studied. In total, crop production in China and the USA would decrease 15-50% averaged over the 10 years using both models' output. Simulations forced by ModelE output show smaller impacts than simulations forced by WACCM output at the end of the 10 year period because of the different temperature responses in the two models.

An Experimental and Numerical Comparison of the Rupture Locations of an Abdominal Aortic Aneurysm

PubMed Central

Doyle, Barry J.; Corbett, Timothy J.; Callanan, Anthony; Walsh, Michael T.; Vorp, David A.; McGloughlin, Timothy M.

2009-01-01

Purpose: To identify the rupture locations of idealized physical models of abdominal aortic aneurysm (AAA) using an in-vitro setup and to compare the findings to those predicted numerically. Methods: Five idealized AAAs were manufactured using Sylgard 184 silicone rubber, which had been mechanically characterized from tensile tests, tear tests, and finite element analysis. The models were then inflated to the point of rupture and recorded using a high-speed camera. Numerical modeling attempted to confirm these rupture locations. Regional variations in wall thickness of the silicone models was also quantified and applied to numerical models. Results: Four of the 5 models tested ruptured at inflection points in the proximal and distal regions of the aneurysm sac and not at regions of maximum diameter. These findings agree with high stress regions computed numerically. Wall stress appears to be independent of wall thickness, with high stress occurring at regions of inflection regardless of wall thickness variations. Conclusion: According to these experimental and numerical findings, AAAs experience higher stresses at regions of inflection compared to regions of maximum diameter. Ruptures of the idealized silicone models occurred predominantly at the inflection points, as numerically predicted. Regions of inflection can be easily identified from basic 3-dimensional reconstruction; as ruptures appear to occur at inflection points, these findings may provide a useful insight into the clinical significance of inflection regions. This approach will be applied to patient-specific models in a future study. PMID:19642790

High-resolution, regional-scale crop yield simulations for the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and maximum temperature), beyond which the yields were negatively affected. These results are now being used for further regional-scale yield analysis as the aforementioned framework is adaptable to multiple geographic regions and crop types.

Agricultural disturbance response models for invertebrate and algal metrics from streams at two spatial scales within the U.S.

USGS Publications Warehouse

Waite, Ian R.

2014-01-01

As part of the USGS study of nutrient enrichment of streams in agricultural regions throughout the United States, about 30 sites within each of eight study areas were selected to capture a gradient of nutrient conditions. The objective was to develop watershed disturbance predictive models for macroinvertebrate and algal metrics at national and three regional landscape scales to obtain a better understanding of important explanatory variables. Explanatory variables in models were generated from landscape data, habitat, and chemistry. Instream nutrient concentration and variables assessing the amount of disturbance to the riparian zone (e.g., percent row crops or percent agriculture) were selected as most important explanatory variable in almost all boosted regression tree models regardless of landscape scale or assemblage. Frequently, TN and TP concentration and riparian agricultural land use variables showed a threshold type response at relatively low values to biotic metrics modeled. Some measure of habitat condition was also commonly selected in the final invertebrate models, though the variable(s) varied across regions. Results suggest national models tended to account for more general landscape/climate differences, while regional models incorporated both broad landscape scale and more specific local-scale variables.

Modeling of Tracer Transport Delays for Improved Quantification of Regional Pulmonary ¹⁸F-FDG Kinetics, Vascular Transit Times, and Perfusion.

PubMed

Wellman, Tyler J; Winkler, Tilo; Vidal Melo, Marcos F

2015-11-01

¹⁸F-FDG-PET is increasingly used to assess pulmonary inflammatory cell activity. However, current models of pulmonary ¹⁸F-FDG kinetics do not account for delays in ¹⁸F-FDG transport between the plasma sampling site and the lungs. We developed a three-compartment model of ¹⁸F-FDG kinetics that includes a delay between the right heart and the local capillary blood pool, and used this model to estimate regional pulmonary perfusion. We acquired dynamic ¹⁸F-FDG scans in 12 mechanically ventilated sheep divided into control and lung injury groups (n = 6 each). The model was fit to tracer kinetics in three isogravitational regions-of-interest to estimate regional lung transport delays and regional perfusion. ¹³NN bolus infusion scans were acquired during a period of apnea to measure regional perfusion using an established reference method. The delayed input function model improved description of ¹⁸F-FDG kinetics (lower Akaike Information Criterion) in 98% of studied regions. Local transport delays ranged from 2.0 to 13.6 s, averaging 6.4 ± 2.9 s, and were highest in non-dependent regions. Estimates of regional perfusion derived from model parameters were highly correlated with perfusion measurements based on ¹³NN-PET (R² = 0.92, p < 0.001). By incorporating local vascular transports delays, this model of pulmonary ¹⁸F-FDG kinetics allows for simultaneous assessment of regional lung perfusion, transit times, and inflammation.

Sensitivity of Sahelian Precipitation to Desert Dust under ENSO variability: a regional modeling study

NASA Astrophysics Data System (ADS)

Jordan, A.; Zaitchik, B. F.; Gnanadesikan, A.

2016-12-01

Mineral dust is estimated to comprise over half the total global aerosol burden, with a majority coming from the Sahara and Sahel region. Bounded by the Sahara Desert to the north and the Sahelian Savannah to the south, the Sahel experiences high interannual rainfall variability and a short rainy season during the boreal summer months. Observation-based data for the past three decades indicates a reduced dust emission trend, together with an increase in greening and surface roughness within the Sahel. Climate models used to study regional precipitation changes due to Saharan dust yield varied results, both in sign convention and magnitude. Inconsistency of model estimates drives future climate projections for the region that are highly varied and uncertain. We use the NASA-Unified Weather Research and Forecasting (NU-WRF) model to quantify the interaction and feedback between desert dust aerosol and Sahelian precipitation. Using nested domains at fine spatial resolution we resolve changes to mesoscale atmospheric circulation patterns due to dust, for representative phases of El Niño-Southern Oscillation (ENSO). The NU-WRF regional earth system model offers both advanced land surface data and resolvable detail of the mechanisms of the impact of Saharan dust. Results are compared to our previous work assessed over the Western Sahel using the Geophysical Fluid Dynamics Laboratory (GFDL) CM2Mc global climate model, and to other previous regional climate model studies. This prompts further research to help explain the dust-precipitation relationship and recent North African dust emission trends. This presentation will offer a quantitative analysis of differences in radiation budget, energy and moisture fluxes, and atmospheric dynamics due to desert dust aerosol over the Sahel.

What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Di Vittorio, Alan V.; Kyle, Page; Collins, William D.

Understanding the potential impacts of climate change is complicated by mismatched spatial representations between gridded Earth System Models (ESMs) and Integrated Assessment Models (IAMs), whose regions are typically larger and defined by geopolitical and biophysical criteria. In this study we address uncertainty stemming from the construction of land use regions in an IAM, the Global Change Assessment Model (GCAM), whose regions are currently based on historical climatic conditions (1961-1990). We re-define GCAM’s regions according to projected climatic conditions (2070-2099), and investigate how this changes model outcomes for land use, agriculture, and forestry. By 2100, we find potentially large differences inmore » projected global and regional area of biomass energy crops, fodder crops, harvested forest, and intensive pasture. These land area differences correspond with changes in agricultural commodity prices and production. These results have broader implications for understanding policy scenarios and potential impacts, and for evaluating and comparing IAM and ESM simulations.« less

Bayesian generalized least squares regression with application to log Pearson type 3 regional skew estimation

NASA Astrophysics Data System (ADS)

Reis, D. S.; Stedinger, J. R.; Martins, E. S.

2005-10-01

This paper develops a Bayesian approach to analysis of a generalized least squares (GLS) regression model for regional analyses of hydrologic data. The new approach allows computation of the posterior distributions of the parameters and the model error variance using a quasi-analytic approach. Two regional skew estimation studies illustrate the value of the Bayesian GLS approach for regional statistical analysis of a shape parameter and demonstrate that regional skew models can be relatively precise with effective record lengths in excess of 60 years. With Bayesian GLS the marginal posterior distribution of the model error variance and the corresponding mean and variance of the parameters can be computed directly, thereby providing a simple but important extension of the regional GLS regression procedures popularized by Tasker and Stedinger (1989), which is sensitive to the likely values of the model error variance when it is small relative to the sampling error in the at-site estimator.

Integrating Geo-Spatial Data for Regional Landslide Susceptibility Modeling in Consideration of Run-Out Signature

NASA Astrophysics Data System (ADS)

Lai, J.-S.; Tsai, F.; Chiang, S.-H.

2016-06-01

This study implements a data mining-based algorithm, the random forests classifier, with geo-spatial data to construct a regional and rainfall-induced landslide susceptibility model. The developed model also takes account of landslide regions (source, non-occurrence and run-out signatures) from the original landslide inventory in order to increase the reliability of the susceptibility modelling. A total of ten causative factors were collected and used in this study, including aspect, curvature, elevation, slope, faults, geology, NDVI (Normalized Difference Vegetation Index), rivers, roads and soil data. Consequently, this study transforms the landslide inventory and vector-based causative factors into the pixel-based format in order to overlay with other raster data for constructing the random forests based model. This study also uses original and edited topographic data in the analysis to understand their impacts to the susceptibility modeling. Experimental results demonstrate that after identifying the run-out signatures, the overall accuracy and Kappa coefficient have been reached to be become more than 85 % and 0.8, respectively. In addition, correcting unreasonable topographic feature of the digital terrain model also produces more reliable modelling results.

Eliciting climate experts' knowledge to address model uncertainties in regional climate projections: a case study of Guanacaste, Northwest Costa Rica

NASA Astrophysics Data System (ADS)

Grossmann, I.; Steyn, D. G.

2014-12-01

Global general circulation models typically cannot provide the detailed and accurate regional climate information required by stakeholders for climate adaptation efforts, given their limited capacity to resolve the regional topography and changes in local sea surface temperature, wind and circulation patterns. The study region in Northwest Costa Rica has a tropical wet-dry climate with a double-peak wet season. During the dry season the central Costa Rican mountains prevent tropical Atlantic moisture from reaching the region. Most of the annual precipitation is received following the northward migration of the ITCZ in May that allows the region to benefit from moist southwesterly flow from the tropical Pacific. The wet season begins with a short period of "early rains" and is interrupted by the mid-summer drought associated with the intensification and westward expansion of the North Atlantic subtropical high in late June. Model projections for the 21st century indicate a lengthening and intensification of the mid-summer drought and a weakening of the early rains on which current crop cultivation practices rely. We developed an expert elicitation to systematically address uncertainties in the available model projections of changes in the seasonal precipitation pattern. Our approach extends an elicitation approach developed previously at Carnegie Mellon University. Experts in the climate of the study region or Central American climate were asked to assess the mechanisms driving precipitation during each part of the season, uncertainties regarding these mechanisms, expected changes in each mechanism in a warming climate, and the capacity of current models to reproduce these processes. To avoid overconfidence bias, a step-by-step procedure was followed to estimate changes in the timing and intensity of precipitation during each part of the season. The questions drew upon interviews conducted with the regions stakeholders to assess their climate information needs. This study is part of the FuturAgua project funded by the Belmont Freshwater Security call. The expert opinions on expected changes in the seasonal precipitation pattern are being used to inform regional efforts to build drought resilience and to create and compare alternative water management strategies with the region's stakeholders.

The influence of regional deprivation index on personal happiness using multilevel analysis

PubMed Central

Kim, Kil Hun; Chun, Jin-Ho; Sohn, Hae Sook

2015-01-01

OBJECTIVES: The objective of the present study was to identify the factors that influence the happiness index of community residents, by considering personal and regional aspects, and to use as evidence of efforts for improvement of the happiness index. METHODS: The study was conducted based on information from 16,270 participants who met the data requirement among those who participated in the 2011 South Gyeongsang Community Health Survey. Of the factors that can influence the happiness index, socioeconomic characteristics, health behavior, morbidity, and healthcare use, social contact, and participation in social activities were classified as personal factors; for regional factors, data from the 2010 census were used to extrapolate the regional deprivation indices at the submunicipal-level (eup, myeon, and dong) in South Gyeongsang Province. The happiness index for each characteristic was compared to that for others via t-test and ANOVA, and multilevel analysis was performed, using four models: a basic model for identification of only random effects, model 1 for identification of personal factors, model 2 for identification of regional factors, and model 3 for simultaneous consideration of both personal and regional factors. RESULTS: The mean happiness index was 63.2 points (64.6 points in males and 62.0 points in females), while the mean deprivation index was -1.58 points. In the multilevel analysis, the regional-level variance ratio of the basic model was 10.8%, confirming interregional differences. At the personal level, higher happiness indices were seen in groups consisting of males with high educational level, high income, high degree of physical activity, sufficient sleep, active social contact, and participation in social activities; whereas lower happiness indices were seen in people who frequently skipped breakfast, had unmet healthcare needs, and had accompanying diseases, as well as those with higher deprivation index. CONCLUSIONS: The study confirmed that the happiness index of community residents was influenced by not only personal aspects but also various regional characteristics. To increase the happiness index, interests at both personal and regional levels, as well as community emphasis on creating social rapport and engaging in selective efforts, are needed in vulnerable regions with relatively high deprivation index. PMID:26725223

The influence of regional deprivation index on personal happiness using multilevel analysis.

PubMed

Kim, Kil Hun; Chun, Jin-Ho; Sohn, Hae Sook

2015-01-01

The objective of the present study was to identify the factors that influence the happiness index of community residents, by considering personal and regional aspects, and to use as evidence of efforts for improvement of the happiness index. The study was conducted based on information from 16,270 participants who met the data requirement among those who participated in the 2011 South Gyeongsang Community Health Survey. Of the factors that can influence the happiness index, socioeconomic characteristics, health behavior, morbidity, and healthcare use, social contact, and participation in social activities were classified as personal factors; for regional factors, data from the 2010 census were used to extrapolate the regional deprivation indices at the submunicipal-level (eup, myeon, and dong) in South Gyeongsang Province. The happiness index for each characteristic was compared to that for others via t-test and ANOVA, and multilevel analysis was performed, using four models: a basic model for identification of only random effects, model 1 for identification of personal factors, model 2 for identification of regional factors, and model 3 for simultaneous consideration of both personal and regional factors. The mean happiness index was 63.2 points (64.6 points in males and 62.0 points in females), while the mean deprivation index was -1.58 points. In the multilevel analysis, the regional-level variance ratio of the basic model was 10.8%, confirming interregional differences. At the personal level, higher happiness indices were seen in groups consisting of males with high educational level, high income, high degree of physical activity, sufficient sleep, active social contact, and participation in social activities; whereas lower happiness indices were seen in people who frequently skipped breakfast, had unmet healthcare needs, and had accompanying diseases, as well as those with higher deprivation index. The study confirmed that the happiness index of community residents was influenced by not only personal aspects but also various regional characteristics. To increase the happiness index, interests at both personal and regional levels, as well as community emphasis on creating social rapport and engaging in selective efforts, are needed in vulnerable regions with relatively high deprivation index.

The Development Model Electronic Commerce of Regional Agriculture

NASA Astrophysics Data System (ADS)

Kang, Jun; Cai, Lecai; Li, Hongchan

With the developing of the agricultural information, it is inevitable trend of the development of agricultural electronic commercial affairs. On the basis of existing study on the development application model of e-commerce, combined with the character of the agricultural information, compared with the developing model from the theory and reality, a new development model electronic commerce of regional agriculture base on the government is put up, and such key issues as problems of the security applications, payment mode, sharing mechanisms, and legal protection are analyzed, etc. The among coordination mechanism of the region is discussed on, it is significance for regulating the development of agricultural e-commerce and promoting the regional economical development.

A Practical, Robust Methodology for Acquiring New Observation Data Using Computationally Expensive Groundwater Models

NASA Astrophysics Data System (ADS)

Siade, Adam J.; Hall, Joel; Karelse, Robert N.

2017-11-01

Regional groundwater flow models play an important role in decision making regarding water resources; however, the uncertainty embedded in model parameters and model assumptions can significantly hinder the reliability of model predictions. One way to reduce this uncertainty is to collect new observation data from the field. However, determining where and when to obtain such data is not straightforward. There exist a number of data-worth and experimental design strategies developed for this purpose. However, these studies often ignore issues related to real-world groundwater models such as computational expense, existing observation data, high-parameter dimension, etc. In this study, we propose a methodology, based on existing methods and software, to efficiently conduct such analyses for large-scale, complex regional groundwater flow systems for which there is a wealth of available observation data. The method utilizes the well-established d-optimality criterion, and the minimax criterion for robust sampling strategies. The so-called Null-Space Monte Carlo method is used to reduce the computational burden associated with uncertainty quantification. And, a heuristic methodology, based on the concept of the greedy algorithm, is proposed for developing robust designs with subsets of the posterior parameter samples. The proposed methodology is tested on a synthetic regional groundwater model, and subsequently applied to an existing, complex, regional groundwater system in the Perth region of Western Australia. The results indicate that robust designs can be obtained efficiently, within reasonable computational resources, for making regional decisions regarding groundwater level sampling.

Influence of Boundary Conditions on Simulated U.S. Air Quality

EPA Science Inventory

One of the key inputs to regional-scale photochemical models frequently used in air quality planning and forecasting applications are chemical boundary conditions representing background pollutant concentrations originating outside the regional modeling domain. A number of studie...

Region Spherical Harmonic Magnetic Modeling from Near-Surface and Satellite-Altitude Anomlaies

NASA Technical Reports Server (NTRS)

Kim, Hyung Rae; von Frese, Ralph R. B.; Taylor, Patrick T.

2013-01-01

The compiled near-surface data and satellite crustal magnetic measured data are modeled with a regionally concentrated spherical harmonic presentation technique over Australia and Antarctica. Global crustal magnetic anomaly studies have used a spherical harmonic analysis to represent the Earth's magnetic crustal field. This global approach, however is best applied where the data are uniformly distributed over the entire Earth. Satellite observations generally meet this requirement, but unequally distributed data cannot be easily adapted in global modeling. Even for the satellite observations, due to the errors spread over the globe, data smoothing is inevitable in the global spherical harmonic presentations. In addition, global high-resolution modeling requires a great number of global spherical harmonic coefficients for the regional presentation of crustal magnetic anomalies, whereas a lesser number of localized spherical coefficients will satisfy. We compared methods in both global and regional approaches and for a case where the errors were propagated outside the region of interest. For observations from the upcoming Swarm constellation, the regional modeling will allow the production a lesser number of spherical coefficients that are relevant to the region of interest

EVALUATING THE PERFORMANCE OF REGIONAL-SCALE PHOTOCHEMICAL MODELING SYSTEMS: PART I--METEOROLOGICAL PREDICTIONS. (R825260)

EPA Science Inventory

In this study, the concept of scale analysis is applied to evaluate two state-of-science meteorological models, namely MM5 and RAMS3b, currently being used to drive regional-scale air quality models. To this end, seasonal time series of observations and predictions for temperatur...

Evaluating the capability of regional-scale air quality models to capture the vertical distribution of pollutants

EPA Science Inventory

This study is conducted in the framework of the Air Quality Modelling Evaluation International Initiative (AQMEII) and aims at the operational evaluation of an ensemble of 12 regional-scale chemical transport models used to predict air quality over the North American (NA) and Eur...

PLANNING MODELS FOR URBAN WATER SUPPLY EXPANSION. VOLUME 1. PLANNING FOR THE EXPANSION OF REGIONAL WATER SUPPLY SYSTEMS

EPA Science Inventory

A three-volume report was developed relative to the modelling of investment strategies for regional water supply planning. Volume 1 is the study of capacity expansion over time. Models to aid decision making for the deterministic case are presented, and a planning process under u...

MODELING ASSESSMENT OF TRANSPORT AND DEPOSITION PATTERNS OF MERCURY AIR EMISSIONS FROM THE U.S. AND CANADA

EPA Science Inventory

In December 1997, the U.S. EPA submitted the Mercury Study Report to Congress which included a regional-scale modeling assessment of the transport and deposition of U.S. air emissions of mercury. This modeling was performed with a modified version of the Regional Lagrangian Mode...

Methods for estimating annual exceedance probability discharges for streams in Arkansas, based on data through water year 2013

USGS Publications Warehouse

Wagner, Daniel M.; Krieger, Joshua D.; Veilleux, Andrea G.

2016-08-04

In 2013, the U.S. Geological Survey initiated a study to update regional skew, annual exceedance probability discharges, and regional regression equations used to estimate annual exceedance probability discharges for ungaged locations on streams in the study area with the use of recent geospatial data, new analytical methods, and available annual peak-discharge data through the 2013 water year. An analysis of regional skew using Bayesian weighted least-squares/Bayesian generalized-least squares regression was performed for Arkansas, Louisiana, and parts of Missouri and Oklahoma. The newly developed constant regional skew of -0.17 was used in the computation of annual exceedance probability discharges for 281 streamgages used in the regional regression analysis. Based on analysis of covariance, four flood regions were identified for use in the generation of regional regression models. Thirty-nine basin characteristics were considered as potential explanatory variables, and ordinary least-squares regression techniques were used to determine the optimum combinations of basin characteristics for each of the four regions. Basin characteristics in candidate models were evaluated based on multicollinearity with other basin characteristics (variance inflation factor < 2.5) and statistical significance at the 95-percent confidence level (p ≤ 0.05). Generalized least-squares regression was used to develop the final regression models for each flood region. Average standard errors of prediction of the generalized least-squares models ranged from 32.76 to 59.53 percent, with the largest range in flood region D. Pseudo coefficients of determination of the generalized least-squares models ranged from 90.29 to 97.28 percent, with the largest range also in flood region D. The regional regression equations apply only to locations on streams in Arkansas where annual peak discharges are not substantially affected by regulation, diversion, channelization, backwater, or urbanization. The applicability and accuracy of the regional regression equations depend on the basin characteristics measured for an ungaged location on a stream being within range of those used to develop the equations.

Proposing a Compartmental Model for Leprosy and Parameterizing Using Regional Incidence in Brazil.

PubMed

Smith, Rebecca Lee

2016-08-01

Hansen's disease (HD), or leprosy, is still considered a public health risk in much of Brazil. Understanding the dynamics of the infection at a regional level can aid in identification of targets to improve control. A compartmental continuous-time model for leprosy dynamics was designed based on understanding of the biology of the infection. The transmission coefficients for the model and the rate of detection were fit for each region using Approximate Bayesian Computation applied to paucibacillary and multibacillary incidence data over the period of 2000 to 2010, and model fit was validated on incidence data from 2011 to 2012. Regional variation was noted in detection rate, with cases in the Midwest estimated to be infectious for 10 years prior to detection compared to 5 years for most other regions. Posterior predictions for the model estimated that elimination of leprosy as a public health risk would require, on average, 44-45 years in the three regions with the highest prevalence. The model is easily adaptable to other settings, and can be studied to determine the efficacy of improved case finding on leprosy control.

Analysis of High School German Textbooks through Rasch Measurement Model

ERIC Educational Resources Information Center

Batdi, Veli; Elaldi, Senel

2016-01-01

The purpose of the present study is to analyze German teacher trainers' views on high school German textbooks through the Rasch measurement model. A survey research design was employed and study group consisted of a total of 21 teacher trainers, three from each region and selected randomly from provinces which are located in seven regions and…

An empirical study on the utility of BRDF model parameters and topographic parameters for mapping vegetation in a semi-arid region with MISR imagery

USDA-ARS?s Scientific Manuscript database

Multi-angle remote sensing has been proved useful for mapping vegetation community types in desert regions. Based on Multi-angle Imaging Spectro-Radiometer (MISR) multi-angular images, this study compares roles played by Bidirectional Reflectance Distribution Function (BRDF) model parameters with th...

ADVANCEMENTS IN SOURCE-TO-DOSE ANALYSIS OF POPULATION EXPOSURES TO OZONE

EPA Science Inventory

The current study takes advantage of the observations from regional air quality monitoring networks, the data from the NE-OPS (North East Oxidant and Particulate Study) Project in the Philadelphia region, and regional photochemical air quality model predictions to obtain and co...

Intercomparison and Uncertainty Assessment of Nine Evapotranspiration Estimates Over South America

NASA Astrophysics Data System (ADS)

Sörensson, Anna A.; Ruscica, Romina C.

2018-04-01

This study examines the uncertainties and the representations of anomalies of a set of evapotranspiration products over climatologically distinct regions of South America. The products, coming from land surface models, reanalysis, and remote sensing, are chosen from sources that are readily available to the community of users. The results show that the spatial patterns of maximum uncertainty differ among metrics, with dry regions showing maximum relative uncertainties of annual mean evapotranspiration, while energy-limited regions present maximum uncertainties in the representation of the annual cycle and monsoon regions in the representation of anomalous conditions. Furthermore, it is found that land surface models driven by observed atmospheric fields detect meteorological and agricultural droughts in dry regions unequivocally. The remote sensing products employed do not distinguish all agricultural droughts and this could be attributed to the forcing net radiation. The study also highlights important characteristics of individual data sets and recommends users to include assessments of sensitivity to evapotranspiration data sets in their studies, depending on region and nature of study to be conducted.

Wildfire potential evaluation during a drought event with a regional climate model and NDVI

Treesearch

Y. Liu; J. Stanturf; S. Goodrick

2010-01-01

Regional climate modeling is a technique for simulating high-resolution physical processes in the atmosphere, soil and vegetation. It can be used to evaluate wildfire potential by either providing meteorological conditions for computation of fire indices or predicting soil moisture as a direct measure of fire potential. This study examines these roles using a regional...

Modeling Wildfire Hazard in the Western Hindu Kush-Himalayas

NASA Astrophysics Data System (ADS)

Bylow, D.

2012-12-01

Wildfire regimes are a leading driver of global environmental change affecting a diverse array of global ecosystems. Particulates and aerosols produced by wildfires are a primary source of air pollution making the early detection and monitoring of wildfires crucial. The objectives of this study were to model regional wildfire potential and identify environmental, topological, and sociological factors that contribute to the ignition of wildfire events in the Western Hindu Kush-Himalayas of South Asia. The environmental, topological, and sociological factors were used to model regional wildfire potential through multi-criteria evaluation using a method of weighted linear combination. Moderate Resolution Imaging Spectroradiometer (MODIS) and geographic information systems (GIS) data were integrated to analyze regional wildfires and construct the model. Model validation was performed using a holdout cross validation method. The study produced a significant model of wildfire potential in the Western Hindu Kush-Himalayas.; Western Hindu Kush-Himalayas ; Western Hindu Kush-Himalayas Wildfire Potential

Multi-year downscaling application of two-way coupled WRF v3.4 and CMAQ v5.0.2 over east Asia for regional climate and air quality modeling: model evaluation and aerosol direct effects

NASA Astrophysics Data System (ADS)

Hong, Chaopeng; Zhang, Qiang; Zhang, Yang; Tang, Youhua; Tong, Daniel; He, Kebin

2017-06-01

In this study, a regional coupled climate-chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM) and the regional two-way coupled Weather Research and Forecasting - Community Multi-scale Air Quality (WRF-CMAQ) model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over east Asia for a multi-year climatological application during 2006-2010, driven with CESM downscaling data under Representative Concentration Pathways 4.5 (RCP4.5), along with a short-term air quality application in representative months in 2013 that was driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the two-way coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2 m temperature (T2) in this study (with a mean bias of -0.6 °C) compared with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2. 5 in winter (with a normalized mean bias (NMB) of 6.4 % in 2013) and O3 in summer (with an NMB of 18.2 % in 2013) in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2. 5 concentrations in China, WRF-CMAQ was able to capture the high PM2. 5 concentrations in urban areas. In general, the two-way coupled WRF-CMAQ model performed well for both climatological and air quality applications. The coupled modeling system with direct aerosol feedbacks predicted aerosol optical depth relatively well and significantly reduced the overprediction in downward shortwave radiation at the surface (SWDOWN) over polluted regions in China. The performance of cloud variables was not as good as other meteorological variables, and underpredictions of cloud fraction resulted in overpredictions of SWDOWN and underpredictions of shortwave and longwave cloud forcing. The importance of climate-chemistry interactions was demonstrated via the impacts of aerosol direct effects on climate and air quality. The aerosol effects on climate and air quality in east Asia (e.g., SWDOWN and T2 decreased by 21.8 W m-2 and 0.45 °C, respectively, and most pollutant concentrations increased by 4.8-9.5 % in January over China's major cities) were more significant than in other regions because of higher aerosol loadings that resulted from severe regional pollution, which indicates the need for applying online-coupled models over east Asia for regional climate and air quality modeling and to study the important climate-chemistry interactions. This work established a baseline for WRF-CMAQ simulations for a future period under the RCP4.5 climate scenario, which will be presented in a future paper.

Linear mixed-effects models to describe length-weight relationships for yellow croaker (Larimichthys Polyactis) along the north coast of China.

PubMed

Ma, Qiuyun; Jiao, Yan; Ren, Yiping

2017-01-01

In this study, length-weight relationships and relative condition factors were analyzed for Yellow Croaker (Larimichthys polyactis) along the north coast of China. Data covered six regions from north to south: Yellow River Estuary, Coastal Waters of Northern Shandong, Jiaozhou Bay, Coastal Waters of Qingdao, Haizhou Bay, and South Yellow Sea. In total 3,275 individuals were collected during six years (2008, 2011-2015). One generalized linear model, two simply linear models and nine linear mixed effect models that applied the effects from regions and/or years to coefficient a and/or the exponent b were studied and compared. Among these twelve models, the linear mixed effect model with random effects from both regions and years fit the data best, with lowest Akaike information criterion value and mean absolute error. In this model, the estimated a was 0.0192, with 95% confidence interval 0.0178~0.0308, and the estimated exponent b was 2.917 with 95% confidence interval 2.731~2.945. Estimates for a and b with the random effects in intercept and coefficient from Region and Year, ranged from 0.013 to 0.023 and from 2.835 to 3.017, respectively. Both regions and years had effects on parameters a and b, while the effects from years were shown to be much larger than those from regions. Except for Coastal Waters of Northern Shandong, a decreased from north to south. Condition factors relative to reference years of 1960, 1986, 2005, 2007, 2008~2009 and 2010 revealed that the body shape of Yellow Croaker became thinner in recent years. Furthermore relative condition factors varied among months, years, regions and length. The values of a and relative condition factors decreased, when the environmental pollution became worse, therefore, length-weight relationships could be an indicator for the environment quality. Results from this study provided basic description of current condition of Yellow Croaker along the north coast of China.

The magnetotelluric phase tensor analysis of the Sembalun-Propok area, West Nusa Tenggara, Indonesia

NASA Astrophysics Data System (ADS)

Febriani, F.; Widarto, D. S.; Gaffar, E.; Nasution, A.; Grandis, H.

2017-04-01

The subsurface structure of the Sembalun-Propok area, NTB, Indonesia, has been investigated using magnetotelluric method (MT). To obtain the information of the dimensionality of the regional structure and determine the regional strike of the study area, the phase tensor analysis has been performed in this study. The results show that most of the skew angle values (β) are distributed within ± 5°. It indicates that the regional structure of the study area can be assumed as two dimensional. In addition, to determine the regional strike of the study area, we also calculated the major axes of the phase tensor. The result presents that the regional strike of the study area is about N330°E. According to the results of the phase tensor analysis, we rotated the impedance tensor to N330°E and performed 2-D inversion modeling. The result presents that the substructure model suits with the geological background of the study area.

Assessing Changes in Precipitation and Impacts on Groundwater in Southeastern Brazil using Regional Hydroclimate Reconstruction

NASA Astrophysics Data System (ADS)

Nunes, A.; Fernandes, M.; Silva, G. C., Jr.

2017-12-01

Aquifers can be key players in regional water resources. Precipitation infiltration is the most relevant process in recharging the aquifers. In that regard, understanding precipitation changes and impacts on the hydrological cycle helps in the assessment of groundwater availability from the aquifers. Regional modeling systems can provide precipitation, near-surface air temperature, together with soil moisture at different ground levels from coupled land-surface schemes. More accurate those variables are better the evaluation of the precipitation impact on the groundwater. Downscaling of global reanalysis very often employs regional modeling systems, in order to give more detailed information for impact assessment studies at regional scales. In particular, the regional modeling system, Satellite-enhanced Regional Downscaling for Applied Studies (SRDAS), might improve the accuracy of hydrometeorological variables in regions with spatial and temporal scarcity of in-situ observations. SRDAS combines assimilation of precipitation estimates from gauge-corrected satellite-based products with spectral nudging technique. The SRDAS hourly outputs provide monthly means of atmospheric and land-surface variables, including precipitation, used in the calculations of the hydrological budget terms. Results show the impact of changes in precipitation on groundwater in the aquifer located near the southeastern coastline of Brazil, through the assessment of the water-cycle terms, using a hydrological model during dry and rainy periods found in the 15-year numerical integration of SRDAS.

Nonlinear time series modeling and forecasting the seismic data of the Hindu Kush region

NASA Astrophysics Data System (ADS)

Khan, Muhammad Yousaf; Mittnik, Stefan

2018-01-01

In this study, we extended the application of linear and nonlinear time models in the field of earthquake seismology and examined the out-of-sample forecast accuracy of linear Autoregressive (AR), Autoregressive Conditional Duration (ACD), Self-Exciting Threshold Autoregressive (SETAR), Threshold Autoregressive (TAR), Logistic Smooth Transition Autoregressive (LSTAR), Additive Autoregressive (AAR), and Artificial Neural Network (ANN) models for seismic data of the Hindu Kush region. We also extended the previous studies by using Vector Autoregressive (VAR) and Threshold Vector Autoregressive (TVAR) models and compared their forecasting accuracy with linear AR model. Unlike previous studies that typically consider the threshold model specifications by using internal threshold variable, we specified these models with external transition variables and compared their out-of-sample forecasting performance with the linear benchmark AR model. The modeling results show that time series models used in the present study are capable of capturing the dynamic structure present in the seismic data. The point forecast results indicate that the AR model generally outperforms the nonlinear models. However, in some cases, threshold models with external threshold variables specification produce more accurate forecasts, indicating that specification of threshold time series models is of crucial importance. For raw seismic data, the ACD model does not show an improved out-of-sample forecasting performance over the linear AR model. The results indicate that the AR model is the best forecasting device to model and forecast the raw seismic data of the Hindu Kush region.

Influence investigation of a void region on modeling light propagation in a heterogeneous medium.

PubMed

Yang, Defu; Chen, Xueli; Ren, Shenghan; Qu, Xiaochao; Tian, Jie; Liang, Jimin

2013-01-20

A void region exists in some biological tissues, and previous studies have shown that inaccurate images would be obtained if it were not processed. A hybrid radiosity-diffusion method (HRDM) that couples the radiosity theory and the diffusion equation has been proposed to deal with the void problem and has been well demonstrated in two-dimensional and three-dimensional (3D) simple models. However, the extent of the impact of the void region on the accuracy of modeling light propagation has not been investigated. In this paper, we first implemented and verified the HRDM in 3D models, including both the regular geometries and a digital mouse model, and then investigated the influences of the void region on modeling light propagation in a heterogeneous medium. Our investigation results show that the influence of the region can be neglected when the size of the void is less than a certain range, and other cases must be taken into account.

Potential role of vegetation dynamics on recent extreme droughts over tropical South America

NASA Astrophysics Data System (ADS)

Wang, G.; Erfanian, A.; Fomenko, L.

2017-12-01

Tropical South America is a drought hot spot. In slightly over a decade (2005-2016), the region encountered three extreme droughts (2005, 2010, and 2016). Recurrent extreme droughts not only impact the region's eco-hydrology and socio-economy, but are also globally important as they can transform the planet's largest rainforest, the Amazon, from a carbon sink to a carbon source. Understanding drought drivers and mechanisms underlying extreme droughts in tropical South America can help better project the fate of the Amazon rainforest in a changing climate. In this study we use a regional climate model (RegCM4.3.4) coupled with a comprehensive land-surface model (CLM4.5) to study the present-day hydroclimate of the region, focusing specifically on what might have caused the frequent recurrence of extreme droughts. In the context of observation natural variability of the global oceanic forcing, we tackle the role of land-atmosphere interactions and ran the model with and without dynamic vegetation to study how vegetation dynamics and carbon-nitrogen cycles may have influenced the drought characteristics. Our results demonstrate skillful simulation of the South American climate in the model, and indicate substantial sensitivity of the region's hydroclimatology to vegetation dynamics. This presentation will compare the role of global oceanic forcing versus regional land surface feedback in the recent recurrent droughts, and will characterize the effects of vegetation dynamics in enhancing the drought severity. Preliminary results on future projections of the regional ecosystem and droughts perspective will be also presented.

Genomewide association study for susceptibility genes contributing to familial Parkinson disease

PubMed Central

Pankratz, Nathan; Wilk, Jemma B.; Latourelle, Jeanne C.; DeStefano, Anita L.; Halter, Cheryl; Pugh, Elizabeth W.; Doheny, Kimberly F.; Gusella, James F.; Nichols, William C.

2009-01-01

Five genes have been identified that contribute to Mendelian forms of Parkinson disease (PD); however, mutations have been found in fewer than 5% of patients, suggesting that additional genes contribute to disease risk. Unlike previous studies that focused primarily on sporadic PD, we have performed the first genomewide association study (GWAS) in familial PD. Genotyping was performed with the Illumina HumanCNV370Duo array in 857 familial PD cases and 867 controls. A logistic model was employed to test for association under additive and recessive modes of inheritance after adjusting for gender and age. No result met genomewide significance based on a conservative Bonferroni correction. The strongest association result was with SNPs in the GAK/DGKQ region on chromosome 4 (additive model: p = 3.4 × 10−6; OR = 1.69). Consistent evidence of association was also observed to the chromosomal regions containing SNCA (additive model: p = 5.5 × 10−5; OR = 1.35) and MAPT (recessive model: p = 2.0 × 10−5; OR = 0.56). Both of these genes have been implicated previously in PD susceptibility; however, neither was identified in previous GWAS studies of PD. Meta-analysis was performed using data from a previous case–control GWAS, and yielded improved p values for several regions, including GAK/DGKQ (additive model: p = 2.5 × 10−7) and the MAPT region (recessive model: p = 9.8 × 10−6; additive model: p = 4.8 × 10−5). These data suggest the identification of new susceptibility alleles for PD in the GAK/DGKQ region, and also provide further support for the role of SNCA and MAPT in PD susceptibility. PMID:18985386

Assessing the quality of bottom water temperatures from the Finite-Volume Community Ocean Model (FVCOM) in the Northwest Atlantic Shelf region

NASA Astrophysics Data System (ADS)

Li, Bai; Tanaka, Kisei R.; Chen, Yong; Brady, Damian C.; Thomas, Andrew C.

2017-09-01

The Finite-Volume Community Ocean Model (FVCOM) is an advanced coastal circulation model widely utilized for its ability to simulate spatially and temporally evolving three-dimensional geophysical conditions of complex and dynamic coastal regions. While a body of literature evaluates model skill in surface fields, independent studies validating model skill in bottom fields over large spatial and temporal scales are scarce because these fields cannot be remotely sensed. In this study, an evaluation of FVCOM skill in modeling bottom water temperature was conducted by comparison to hourly in situ observed bottom temperatures recorded by the Environmental Monitors on Lobster Traps (eMOLT), a program that attached thermistors to commercial lobster traps from 2001 to 2013. Over 2 × 106 pairs of FVCOM-eMOLT records were evaluated by a series of statistical measures to quantify accuracy and precision of the modeled data across the Northwest Atlantic Shelf region. The overall comparison between modeled and observed data indicates reliable skill of FVCOM (r2 = 0.72; root mean squared error = 2.28 °C). Seasonally, the average absolute errors show higher model skill in spring, fall and winter than summer. We speculate that this is due to the increased difficulty of modeling high frequency variability in the exact position of the thermocline and frontal zones. The spatial patterns of the residuals suggest that there is improved similarity between modeled and observed data at higher latitudes. We speculate that this is due to increased tidal mixing at higher latitudes in our study area that reduces stratification in winter, allowing improved model accuracy. Modeled bottom water temperatures around Cape Cod, the continental shelf edges, and at one location at the entrance to Penobscot Bay were characterized by relatively high errors. Constraints for future uses of FVCOM bottom water temperature are provided based on the uncertainties in temporal-spatial patterns. This study is novel as it is the first skill assessment of a regional ocean circulation model in bottom fields at high spatial and temporal scales in the Northwest Atlantic Shelf region.

Regional climate and vegetation response to orbital forcing within the mid-Pliocene Warm Period: A study using HadCM3

NASA Astrophysics Data System (ADS)

Prescott, C. L.; Dolan, A. M.; Haywood, A. M.; Hunter, S. J.; Tindall, J. C.

2018-02-01

Regional climate and environmental variability in response to orbital forcing during interglacial events within the mid-Piacenzian (Pliocene) Warm Period (mPWP; 3.264-3.025 Ma) has been rarely studied using climate and vegetation models. Here we use climate and vegetation model simulations to predict changes in regional vegetation patterns in response to orbital forcing for four different interglacial events within the mPWP (Marine Isotope Stages (MIS) G17, K1, KM3 and KM5c). The efficacy of model-predicted changes in regional vegetation is assessed by reference to selected high temporal resolution palaeobotanical studies that are theoretically capable of discerning vegetation patterns for the selected interglacial stages. Annual mean surface air temperatures for the studied interglacials are between 0.4 °C to 0.7 °C higher than a comparable Pliocene experiment using modern orbital parameters. Increased spring/summer and reduced autumn/winter insolation in the Northern Hemisphere during MIS G17, K1 and KM3 enhances seasonality in surface air temperature. The two most robust and notable regional responses to this in vegetation cover occur in North America and continental Eurasia, where forests are replaced by more open-types of vegetation (grasslands and shrubland). In these regions our model results appear to be inconsistent with local palaeobotanical data. The orbitally driven changes in seasonal temperature and precipitation lead to a 30% annual reduction in available deep soil moisture (2.0 m from surface), a critical parameter for forest growth, and subsequent reduction in the geographical coverage of forest-type vegetation; a phenomenon not seen in comparable simulations of Pliocene climate and vegetation run with a modern orbital configuration. Our results demonstrate the importance of examining model performance under a range of realistic orbital forcing scenarios within any defined time interval (e.g. mPWP). Additional orbitally resolved records of regional vegetation are needed to further examine the validity of model-predicted regional climate and vegetation responses in greater detail.

Multi-region statistical shape model for cochlear implantation

NASA Astrophysics Data System (ADS)

Romera, Jordi; Kjer, H. Martin; Piella, Gemma; Ceresa, Mario; González Ballester, Miguel A.

2016-03-01

Statistical shape models are commonly used to analyze the variability between similar anatomical structures and their use is established as a tool for analysis and segmentation of medical images. However, using a global model to capture the variability of complex structures is not enough to achieve the best results. The complexity of a proper global model increases even more when the amount of data available is limited to a small number of datasets. Typically, the anatomical variability between structures is associated to the variability of their physiological regions. In this paper, a complete pipeline is proposed for building a multi-region statistical shape model to study the entire variability from locally identified physiological regions of the inner ear. The proposed model, which is based on an extension of the Point Distribution Model (PDM), is built for a training set of 17 high-resolution images (24.5 μm voxels) of the inner ear. The model is evaluated according to its generalization ability and specificity. The results are compared with the ones of a global model built directly using the standard PDM approach. The evaluation results suggest that better accuracy can be achieved using a regional modeling of the inner ear.

A new conceptual model for quantifying transboundary contribution of atmospheric pollutants in the East Asian Pacific rim region.

PubMed

Lai, I-Chien; Lee, Chon-Lin; Huang, Hu-Ching

2016-03-01

Transboundary transport of air pollution is a serious environmental concern as pollutant affects both human health and the environment. Many numerical approaches have been utilized to quantify the amounts of pollutants transported to receptor regions, based on emission inventories from possible source regions. However, sparse temporal-spatial observational data and uncertainty in emission inventories might make the transboundary transport contribution difficult to estimate. This study presents a conceptual quantitative approach that uses transport pathway classification in combination with curve fitting models to simulate an air pollutant concentration baseline for pollution background concentrations. This approach is used to investigate the transboundary transport contribution of atmospheric pollutants to a metropolitan area in the East Asian Pacific rim region. Trajectory analysis categorized pollution sources for the study area into three regions: East Asia, Southeast Asia, and Taiwan cities. The occurrence frequency and transboundary contribution results suggest the predominant source region is the East Asian continent. This study also presents an application to evaluate heavy pollution cases for health concerns. This new baseline construction model provides a useful tool for the study of the contribution of transboundary pollution delivered to receptors, especially for areas deficient in emission inventories and regulatory monitoring data for harmful air pollutants. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Rural Transformation Model: The facts of rural development in the Surakarta Metropolitan Region

NASA Astrophysics Data System (ADS)

Puspa Sari, D. P.; Asyifa, I.; Derman, I. F.; Jayanti, D. R.; Hanatya, F. Y.

2018-05-01

Not only cities are entering the urban age but suburban villages are also feeling the impact of this global phenomenon. In Indonesia, the uncontrolled rural transformation has had some negative impacts because of the unpreparedness of various aspects such as land conversion, the emergence of the informal sector, and crime. This phenomenon is often referred to as developmental externalities that need to be anticipated in planning and controlling the growth of cities and villages. This inevitable rural transformation also occurs in the Surakarta Metropolitan Region. The previous rural transformation studies in the Surakarta Metropolitan Region are based on economic, spatial to socio-ecological perspectives and are still rarely studied from the perspective of urban studies. This article aims to examine the model of rural transformation in the Surakarta Metropolitan Region based on the Rural-Urban Transformation theory by Lo, Shalih & Douglass (1998), especially in the Simo, Sambi, Ngemplak, and Nogosari Sub-districts in Boyolali District. The qualitative methods consisting of interviews, 150 questionnaires, and field observations in 2017 and literature study were used for the discussion in this article. The rural to urban transformation of the Surakarta Metropolitan Region follows the Southeast Asian Model. This research opens a new discussion on how to create a sustainable city system in the Surakarta Metropolitan Region.

Empirical Study on Total Factor Productive Energy Efficiency in Beijing-Tianjin-Hebei Region-Analysis based on Malmquist Index and Window Model

NASA Astrophysics Data System (ADS)

Xu, Qiang; Ding, Shuai; An, Jingwen

2017-12-01

This paper studies the energy efficiency of Beijing-Tianjin-Hebei region and to finds out the trend of energy efficiency in order to improve the economic development quality of Beijing-Tianjin-Hebei region. Based on Malmquist index and window analysis model, this paper estimates the total factor energy efficiency in Beijing-Tianjin-Hebei region empirically by using panel data in this region from 1991 to 2014, and provides the corresponding political recommendations. The empirical result shows that, the total factor energy efficiency in Beijing-Tianjin-Hebei region increased from 1991 to 2014, mainly relies on advances in energy technology or innovation, and obvious regional differences in energy efficiency to exist. Throughout the window period of 24 years, the regional differences of energy efficiency in Beijing-Tianjin-Hebei region shrank. There has been significant convergent trend in energy efficiency after 2000, mainly depends on the diffusion and spillover of energy technologies.

Investigating Downscaling Methods and Evaluating Climate Models for Use in Estimating Regional Water Resources in Mountainous Regions under Changing Climatic Conditions

NASA Technical Reports Server (NTRS)

Frei, Allan; Nolin, Anne W.; Serreze, Mark C.; Armstrong, Richard L.; McGinnis, David L.; Robinson, David A.

2004-01-01

The purpose of this three-year study is to develop and evaluate techniques to estimate the range of potential hydrological impacts of climate change in mountainous areas. Three main objectives are set out in the proposal. (1) To develop and evaluate transfer functions to link tropospheric circulation to regional snowfall. (2) To evaluate a suite of General Circulation Models (GCMs) for use in estimating synoptic scale circulation and the resultant regional snowfall. And (3) to estimate the range of potential hydrological impacts of changing climate in the two case study areas: the Upper Colorado River basin, and the Catskill Mountains of southeastern New York State. Both regions provide water to large populations.

Shallow groundwater in the Matanuska-Susitna Valley, Alaska—Conceptualization and simulation of flow

USGS Publications Warehouse

Kikuchi, Colin P.

2013-01-01

The Matanuska-Susitna Valley is in the Upper Cook Inlet Basin and is currently undergoing rapid population growth outside of municipal water and sewer service areas. In response to concerns about the effects of increasing water use on future groundwater availability, a study was initiated between the Alaska Department of Natural Resources and the U.S. Geological Survey. The goals of the study were (1) to compile existing data and collect new data to support hydrogeologic conceptualization of the study area, and (2) to develop a groundwater flow model to simulate flow dynamics important at the regional scale. The purpose of the groundwater flow model is to provide a scientific framework for analysis of regional-scale groundwater availability. To address the first study goal, subsurface lithologic data were compiled into a database and were used to construct a regional hydrogeologic framework model describing the extent and thickness of hydrogeologic units in the Matanuska-Susitna Valley. The hydrogeologic framework model synthesizes existing maps of surficial geology and conceptual geochronologies developed in the study area with the distribution of lithologies encountered in hundreds of boreholes. The geologic modeling package Geological Surveying and Investigation in Three Dimensions (GSI3D) was used to construct the hydrogeologic framework model. In addition to characterizing the hydrogeologic framework, major groundwater-budget components were quantified using several different techniques. A land-surface model known as the Deep Percolation Model was used to estimate in-place groundwater recharge across the study area. This model incorporates data on topography, soils, vegetation, and climate. Model-simulated surface runoff was consistent with observed streamflow at U.S. Geological Survey streamgages. Groundwater withdrawals were estimated on the basis of records from major water suppliers during 2004-2010. Fluxes between groundwater and surface water were estimated during field investigations on several small streams. Regional groundwater flow patterns were characterized by synthesizing previous water-table maps with a synoptic water-level measurement conducted during 2009. Time-series water-level data were collected at groundwater and lake monitoring stations over the study period (2009–present). Comparison of historical groundwater-level records with time-series groundwater-level data collected during this study showed similar patterns in groundwater-level fluctuation in response to precipitation. Groundwater-age data collected during previous studies show that water moves quickly through the groundwater system, suggesting that the system responds quickly to changes in climate forcing. Similarly, the groundwater system quickly returns to long-term average conditions following variability due to seasonal or interannual changes in precipitation. These analyses indicate that the groundwater system is in a state of dynamic equilibrium, characterized by water-level fluctuation about a constant average state, with no long-term trends in aquifer-system storage. To address the second study goal, a steady-state groundwater flow model was developed to simulate regional groundwater flow patterns. The groundwater flow model was bounded by physically meaningful hydrologic features, and appropriate internal model boundaries were specified on the basis of conceptualization of the groundwater system resulting in a three-layer model. Calibration data included 173 water‑level measurements and 18 measurements of streamflow gains and losses along small streams. Comparison of simulated and observed heads and flows showed that the model accurately simulates important regional characteristics of the groundwater flow system. This model is therefore appropriate for studying regional-scale groundwater availability. Mismatch between model-simulated and observed hydrologic quantities is likely because of the coarse grid size of the model and seasonal transient effects. Next steps towards model refinement include the development of a transient groundwater flow model that is suitable for analysis of seasonal variability in hydraulic heads and flows. In addition, several important groundwater budget components remain poorly quantified—including groundwater outflow to the Matanuska River, Little Susitna River, and Knik Arm.

Study of Regional Downscaled Climate and Air Quality in the United States

NASA Astrophysics Data System (ADS)

Gao, Y.; Fu, J. S.; Drake, J.; Lamarque, J.; Lam, Y.; Huang, K.

2011-12-01

Due to the increasing anthropogenic greenhouse gas emissions, the global and regional climate patterns have significantly changed. Climate change has exerted strong impact on ecosystem, air quality and human life. The global model Community Earth System Model (CESM v1.0) was used to predict future climate and chemistry under projected emission scenarios. Two new emission scenarios, Representative Community Pathways (RCP) 4.5 and RCP 8.5, were used in this study for climate and chemistry simulations. The projected global mean temperature will increase 1.2 and 1.7 degree Celcius for the RCP 4.5 and RCP 8.5 scenarios in 2050s, respectively. In order to take advantage of local detailed topography, land use data and conduct local climate impact on air quality, we downscaled CESM outputs to 4 km by 4 km Eastern US domain using Weather Research and Forecasting (WRF) Model and Community Multi-scale Air Quality modeling system (CMAQ). The evaluations between regional model outputs and global model outputs, regional model outputs and observational data were conducted to verify the downscaled methodology. Future climate change and air quality impact were also examined on a 4 km by 4 km high resolution scale.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shiddiqi, Hasbi Ash, E-mail: h.a.shiddiqi@students.itb.ac.id, E-mail: h.a.shiddiqi@gmail.com; Widiyantoro, Sri; Nugraha, Andri Dian

We have relocated hypocenters of earthquakes occurring in the Molucca collision zone and surrounding region taken from the BMKG catalog using teleseismic double-difference relocation algorithm (teletomoDD). We used P-wave arrival times of local, regional, and teleseismic events recorded at 304 recording stations. Over 7,000 earthquakes were recorded by the BMKG seismographicnetworkin the study region from April, 2009 toJune, 2014. We used a 3D regional-global nested velocity modelresulting fromprevious global tomographystudy. In this study, the3D seismic velocity model was appliedto theIndonesian region, whilethe1D seismicvelocity model (ak135)wasused for regions outside of Indonesia. Our relocation results show a better improvement in travel-time RMSmore » residuals comparedto those of the BMKG catalog.Ourresultsalso show that relocation shifts were dominated intheeast-west direction, whichmaybeinfluenced by theexistingvelocity anomaly related to the reversed V-shaped slabbeneaththestudy region. Our eventrelocation results refine the geometry of slabs beneath the Halmahera and Sangihe arcs.« less

Regional Permafrost Probability Modelling in the northwestern Cordillera, 59°N - 61°N, Canada

NASA Astrophysics Data System (ADS)

Bonnaventure, P. P.; Lewkowicz, A. G.

2010-12-01

High resolution (30 x 30 m) permafrost probability models were created for eight mountainous areas in the Yukon and northernmost British Columbia. Empirical-statistical modelling based on the Basal Temperature of Snow (BTS) method was used to develop spatial relationships. Model inputs include equivalent elevation (a variable that incorporates non-uniform temperature change with elevation), potential incoming solar radiation and slope. Probability relationships between predicted BTS and permafrost presence were developed for each area using late-summer physical observations in pits, or by using year-round ground temperature measurements. A high-resolution spatial model for the region has now been generated based on seven of the area models. Each was applied to the entire region, and their predictions were then blended based on a distance decay function from the model source area. The regional model is challenging to validate independently because there are few boreholes in the region. However, a comparison of results to a recently established inventory of rock glaciers for the Yukon suggests its validity because predicted permafrost probabilities were 0.8 or greater for almost 90% of these landforms. Furthermore, the regional model results have a similar spatial pattern to those modelled independently in the eighth area, although predicted probabilities using the regional model are generally higher. The regional model predicts that permafrost underlies about half of the non-glaciated terrain in the region, with probabilities increasing regionally from south to north and from east to west. Elevation is significant, but not always linked in a straightforward fashion because of weak or inverted trends in permafrost probability below treeline. Above treeline, however, permafrost probabilities increase and approach 1.0 in very high elevation areas throughout the study region. The regional model shows many similarities to previous Canadian permafrost maps (Heginbottom and Radburn, 1992; Heginbottom et al., 1995) but is several orders of magnitude more detailed. It also exhibits some significant differences, including the presence of an area of valley-floor continuous permafrost around Beaver Creek near the Alaskan border in the west, as well as higher probabilities of permafrost in the central parts of the region near the boundaries of the sporadic and extensive discontinuous zones. In addition, parts of the northernmost portion of the region would be classified as sporadic discontinuous permafrost because of inversions in the terrestrial surface lapse rate which cause permafrost probabilities to decrease with elevation through the forest. These model predictions are expected to of direct use for infrastructure planning and northern development and can serve as a benchmark for future studies of permafrost distribution in the Yukon. References Heginbottom JR, Dubreuil MA and Haker PT. 1995. Canada Permafrost. (1:7,500,000 scale). In The National Atlas of Canada, 5th Edition, sheet MCR 4177. Ottawa: National Resources Canada. Heginbottom, J.A. and Radburn, L.K. 1992. Permafrost and ground ice conditions of northwestern Canada; Geological Survey of Canada, Map 1691A, scale 1:1,000,000. Digitized by S. Smith, Geological Survey of Canada.

A semi-Lagrangian advection scheme for radioactive tracers in the NCEP Regional Spectral Model (RSM)

NASA Astrophysics Data System (ADS)

Chang, E.-C.; Yoshimura, K.

2015-10-01

In this study, the non-iteration dimensional-split semi-Lagrangian (NDSL) advection scheme is applied to the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) to alleviate the Gibbs phenomenon. The Gibbs phenomenon is a problem wherein negative values of positive-definite quantities (e.g., moisture and tracers) are generated by the spectral space transformation in a spectral model system. To solve this problem, the spectral prognostic specific humidity and radioactive tracer advection scheme is replaced by the NDSL advection scheme, which considers advection of tracers in a grid system without spectral space transformations. A regional version of the NDSL is developed in this study and is applied to the RSM. Idealized experiments show that the regional version of the NDSL is successful. The model runs for an actual case study suggest that the NDSL can successfully advect radioactive tracers (iodine-131 and cesium-137) without noise from the Gibbs phenomenon. The NDSL can also remove negative specific humidity values produced in spectral calculations without losing detailed features.

The Impact of Spring Subsurface Soil Temperature Anomaly in the Western U.S. on North American Summer Precipitation: A Case Study Using Regional Climate Model Downscaling

DTIC Science & Technology

2012-06-02

regional climate model downscaling , J. Geophys. Res., 117, D11103, doi:10.1029/2012JD017692. 1. Introduction [2] Modeling studies and data analyses...based on ground and satellite data have demonstrated that the land surface state variables, such as soil moisture, snow, vegetation, and soil temperature... downscaling rather than simply applying reanal- ysis data as LBC for both Eta control and sensitivity experiments as done in many RCM sensitivity studies

Regional impacts of climate change on a temperate mixed forest: species-specific microscopic root water uptake strategies

NASA Astrophysics Data System (ADS)

He, L.; Ivanov, V. Y.; Bisht, G.; Schneider, C.; Kalbacher, T.; Hildebrandt, A.

2013-12-01

The current generation of ecohydrological or land surface models oversimplify fine-scale root water uptake processes and are thus likely to produce errors in estimating regional transpiration flux when soil approaches dry condition. As future climate is likely to result in a drier soil state in many regions around the world, a better understanding and numerical representation of plant root water uptake process is crucial. In this study, a microscopic root water uptake approach is proposed to simulate the three-dimensional radial moisture fluxes from the soil to roots, and water flux transfer processes within the root systems. During dry conditions, this microscopic approach can simulate plant's ability to compensate the suppressed root water uptake in water-stressed regions by increasing uptake density in moister regions. This study incorporated the microscopic root water uptake approach based on 'aRoot' and 'PFLOTRAN' models into a larger-scale ecohydrological model ('tRIBS+VEGGIE'). The ecohydrological model provides boundary conditions for the microscopic module, and the latter feedbacks with actual transpiration rates and profiles of moisture sinks. The study is conducted for a northern temperate mixed forest of Northern Michigan. The study addresses two species (oak and aspen) with different root architectures, the primary and secondary type root systems. The modeling results use historical climate situations, as well as empirical observations suggesting that transpiration was not limited by soil moisture even when the surface soil water content approached the residual value. Climate projection scenarios are used to predict different water stress levels that would be experienced by the studied species.

Feature-oriented regional modeling and simulations in the Gulf of Maine and Georges Bank

NASA Astrophysics Data System (ADS)

Gangopadhyay, Avijit; Robinson, Allan R.; Haley, Patrick J.; Leslie, Wayne G.; Lozano, Carlos J.; Bisagni, James J.; Yu, Zhitao

2003-03-01

The multiscale synoptic circulation system in the Gulf of Maine and Georges Bank (GOMGB) region is presented using a feature-oriented approach. Prevalent synoptic circulation structures, or 'features', are identified from previous observational studies. These features include the buoyancy-driven Maine Coastal Current, the Georges Bank anticyclonic frontal circulation system, the basin-scale cyclonic gyres (Jordan, Georges and Wilkinson), the deep inflow through the Northeast Channel (NEC), the shallow outflow via the Great South Channel (GSC), and the shelf-slope front (SSF). Their synoptic water-mass ( T- S) structures are characterized and parameterized in a generalized formulation to develop temperature-salinity feature models. A synoptic initialization scheme for feature-oriented regional modeling and simulation (FORMS) of the circulation in the coastal-to-deep region of the GOMGB system is then developed. First, the temperature and salinity feature-model profiles are placed on a regional circulation template and then objectively analyzed with appropriate background climatology in the coastal region. Furthermore, these fields are melded with adjacent deep-ocean regional circulation (Gulf Stream Meander and Ring region) along and across the SSF. These initialization fields are then used for dynamical simulations via the primitive equation model. Simulation results are analyzed to calibrate the multiparameter feature-oriented modeling system. Experimental short-term synoptic simulations are presented for multiple resolutions in different regions with and without atmospheric forcing. The presented 'generic and portable' methodology demonstrates the potential of applying similar FORMS in many other regions of the Global Coastal Ocean.

Multiregional input-output model for the evaluation of Spanish water flows.

PubMed

Cazcarro, Ignacio; Duarte, Rosa; Sánchez Chóliz, Julio

2013-01-01

We construct a multiregional input-output model for Spain, in order to evaluate the pressures on the water resources, virtual water flows, and water footprints of the regions, and the water impact of trade relationships within Spain and abroad. The study is framed with those interregional input-output models constructed to study water flows and impacts of regions in China, Australia, Mexico, or the UK. To build our database, we reconcile regional IO tables, national and regional accountancy of Spain, trade and water data. Results show an important imbalance between origin of water resources and final destination, with significant water pressures in the South, Mediterranean, and some central regions. The most populated and dynamic regions of Madrid and Barcelona are important drivers of water consumption in Spain. Main virtual water exporters are the South and Central agrarian regions: Andalusia, Castile-La Mancha, Castile-Leon, Aragon, and Extremadura, while the main virtual water importers are the industrialized regions of Madrid, Basque country, and the Mediterranean coast. The paper shows the different location of direct and indirect consumers of water in Spain and how the economic trade and consumption pattern of certain areas has significant impacts on the availability of water resources in other different and often drier regions.

Dynamic Bayesian network modeling for longitudinal brain morphometry

PubMed Central

Chen, Rong; Resnick, Susan M; Davatzikos, Christos; Herskovits, Edward H

2011-01-01

Identifying interactions among brain regions from structural magnetic-resonance images presents one of the major challenges in computational neuroanatomy. We propose a Bayesian data-mining approach to the detection of longitudinal morphological changes in the human brain. Our method uses a dynamic Bayesian network to represent evolving inter-regional dependencies. The major advantage of dynamic Bayesian network modeling is that it can represent complicated interactions among temporal processes. We validated our approach by analyzing a simulated atrophy study, and found that this approach requires only a small number of samples to detect the ground-truth temporal model. We further applied dynamic Bayesian network modeling to a longitudinal study of normal aging and mild cognitive impairment — the Baltimore Longitudinal Study of Aging. We found that interactions among regional volume-change rates for the mild cognitive impairment group are different from those for the normal-aging group. PMID:21963916

A Simple Forecasting Model Linking Macroeconomic Policy to Industrial Employment Demand.

ERIC Educational Resources Information Center

Malley, James R.; Hady, Thomas F.

A study detailed further a model linking monetary and fiscal policy to industrial employment in metropolitan and nonmetropolitan areas of four United States regions. The model was used to simulate the impacts on area and regional employment of three events in the economy: changing real gross national product (GNP) via monetary policy, holding the…

DESIGN ARTIFACTS IN EULERIAN REGIONAL AIR QUALITY MODELS: EVALUATION OF THE EFFECTS OF LAYER THICKNESS AND VERTICAL PROFILE CORRECTION ON SURFACE OZONE CONCENTRATIONS

EPA Science Inventory

Evaluation studies of the Regional Acid Deposition Model (RADM) results have revealed that there exists high bias of surface SO2 and O3 concentrations by the model, especially during nighttime hours. omparison of the RADM results with surface measurements of hourly ozone concentr...

Investigating NARCCAP Precipitation Extremes via Bivariate Extreme Value Theory (Invited)

NASA Astrophysics Data System (ADS)

Weller, G. B.; Cooley, D. S.; Sain, S. R.; Bukovsky, M. S.; Mearns, L. O.

2013-12-01

We introduce methodology from statistical extreme value theory to examine the ability of reanalysis-drive regional climate models to simulate past daily precipitation extremes. Going beyond a comparison of summary statistics such as 20-year return values, we study whether the most extreme precipitation events produced by climate model simulations exhibit correspondence to the most extreme events seen in observational records. The extent of this correspondence is formulated via the statistical concept of tail dependence. We examine several case studies of extreme precipitation events simulated by the six models of the North American Regional Climate Change Assessment Program (NARCCAP) driven by NCEP reanalysis. It is found that the NARCCAP models generally reproduce daily winter precipitation extremes along the Pacific coast quite well; in contrast, simulation of past daily summer precipitation extremes in a central US region is poor. Some differences in the strength of extremal correspondence are seen in the central region between models which employ spectral nudging and those which do not. We demonstrate how these techniques may be used to draw a link between extreme precipitation events and large-scale atmospheric drivers, as well as to downscale extreme precipitation simulated by a future run of a regional climate model. Specifically, we examine potential future changes in the nature of extreme precipitation along the Pacific coast produced by the pineapple express (PE) phenomenon. A link between extreme precipitation events and a "PE Index" derived from North Pacific sea-surface pressure fields is found. This link is used to study PE-influenced extreme precipitation produced by a future-scenario climate model run.

The DOE water cycle pilot study.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, N. L.; King, A. W.; Miller, M. A.

In 1999, the U.S. Global Change Research Program (USGCRP) formed a Water Cycle Study Group (Hornberger et al. 2001) to organize research efforts in regional hydrologic variability, the extent to which this variability is caused by human activity, and the influence of ecosystems. The USGCRP Water Cycle Study Group was followed by a U.S. Department of Energy (DOE) Water Cycle Research Plan (Department of Energy 2002) that outlined an approach toward improving seasonal-to-interannual hydroclimate predictability and closing a regional water budget. The DOE Water Cycle Research Plan identified key research areas, including a comprehensive long-term observational database to support modelmore » development, and to develop a better understanding of the relationship between the components of local water budgets and large scale processes. In response to this plan, a multilaboratory DOE Water Cycle Pilot Study (WCPS) demonstration project began with a focus on studying the water budget and its variability at multiple spatial scales. Previous studies have highlighted the need for continued efforts to observationally close a local water budget, develop a numerical model closure scheme, and further quantify the scales in which predictive accuracy are optimal. A concerted effort within the National Oceanic and Atmospheric Administration (NOAA)-funded Global Energy and Water Cycle Experiment (GEWEX) Continental-scale International Project (GCIP) put forth a strategy to understand various hydrometeorological processes and phenomena with an aim toward closing the water and energy budgets of regional watersheds (Lawford 1999, 2001). The GCIP focus on such regional budgets includes the measurement of all components and reduction of the error in the budgets to near zero. To approach this goal, quantification of the uncertainties in both measurements and modeling is required. Model uncertainties within regional climate models continue to be evaluated within the Program to Intercompare Regional Climate Simulations (Takle et al. 1999), and model uncertainties within land surface models are being evaluated within the Program to Intercompare Land Surface Schemes (e.g., Henderson-Sellers 1993; Wood et al. 1998; Lohmann et al. 1998). In the context of understanding the water budget at watershed scales, the following two research questions that highlight DOE's unique water isotope analysis and high-performance modeling capabilities were posed as the foci of this pilot study: (1) Can the predictability of the regional water budget be improved using high-resolution model simulations that are constrained and validated with new hydrospheric water measurements? (2) Can water isotopic tracers be used to segregate different pathways through the water cycle and predict a change in regional climate patterns? To address these questions, numerical studies using regional atmospheric-land surface models and multiscale land surface hydrologic models were generated and, to the extent possible, the results were evaluated with observations. While the number of potential processes that may be important in the local water budget is large, several key processes were examined in detail. Most importantly, a concerted effort was made to understand water cycle processes and feedbacks at the land surface-atmosphere interface at spatial scales ranging from 30 m to hundreds of kilometers. A simple expression for the land surface water budget at the watershed scale is expressed as {Delta}S = P + G{sub in} - ET - Q - G{sub out}, where {Delta}S is the change in water storage, P is precipitation, ET is evapotranspiration, Q is streamflow, G{sub in} is groundwater entering the watershed, and G{sub out} is groundwater leaving the watershed, per unit time. The WCPS project identified data gaps and necessary model improvements that will lead to a more accurate representation of the terms in Eq. (1). Table 1 summarizes the components of this water cycle pilot study and the respective participants. The following section provides a description of the surface observation and modeling sites. This is followed by a section on model analyses, and then the summary and concluding remarks.« less

Transport and Chemical Production of Ozone in the East Asian Pacific Rim Region: -Modeling Study Based on Observation-

NASA Astrophysics Data System (ADS)

Akimoto, H.; Li, J.; Wang, Z.; Yamaji, K.; Pochanart, P.; Ohara, T.; Uno, I.; Gao, C.; Wang, X.; Tanimoto, H.; Kurokawa, J.

2007-12-01

Form satellite observational data, east-central China covering the North China Plain (NCP) and Yanzi Delta (YZD) has been identified as the most widely spread source area of air pollutants in the East Asian Pacific region. In order to quantify transport and chemical production of ozone in this region, both of observational and modeling studies in both of source and outflow region are necessary. In the present study, we investigated the budgets of ozone over East Asia by using regional chemical transport models (NAQPMS and CMAQ) based on observations at newly founded three mountain sites (Mt. Tai, Hua and Huang) in east-central China, and several sites from EANET and regional WMO/GAW. The observations show that a striking pattern of two sharp high ozone peaks in May-June and September-October at the three mountain sites. The budget analysis by the model confirms that maximum of net photochemical ozone production reaches 31.8, 15.1 and 11.4 ppb/day at Mt. Tai, Hua and Huang, respectively. The net chemical production dominates the formation of ozone maximum at Mt. Tai and Hua in June, and the importing transport also plays a comparable importance at Mt. Huang. In the outflow region at Oki, Japan, transport of ozone produced by East Asian emissions accounts up to 21 ppb in summer but less than 3 ppb in winter agreeing with the model analysis. The contribution of ozone due to East Asian emission is the largest (53.6%) in July-August, and somewhat smaller in May-June (34.0%) and September-October (30.7%) on the transect between Japan and the Asian continent.

A framework for modeling uncertainty in regional climate change

EPA Science Inventory

In this study, we present a new modeling framework and a large ensemble of climate projections to investigate the uncertainty in regional climate change over the United States associated with four dimensions of uncertainty. The sources of uncertainty considered in this framework ...

Aerosol Source Attributions and Source-Receptor Relationships Across the Northern Hemisphere

NASA Technical Reports Server (NTRS)

Bian, Huisheng; Chin, Mian; Kucsera, Tom; Pan, Xiaohua; Darmenov, Anton; Colarco, Peter; Torres, Omar; Shults, Michael

2014-01-01

Emissions and long-range transport of air pollution pose major concerns on air quality and climate change. To better assess the impact of intercontinental transport of air pollution on regional and global air quality, ecosystems, and near-term climate change, the UN Task Force on Hemispheric Transport of Air Pollution (HTAP) is organizing a phase II activity (HTAP2) that includes global and regional model experiments and data analysis, focusing on ozone and aerosols. This study presents the initial results of HTAP2 global aerosol modeling experiments. We will (a) evaluate the model results with surface and aircraft measurements, (b) examine the relative contributions of regional emission and extra-regional source on surface PM concentrations and column aerosol optical depth (AOD) over several NH pollution and dust source regions and the Arctic, and (c) quantify the source-receptor relationships in the pollution regions that reflect the sensitivity of regional aerosol amount to the regional and extra-regional emission reductions.

Spatial Epidemic Modelling in Social Networks

NASA Astrophysics Data System (ADS)

Simoes, Joana Margarida

2005-06-01

The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.

Benefits of explicit urban parameterization in regional climate modeling to study climate and city interactions

NASA Astrophysics Data System (ADS)

Daniel, M.; Lemonsu, Aude; Déqué, M.; Somot, S.; Alias, A.; Masson, V.

2018-06-01

Most climate models do not explicitly model urban areas and at best describe them as rock covers. Nonetheless, the very high resolutions reached now by the regional climate models may justify and require a more realistic parameterization of surface exchanges between urban canopy and atmosphere. To quantify the potential impact of urbanization on the regional climate, and evaluate the benefits of a detailed urban canopy model compared with a simpler approach, a sensitivity study was carried out over France at a 12-km horizontal resolution with the ALADIN-Climate regional model for 1980-2009 time period. Different descriptions of land use and urban modeling were compared, corresponding to an explicit modeling of cities with the urban canopy model TEB, a conventional and simpler approach representing urban areas as rocks, and a vegetated experiment for which cities are replaced by natural covers. A general evaluation of ALADIN-Climate was first done, that showed an overestimation of the incoming solar radiation but satisfying results in terms of precipitation and near-surface temperatures. The sensitivity analysis then highlighted that urban areas had a significant impact on modeled near-surface temperature. A further analysis on a few large French cities indicated that over the 30 years of simulation they all induced a warming effect both at daytime and nighttime with values up to + 1.5 °C for the city of Paris. The urban model also led to a regional warming extending beyond the urban areas boundaries. Finally, the comparison to temperature observations available for Paris area highlighted that the detailed urban canopy model improved the modeling of the urban heat island compared with a simpler approach.

Northwest Montana/North Idaho transmission corridor study: a computer-assisted corridor location and impact evaluation assessment

Treesearch

Timothy J. Murray; Daniel J. Bisenius; Jay G. Marcotte

1979-01-01

A computer-assisted method was used to locate and evaluate approximately 1,200 miles of alternative corridors within an 8,000 square mile study region. The method involved in-depth impact analyses for nine major location criteria or determinant models. Regional "experts" from the Rocky Mountain area participated with BPA in developing model structure....

A Study of the Impact of Dams on Streamflow and Sediment Retention in the Mekong River Basin

NASA Astrophysics Data System (ADS)

Munroe, T.; Anderson, E.; Markert, K. N.; Griffin, R.

2017-12-01

Dam construction in the Mekong Basin has many cascading effects on the ecology, economy, and hydrology of the surrounding region. Current studies that assess the hydrological impact of dams in the region focus on only one or a small subset (<10) of dams. The focus of this study is to utilize the Soil Water Assessment Tool (SWAT), a rainfall-runoff hydrologic model to determine change in streamflow and sedimentation in the Mekong Basin before and after the construction of dams. This study uses land cover land use and reservoir datasets created by the NASA SERVIR-Mekong Regional Land Cover Monitoring System and Dam Inundation Mapping Tool as inputs into the model. The study also builds on the capabilities of the SWAT model by using the sediment trapping efficiency (STE) equation from Brune (1953), rewritten by Kummu (2007), to calculate STE of dams and estimate change in sediment concentration downstream. The outputs from this study can be used to inform dam operation policies, study the correlation between dams and delta subsidence, and study the impact of dams on river fisheries, which are all pressing issues in the Mekong region.

Haplotype-based approach to known MS-associated regions increases the amount of explained risk

PubMed Central

Khankhanian, Pouya; Gourraud, Pierre-Antoine; Lizee, Antoine; Goodin, Douglas S

2015-01-01

Genome-wide association studies (GWAS), using single nucleotide polymorphisms (SNPs), have yielded 110 non-human leucocyte antigen genomic regions that are associated with multiple sclerosis (MS). Despite this large number of associations, however, only 28% of MS-heritability can currently be explained. Here we compare the use of multi-SNP-haplotypes to the use of single-SNPs as alternative methods to describe MS genetic risk. SNP-haplotypes (of various lengths from 1 up to 15 contiguous SNPs) were constructed at each of the 110 previously identified, MS-associated, genomic regions. Even after correcting for the larger number of statistical comparisons made when using the haplotype-method, in 32 of the regions, the SNP-haplotype based model was markedly more significant than the single-SNP based model. By contrast, in no region was the single-SNP based model similarly more significant than the SNP-haplotype based model. Moreover, when we included the 932 MS-associated SNP-haplotypes (that we identified from 102 regions) as independent variables into a logistic linear model, the amount of MS-heritability, as assessed by Nagelkerke's R-squared, was 38%, which was considerably better than 29%, which was obtained by using only single-SNPs. This study demonstrates that SNP-haplotypes can be used to fine-map the genetic associations within regions of interest previously identified by single-SNP GWAS. Moreover, the amount of the MS genetic risk explained by the SNP-haplotype associations in the 110 MS-associated genomic regions was considerably greater when using SNP-haplotypes than when using single-SNPs. Also, the use of SNP-haplotypes can lead to the discovery of new regions of interest, which have not been identified by a single-SNP GWAS. PMID:26185143

Advances in target imaging of deep Earth structure

NASA Astrophysics Data System (ADS)

Masson, Y.; Romanowicz, B. A.; Clouzet, P.

2015-12-01

A new generation of global tomographic models (Lekić and Romanowicz, 2011; French et al, 2013, 2014) has emerged with the development of accurate numerical wavefield computations in a 3D earth combined with access to enhanced HPC capabilities. These models have sharpened up mantle images and unveiled relatively small scale structures that were blurred out in previous generation models. Fingerlike structures have been found at the base of the oceanic asthenosphere, and vertically oriented broad low velocity plume conduits extend throughout the lower mantle beneath those major hotspots that are located within the perimeter of the deep mantle large low shear velocity provinces (LLSVPs). While providing new insights into our understanding of mantle dynamics, the detailed morphology of these features, requires further efforts to obtain higher resolution images. The focus of our ongoing effort is to develop advanced tomographic methods to image remote regions of the Earth at fine scales. We have developed an approach in which distant sources (located outside of the target region) are replaced by an equivalent set of local sources located at the border of the computational domain (Masson et al., 2014). A limited number of global simulations in a reference 3D earth model is then required. These simulations are computed prior to the regional inversion, while iterations of the model need to be performed only within the region of interest, potentially allowing us to include shorter periods at limited additional computational cost. Until now, the application was limited to a distribution of receivers inside the target region. This is particularly suitable for studies of upper mantle structure in regions with dense arrays (e.g. see our companion presentation Clouzet et al., this Fall AGU). Here we present our latest development that now can include teleseismic data recorded outside the imaged region. This allows us to perform regional waveform tomography in the situation where neither earthquakes nor seismological stations are present within the region of interest, such as would be desireable for the study of a region in the deep mantle. We present benchmark tests showing how the uncertainties in the reference 3D model employed outside of the target region affects the quality of the regional tomographic images obtained.

Regional variability of sea level change using a global ocean model.

NASA Astrophysics Data System (ADS)

Lombard, A.; Garric, G.; Cazenave, A.; Penduff, T.; Molines, J.

2007-12-01

We analyse different runs of a global eddy-permitting (1/4 degree) ocean model driven by atmospheric forcing to evaluate regional variability of sea level change over 1993-2001, 1998-2006 and over the long period 1958-2004. No data assimilation is performed in the model, contrarily to previous similar studies (Carton et al., 2005; Wunsch et al., 2007; Koehl and Stammer, 2007). We compare the model-based regional sea level trend patterns with the one deduced from satellite altimetry data. We examine respective contributions of steric and bottom pressure changes to total regional sea level changes. For the steric component, we analyze separately the contributions of temperature and salinity changes as well as upper and lower ocean contributions.

Meta-modeling soil organic carbon sequestration potential and its application at regional scale.

PubMed

Luo, Zhongkui; Wang, Enli; Bryan, Brett A; King, Darran; Zhao, Gang; Pan, Xubin; Bende-Michl, Ulrike

2013-03-01

Upscaling the results from process-based soil-plant models to assess regional soil organic carbon (SOC) change and sequestration potential is a great challenge due to the lack of detailed spatial information, particularly soil properties. Meta-modeling can be used to simplify and summarize process-based models and significantly reduce the demand for input data and thus could be easily applied on regional scales. We used the pre-validated Agricultural Production Systems sIMulator (APSIM) to simulate the impact of climate, soil, and management on SOC at 613 reference sites across Australia's cereal-growing regions under a continuous wheat system. We then developed a simple meta-model to link the APSIM-modeled SOC change to primary drivers, i.e., the amount of recalcitrant SOC, plant available water capacity of soil, soil pH, and solar radiation, temperature, and rainfall in the growing season. Based on high-resolution soil texture data and 8165 climate data points across the study area, we used the meta-model to assess SOC sequestration potential and the uncertainty associated with the variability of soil characteristics. The meta-model explained 74% of the variation of final SOC content as simulated by APSIM. Applying the meta-model to Australia's cereal-growing regions reveals regional patterns in SOC, with higher SOC stock in cool, wet regions. Overall, the potential SOC stock ranged from 21.14 to 152.71 Mg/ha with a mean of 52.18 Mg/ha. Variation of soil properties induced uncertainty ranging from 12% to 117% with higher uncertainty in warm, wet regions. In general, soils in Australia's cereal-growing regions under continuous wheat production were simulated as a sink of atmospheric carbon dioxide with a mean sequestration potential of 8.17 Mg/ha.

[Effect of near infrared spectrum on the precision of PLS model for oil yield from oil shale].

PubMed

Wang, Zhi-Hong; Liu, Jie; Chen, Xiao-Chao; Sun, Yu-Yang; Yu, Yang; Lin, Jun

2012-10-01

It is impossible to use present measurement methods for the oil yield of oil shale to realize in-situ detection and these methods unable to meet the requirements of the oil shale resources exploration and exploitation. But in-situ oil yield analysis of oil shale can be achieved by the portable near infrared spectroscopy technique. There are different correlativities of NIR spectrum data formats and contents of sample components, and the different absorption specialities of sample components shows in different NIR spectral regions. So with the proportioning samples, the PLS modeling experiments were done by 3 formats (reflectance, absorbance and K-M function) and 4 regions of modeling spectrum, and the effect of NIR spectral format and region to the precision of PLS model for oil yield from oil shale was studied. The results show that the best data format is reflectance and the best modeling region is combination spectral range by PLS model method and proportioning samples. Therefore, the appropriate data format and the proper characteristic spectral region can increase the precision of PLS model for oil yield form oil shale.

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis

PubMed Central

Gobiet, Andreas

2016-01-01

ABSTRACT Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio‐temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan‐European data sets and a set that combines eight very high‐resolution station‐based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post‐processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small‐scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate‐mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments. PMID:28111497

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis.

PubMed

Prein, Andreas F; Gobiet, Andreas

2017-01-01

Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio-temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan-European data sets and a set that combines eight very high-resolution station-based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post-processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small-scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate-mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments.

INTERCOMPARISON STUDY OF ATMOSPHERIC MERCURY MODELS: 1. COMPARISON OF MODELS WITH SHORT-TERM MEASUREMENTS

EPA Science Inventory

Five regional scale models with a horizontal domain covering the European continent and its surrounding seas, one hemispheric and one global scale model participated in an atmospheric mercury modelling intercomparison study. Model-predicted concentrations in ambient air were comp...

Evaluation and application of regional turbidity-sediment regression models in Virginia

USGS Publications Warehouse

Hyer, Kenneth; Jastram, John D.; Moyer, Douglas; Webber, James S.; Chanat, Jeffrey G.

2015-01-01

Conventional thinking has long held that turbidity-sediment surrogate-regression equations are site specific and that regression equations developed at a single monitoring station should not be applied to another station; however, few studies have evaluated this issue in a rigorous manner. If robust regional turbidity-sediment models can be developed successfully, their applications could greatly expand the usage of these methods. Suspended sediment load estimation could occur as soon as flow and turbidity monitoring commence at a site, suspended sediment sampling frequencies for various projects potentially could be reduced, and special-project applications (sediment monitoring following dam removal, for example) could be significantly enhanced. The objective of this effort was to investigate the turbidity-suspended sediment concentration (SSC) relations at all available USGS monitoring sites within Virginia to determine whether meaningful turbidity-sediment regression models can be developed by combining the data from multiple monitoring stations into a single model, known as a “regional” model. Following the development of the regional model, additional objectives included a comparison of predicted SSCs between the regional model and commonly used site-specific models, as well as an evaluation of why specific monitoring stations did not fit the regional model.

Prediction of lake depth across a 17-state region in the United States

USGS Publications Warehouse

Oliver, Samantha K.; Soranno, Patricia A.; Fergus, C. Emi; Wagner, Tyler; Winslow, Luke A.; Scott, Caren E.; Webster, Katherine E.; Downing, John A.; Stanley, Emily H.

2016-01-01

Lake depth is an important characteristic for understanding many lake processes, yet it is unknown for the vast majority of lakes globally. Our objective was to develop a model that predicts lake depth using map-derived metrics of lake and terrestrial geomorphic features. Building on previous models that use local topography to predict lake depth, we hypothesized that regional differences in topography, lake shape, or sedimentation processes could lead to region-specific relationships between lake depth and the mapped features. We therefore used a mixed modeling approach that included region-specific model parameters. We built models using lake and map data from LAGOS, which includes 8164 lakes with maximum depth (Zmax) observations. The model was used to predict depth for all lakes ≥4 ha (n = 42 443) in the study extent. Lake surface area and maximum slope in a 100 m buffer were the best predictors of Zmax. Interactions between surface area and topography occurred at both the local and regional scale; surface area had a larger effect in steep terrain, so large lakes embedded in steep terrain were much deeper than those in flat terrain. Despite a large sample size and inclusion of regional variability, model performance (R2 = 0.29, RMSE = 7.1 m) was similar to other published models. The relative error varied by region, however, highlighting the importance of taking a regional approach to lake depth modeling. Additionally, we provide the largest known collection of observed and predicted lake depth values in the United States.

Dynamics of a developing economy with a remote region: Agglomeration, trade integration and trade patterns

NASA Astrophysics Data System (ADS)

Commendatore, Pasquale; Kubin, Ingrid; Sushko, Iryna

2018-05-01

We consider a three-region developing economy with poor transport infrastructures. Two models are related to different stages of development: in the first all regions are autarkic; in the second two of the regions begin to integrate with the third region still not accessible to trade. The properties of the two models are studied also considering the interplay between industry location and trade patterns. Dynamics of these models are described by two-dimensional piecewise smooth maps, characterized by multistability and complex bifurcation structure of the parameter space. We obtain analytical results related to stability of various fixed points and illustrate several bifurcation structures by means of two-dimensional bifurcation diagrams and basins of coexisting attractors.

Mapping the total electron content over Malaysia using Spherical Cap Harmonic Analysis

NASA Astrophysics Data System (ADS)

Bahari, S.; Abdullah, M.; Bouya, Z.; Musa, T. A.

2017-12-01

The ionosphere over Malaysia is unique because of her location which is in close proximity to the geomagnetic equator and is in the equatorial regions. In this region, the magnetic field is horizontally oriented from south to north and field aligned direction is in the meridional plane (ExB) which becomes the source of equatorial ionospheric anomaly occurrence such as plasma bubble, fountain effects and others. Until today, there is no model that has been developed over Malaysia to study the ionosphere. Due to that, the main objective of this paper is to develop a new technique for mapping the total electron content (TEC) from GPS measurements. Data by myRTKnet network of GPS receiver over Malaysia were used in this study. A new methodology, based on modified spherical cap harmonic analysis (SCHA), was developed to estimate diurnal vertical TEC over the region using GPS observations. The SCHA model is based on longitudinal expansion in Fourier series and fractional Legendre co-latitudinal functions over a spherical cap-like region. The TEC map with spatial resolution of 0.15 ° x 0.15 ° in latitude and longitude with the time resolution of 30 seconds are derived. TEC maps from the SCHA model were compared with the global ionospheric map and other regional models. Result shows that during low solar activity, SCHA model had a better mapping with the accuracy of less than 1 TECU compared to other regional models.

Projected changes over western Canada using convection-permitting regional climate model and the pseudo-global warming method

NASA Astrophysics Data System (ADS)

Li, Y.; Kurkute, S.; Chen, L.

2017-12-01

Results from the General Circulation Models (GCMs) suggest more frequent and more severe extreme rain events in a climate warmer than the present. However, current GCMs cannot accurately simulate extreme rainfall events of short duration due to their coarse model resolutions and parameterizations. This limitation makes it difficult to provide the detailed quantitative information for the development of regional adaptation and mitigation strategies. Dynamical downscaling using nested Regional Climate Models (RCMs) are able to capture key regional and local climate processes with an affordable computational cost. Recent studies have demonstrated that the downscaling of GCM results with weather-permitting mesoscale models, such as the pseudo-global warming (PGW) technique, could be a viable and economical approach of obtaining valuable climate change information on regional scales. We have conducted a regional climate 4-km Weather Research and Forecast Model (WRF) simulation with one domain covering the whole western Canada, for a historic run (2000-2015) and a 15-year future run to 2100 and beyond with the PGW forcing. The 4-km resolution allows direct use of microphysics and resolves the convection explicitly, thus providing very convincing spatial detail. With this high-resolution simulation, we are able to study the convective mechanisms, specifically the control of convections over the Prairies, the projected changes of rainfall regimes, and the shift of the convective mechanisms in a warming climate, which has never been examined before numerically at such large scale with such high resolution.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

NASA Astrophysics Data System (ADS)

Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

2018-04-01

The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins

NASA Astrophysics Data System (ADS)

Arsenault, Richard; Poissant, Dominique; Brissette, François

2015-11-01

This paper evaluated the effects of parametric reduction of a hydrological model on five regionalization methods and 267 catchments in the province of Quebec, Canada. The Sobol' variance-based sensitivity analysis was used to rank the model parameters by their influence on the model results and sequential parameter fixing was performed. The reduction in parameter correlations improved parameter identifiability, however this improvement was found to be minimal and was not transposed in the regionalization mode. It was shown that 11 of the HSAMI models' 23 parameters could be fixed with little or no loss in regionalization skill. The main conclusions were that (1) the conceptual lumped models used in this study did not represent physical processes sufficiently well to warrant parameter reduction for physics-based regionalization methods for the Canadian basins examined and (2) catchment descriptors did not adequately represent the relevant hydrological processes, namely snow accumulation and melt.

Regional contribution to variability and trends of global gross primary productivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Min; Rafique, Rashid; Asrar, Ghassem R.

Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000-2010 total global GPP estimated from the model ensemble to be 117±13 Pg C yr-1 (mean ± 1 standard deviation), whichmore » was higher than MODIS (112 Pg C yr-1), and close to the MTE (120 Pg C yr-1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.« less

Regional contribution to variability and trends of global gross primary productivity

NASA Astrophysics Data System (ADS)

Chen, Min; Rafique, Rashid; Asrar, Ghassem R.; Bond-Lamberty, Ben; Ciais, Philippe; Zhao, Fang; Reyer, Christopher P. O.; Ostberg, Sebastian; Chang, Jinfeng; Ito, Akihiko; Yang, Jia; Zeng, Ning; Kalnay, Eugenia; West, Tristram; Leng, Guoyong; Francois, Louis; Munhoven, Guy; Henrot, Alexandra; Tian, Hanqin; Pan, Shufen; Nishina, Kazuya; Viovy, Nicolas; Morfopoulos, Catherine; Betts, Richard; Schaphoff, Sibyll; Steinkamp, Jörg; Hickler, Thomas

2017-10-01

Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000-2010 total global GPP estimated from the model ensemble to be 117 ± 13 Pg C yr-1 (mean ± 1 standard deviation), which was higher than MODIS (112 Pg C yr-1), and close to the MTE (120 Pg C yr-1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.

Upper Mantle Velocity Structure beneath the Northeastern Philippine Sea Constrained by Waveform Modeling of P Triplicated Phases

NASA Astrophysics Data System (ADS)

Cho, S.; Rhie, J.; Lee, S. H.; Kim, S.; Kang, T. S.

2017-12-01

A study on the detailed velocity structures of the stagnant Pacific slab is important to understand the complex processes happening in the upper mantle. Although waveform modeling of P triplicated phases can reveal the detailed velocity structures especially for the discontinuities, the regions where the method can be applied are limited due to uneven distribution of earthquakes and stations. In this study, we used waveforms generated by two deep earthquakes near Izu-Bonin Trench and recorded by stations in South Korea. These event-station pairs are appropriate to study the upper mantle structures beneath the northeastern Philippine Sea, where no previous results by triplicated waveform modeling have been reported. In this region, the subducting Pacific slab seems to hit the 660 km discontinuity and become stagnant. We applied the reflectivity method to calculate waveforms and found the best fitting model by trial-and-error and manual inspection. In general, our best model is similar to M3.11, which is widely accepted 1D model for the regions where the stagnant slab exists and the 660 km discontinuity is depressed by the slab. The most noticeable feature of our model is that P wave velocities of inside and above the slab are considerably higher and lower than ones for M3.11, respectively. This specific velocity model is necessary to explain arrivals of two distinct phases identified in observed waveforms; one refracts inside the slab and the other reflects on the upper boundary of the slab. To understand the cause of the differences between our model and M3.11, further studies including thermal and mechanical modelling of the slab in this region will be recommended.

Burglar Target Selection

PubMed Central

Townsley, Michael; Bernasco, Wim; Ruiter, Stijn; Johnson, Shane D.; White, Gentry; Baum, Scott

2015-01-01

Objectives: This study builds on research undertaken by Bernasco and Nieuwbeerta and explores the generalizability of a theoretically derived offender target selection model in three cross-national study regions. Methods: Taking a discrete spatial choice approach, we estimate the impact of both environment- and offender-level factors on residential burglary placement in the Netherlands, the United Kingdom, and Australia. Combining cleared burglary data from all study regions in a single statistical model, we make statistical comparisons between environments. Results: In all three study regions, the likelihood an offender selects an area for burglary is positively influenced by proximity to their home, the proportion of easily accessible targets, and the total number of targets available. Furthermore, in two of the three study regions, juvenile offenders under the legal driving age are significantly more influenced by target proximity than adult offenders. Post hoc tests indicate the magnitudes of these impacts vary significantly between study regions. Conclusions: While burglary target selection strategies are consistent with opportunity-based explanations of offending, the impact of environmental context is significant. As such, the approach undertaken in combining observations from multiple study regions may aid criminology scholars in assessing the generalizability of observed findings across multiple environments. PMID:25866418

The CEOP Inter-Monsoon Studies (CIMS)

NASA Technical Reports Server (NTRS)

Lau, William K. M.

2003-01-01

Prediction of climate relies on models, and better model prediction depends on good model physics. Improving model physics requires the maximal utilization of climate data of the past, present and future. CEOP provides the first example of a comprehensive, integrated global and regional data set, consisting of globally gridded data, reference site in-situ observations, model location time series (MOLTS), and integrated satellite data for a two-year period covering two complete annual cycles of 2003-2004. The monsoon regions are the most important socio-economically in terms of devastation by floods and droughts, and potential impacts from climate change md fluctuatinns nf the hydrologic cyc!e. Scientifically, it is most challenging, because of complex interactions of atmosphere, land and oceans, local vs. remote forcings in contributing to climate variability and change in the region. Given that many common features, and physical teleconnection exist among different monsoon regions, an international research focus on monsoon must be coordinated and sustained. Current models of the monsoon are grossly inadequate for regional predictions. For improvement, models must be confronted with relevant observations, and model physic developers must be made to be aware of the wealth of information from existing climate data, field measurements, and satellite data that can be used to improve models. Model transferability studles must be conducted. CIMS is a major initiative under CEOP to engage the modeling and the observational communities to join in a coordinated effort to study the monsoons. The objectives of CIMS are (a) To provide a better understanding of fundamental physical processes (diurnal cycle, annual cycle, and intraseasonal oscillations) in monsoon regions around the world and (b) To demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. In this talk, I will present the basic concepts of CIMS and the key scientific problems facing monsoon climates and provide examples of common monsoon features, and possible monsoon induced teleconnections linking different parts of the world.

Development of a generic auto-calibration package for regional ecological modeling and application in the Central Plains of the United States

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang; Li, Zhengpeng; Dahal, Devendra; Young, Claudia J.; Schmidt, Gail L.; Liu, Jinxun; Davis, Brian; Sohl, Terry L.; Werner, Jeremy M.; Oeding, Jennifer

2014-01-01

Process-oriented ecological models are frequently used for predicting potential impacts of global changes such as climate and land-cover changes, which can be useful for policy making. It is critical but challenging to automatically derive optimal parameter values at different scales, especially at regional scale, and validate the model performance. In this study, we developed an automatic calibration (auto-calibration) function for a well-established biogeochemical model—the General Ensemble Biogeochemical Modeling System (GEMS)-Erosion Deposition Carbon Model (EDCM)—using data assimilation technique: the Shuffled Complex Evolution algorithm and a model-inversion R package—Flexible Modeling Environment (FME). The new functionality can support multi-parameter and multi-objective auto-calibration of EDCM at the both pixel and regional levels. We also developed a post-processing procedure for GEMS to provide options to save the pixel-based or aggregated county-land cover specific parameter values for subsequent simulations. In our case study, we successfully applied the updated model (EDCM-Auto) for a single crop pixel with a corn–wheat rotation and a large ecological region (Level II)—Central USA Plains. The evaluation results indicate that EDCM-Auto is applicable at multiple scales and is capable to handle land cover changes (e.g., crop rotations). The model also performs well in capturing the spatial pattern of grain yield production for crops and net primary production (NPP) for other ecosystems across the region, which is a good example for implementing calibration and validation of ecological models with readily available survey data (grain yield) and remote sensing data (NPP) at regional and national levels. The developed platform for auto-calibration can be readily expanded to incorporate other model inversion algorithms and potential R packages, and also be applied to other ecological models.

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2011-12-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Uncertainty Quantification and Parameter Tuning: A Case Study of Convective Parameterization Scheme in the WRF Regional Climate Model

NASA Astrophysics Data System (ADS)

Qian, Y.; Yang, B.; Lin, G.; Leung, R.; Zhang, Y.

2012-04-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. The latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2012-03-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e. the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Change in the Pathologic Supraspinatus: A Three-Dimensional Model of Fiber Bundle Architecture within Anterior and Posterior Regions

PubMed Central

Kim, Soo Y.; Sachdeva, Rohit; Li, Zi; Rosser, Benjamin W. C.

2015-01-01

Supraspinatus tendon tears are common and lead to changes in the muscle architecture. To date, these changes have not been investigated for the distinct regions and parts of the pathologic supraspinatus. The purpose of this study was to create a novel three-dimensional (3D) model of the muscle architecture throughout the supraspinatus and to compare the architecture between muscle regions and parts in relation to tear severity. Twelve cadaveric specimens with varying degrees of tendon tears were used. Three-dimensional coordinates of fiber bundles were collected in situ using serial dissection and digitization. Data were reconstructed and modeled in 3D using Maya. Fiber bundle length (FBL) and pennation angle (PA) were computed and analyzed. FBL was significantly shorter in specimens with large retracted tears compared to smaller tears, with the deeper fibers being significantly shorter than other parts in the anterior region. PA was significantly greater in specimens with large retracted tears, with the superficial fibers often demonstrating the largest PA. The posterior region was absent in two specimens with extensive tears. Architectural changes associated with tendon tears affect the regions and varying depths of supraspinatus differently. The results provide important insights on residual function of the pathologic muscle, and the 3D model includes detailed data that can be used in future modeling studies. PMID:26413533

Study of Regional Volcanic Impact on the Middle East and North Africa using high-resolution global and regional models

NASA Astrophysics Data System (ADS)

Osipov, Sergey; Dogar, Mohammad; Stenchikov, Georgiy

2016-04-01

High-latitude winter warming after strong equatorial volcanic eruptions caused by circulation changes associated with the anomalously positive phase of Arctic Oscillation is a subject of active research during recent decade. But severe winter cooling in the Middle East observed after the Mt. Pinatubo eruption of 1991, although recognized, was not thoroughly investigated. These severe regional climate perturbations in the Middle East cannot be explained by solely radiative volcanic cooling, which suggests that a contribution of forced circulation changes could be important and significant. To better understand the mechanisms of the Middle East climate response and evaluate the contributions of dynamic and radiative effects we conducted a comparative study using Geophysical Fluid Dynamics Laboratory global High Resolution Atmospheric Model (HiRAM) with the effectively "regional-model-resolution" of 25-km and the regional Weather Research and Forecasting (WRF) model focusing on the eruption of Mount Pinatubo on June 15, 1991 followed by a pronounced positive phase of the Arctic Oscillation. The WRF model has been configured over the Middle East and North Africa (MENA) region. The WRF code has been modified to interactively account for the radiative effect of volcanic aerosols. Both HiRAM and WRF capture the main features of the MENA climate response and show that in winter the dynamic effects in the Middle East prevail the direct radiative cooling from volcanic aerosols.

Climate model assessment of changes in winter-spring streamflow timing over North America

USGS Publications Warehouse

Kam, Jonghun; Knutson, Thomas R.; Milly, Paul C. D.

2018-01-01

Over regions where snow-melt runoff substantially contributes to winter-spring streamflows, warming can accelerate snow melt and reduce dry-season streamflows. However, conclusive detection of changes and attribution to anthropogenic forcing is hindered by brevity of observational records, model uncertainty, and uncertainty concerning internal variability. In this study, a detection/attribution of changes in mid-latitude North American winter-spring streamflow timing is examined using nine global climate models under multiple forcing scenarios. In this study, robustness across models, start/end dates for trends, and assumptions about internal variability is evaluated. Marginal evidence for an emerging detectable anthropogenic influence (according to four or five of nine models) is found in the north-central U.S., where winter-spring streamflows have been coming earlier. Weaker indications of detectable anthropogenic influence (three of nine models) are found in the mountainous western U.S./southwestern Canada and in extreme northeastern U.S./Canadian Maritimes. In the former region, a recent shift toward later streamflows has rendered the full-record trend toward earlier streamflows only marginally significant, with possible implications for previously published climate change detection findings for streamflow timing in this region. In the latter region, no forced model shows as large a shift toward earlier streamflow timing as the detectable observed shift. In other (including warm, snow-free) regions, observed trends are typically not detectable, although in the U.S. central plains we find detectable delays in streamflow, which are inconsistent with forced model experiments.

The Crustal Structure of the North-South Earthquake Belt in China Revealed from Deep Seismic Soundings and Gravity Data

NASA Astrophysics Data System (ADS)

Zhao, Yang; Guo, Lianghui; Shi, Lei; Li, Yonghua

2018-01-01

The North-South earthquake belt (NSEB) is one of the major earthquake regions in China. The studies of crustal structure play a great role in understanding tectonic evolution and in evaluating earthquake hazards in this region. However, some fundamental crustal parameters, especially crustal interface structure, are not clear in this region. In this paper, we reconstructed the crustal interface structure around the NSEB based on both the deep seismic sounding (DSS) data and the gravity data. We firstly reconstructed the crustal structure of crystalline basement (interface G), interface between upper and lower crusts (interface C) and Moho in the study area by compiling the results of 38 DSS profiles published previously. Then, we forwardly calculated the gravity anomalies caused by the interfaces G and C, and then subtracted them from the complete Bouguer gravity anomalies, yielding the regional gravity anomalies mainly due to the Moho interface. We then utilized a lateral-variable density interface inversion technique with constraints of the DSS data to invert the regional anomalies for the Moho depth model in the study area. The reliability of our Moho depth model was evaluated by comparing with other Moho depth models derived from other gravity inversion technique and receiver function analysis. Based on our Moho depth model, we mapped the crustal apparent density distribution in the study area for better understanding the geodynamics around the NSEB.

A holistic approach for large-scale derived flood frequency analysis

NASA Astrophysics Data System (ADS)

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

2017-04-01

Spatial consistency, which has been usually disregarded because of the reported methodological difficulties, is increasingly demanded in regional flood hazard (and risk) assessments. This study aims at developing a holistic approach for deriving flood frequency at large scale consistently. A large scale two-component model has been established for simulating very long-term multisite synthetic meteorological fields and flood flow at many gauged and ungauged locations hence reflecting the spatially inherent heterogeneity. The model has been applied for the region of nearly a half million km2 including Germany and parts of nearby countries. The model performance has been multi-objectively examined with a focus on extreme. By this continuous simulation approach, flood quantiles for the studied region have been derived successfully and provide useful input for a comprehensive flood risk study.

A refined regional modeling approach for the Corn Belt - Experiences and recommendations for large-scale integrated modeling

NASA Astrophysics Data System (ADS)

Panagopoulos, Yiannis; Gassman, Philip W.; Jha, Manoj K.; Kling, Catherine L.; Campbell, Todd; Srinivasan, Raghavan; White, Michael; Arnold, Jeffrey G.

2015-05-01

Nonpoint source pollution from agriculture is the main source of nitrogen and phosphorus in the stream systems of the Corn Belt region in the Midwestern US. This region is comprised of two large river basins, the intensely row-cropped Upper Mississippi River Basin (UMRB) and Ohio-Tennessee River Basin (OTRB), which are considered the key contributing areas for the Northern Gulf of Mexico hypoxic zone according to the US Environmental Protection Agency. Thus, in this area it is of utmost importance to ensure that intensive agriculture for food, feed and biofuel production can coexist with a healthy water environment. To address these objectives within a river basin management context, an integrated modeling system has been constructed with the hydrologic Soil and Water Assessment Tool (SWAT) model, capable of estimating river basin responses to alternative cropping and/or management strategies. To improve modeling performance compared to previous studies and provide a spatially detailed basis for scenario development, this SWAT Corn Belt application incorporates a greatly refined subwatershed structure based on 12-digit hydrologic units or 'subwatersheds' as defined by the US Geological Service. The model setup, calibration and validation are time-demanding and challenging tasks for these large systems, given the scale intensive data requirements, and the need to ensure the reliability of flow and pollutant load predictions at multiple locations. Thus, the objectives of this study are both to comprehensively describe this large-scale modeling approach, providing estimates of pollution and crop production in the region as well as to present strengths and weaknesses of integrated modeling at such a large scale along with how it can be improved on the basis of the current modeling structure and results. The predictions were based on a semi-automatic hydrologic calibration approach for large-scale and spatially detailed modeling studies, with the use of the Sequential Uncertainty Fitting algorithm (SUFI-2) and the SWAT-CUP interface, followed by a manual water quality calibration on a monthly basis. The refined modeling approach developed in this study led to successful predictions across most parts of the Corn Belt region and can be used for testing pollution mitigation measures and agricultural economic scenarios, providing useful information to policy makers and recommendations on similar efforts at the regional scale.

Ethmoidectomy combined with superior meatus enlargement increases olfactory airflow

PubMed Central

Kondo, Kenji; Nomura, Tsutomu; Yamasoba, Tatsuya

2017-01-01

Objectives The relationship between a particular surgical technique in endoscopic sinus surgery (ESS) and airflow changes in the post‐operative olfactory region has not been assessed. The present study aimed to compare olfactory airflow after ESS between conventional ethmoidectomy and ethmoidectomy with superior meatus enlargement, using virtual ESS and computational fluid dynamics (CFD) analysis. Study Design Prospective computational study. Materials and Methods Nasal computed tomography images of four adult subjects were used to generate models of the nasal airway. The original preoperative model was digitally edited as virtual ESS by performing uncinectomy, ethmoidectomy, antrostomy, and frontal sinusotomy. The following two post‐operative models were prepared: conventional ethmoidectomy with normal superior meatus (ESS model) and ethmoidectomy with superior meatus enlargement (ESS‐SM model). The calculated three‐dimensional nasal geometries were confirmed using virtual endoscopy to ensure that they corresponded to the post‐operative anatomy observed in the clinical setting. Steady‐state, laminar, inspiratory airflow was simulated, and the velocity, streamline, and mass flow rate in the olfactory region were compared among the preoperative and two postoperative models. Results The mean velocity in the olfactory region, number of streamlines bound to the olfactory region, and mass flow rate were higher in the ESS‐SM model than in the other models. Conclusion We successfully used an innovative approach involving virtual ESS, virtual endoscopy, and CFD to assess postoperative outcomes after ESS. It is hypothesized that the increased airflow to the olfactory fossa achieved with ESS‐SM may lead to improved olfactory function; however, further studies are required. Level of Evidence NA. PMID:28894833

Comparing the appropriate geographic region for assessing built environmental correlates with walking trips using different metrics and model approaches

PubMed Central

Tribby, Calvin P.; Miller, Harvey J.; Brown, Barbara B.; Smith, Ken R.; Werner, Carol M.

2017-01-01

There is growing international evidence that supportive built environments encourage active travel such as walking. An unsettled question is the role of geographic regions for analyzing the relationship between the built environment and active travel. This paper examines the geographic region question by assessing walking trip models that use two different regions: walking activity spaces and self-defined neighborhoods. We also use two types of built environment metrics, perceived and audit data, and two types of study design, cross-sectional and longitudinal, to assess these regions. We find that the built environment associations with walking are dependent on the type of metric and the type of model. Audit measures summarized within walking activity spaces better explain walking trips compared to audit measures within self-defined neighborhoods. Perceived measures summarized within self-defined neighborhoods have mixed results. Finally, results differ based on study design. This suggests that results may not be comparable among different regions, metrics and designs; researchers need to consider carefully these choices when assessing active travel correlates. PMID:28237743

Comparison of Two Grid Refinement Approaches for High Resolution Regional Climate Modeling: MPAS vs WRF

NASA Astrophysics Data System (ADS)

Leung, L.; Hagos, S. M.; Rauscher, S.; Ringler, T.

2012-12-01

This study compares two grid refinement approaches using global variable resolution model and nesting for high-resolution regional climate modeling. The global variable resolution model, Model for Prediction Across Scales (MPAS), and the limited area model, Weather Research and Forecasting (WRF) model, are compared in an idealized aqua-planet context with a focus on the spatial and temporal characteristics of tropical precipitation simulated by the models using the same physics package from the Community Atmosphere Model (CAM4). For MPAS, simulations have been performed with a quasi-uniform resolution global domain at coarse (1 degree) and high (0.25 degree) resolution, and a variable resolution domain with a high-resolution region at 0.25 degree configured inside a coarse resolution global domain at 1 degree resolution. Similarly, WRF has been configured to run on a coarse (1 degree) and high (0.25 degree) resolution tropical channel domain as well as a nested domain with a high-resolution region at 0.25 degree nested two-way inside the coarse resolution (1 degree) tropical channel. The variable resolution or nested simulations are compared against the high-resolution simulations that serve as virtual reality. Both MPAS and WRF simulate 20-day Kelvin waves propagating through the high-resolution domains fairly unaffected by the change in resolution. In addition, both models respond to increased resolution with enhanced precipitation. Grid refinement induces zonal asymmetry in precipitation (heating), accompanied by zonal anomalous Walker like circulations and standing Rossby wave signals. However, there are important differences between the anomalous patterns in MPAS and WRF due to differences in the grid refinement approaches and sensitivity of model physics to grid resolution. This study highlights the need for "scale aware" parameterizations in variable resolution and nested regional models.

Modified Light Use Efficiency Model for Assessment of Carbon Sequestration in Grasslands of Kazakhstan: Combining Ground Biomass Data and Remote-sensing

NASA Technical Reports Server (NTRS)

Propastin, Pavel A.; Kappas, Martin W.; Herrmann, Stefanie M.; Tucker, Compton J.

2012-01-01

A modified light use efficiency (LUE) model was tested in the grasslands of central Kazakhstan in terms of its ability to characterize spatial patterns and interannual dynamics of net primary production (NPP) at a regional scale. In this model, the LUE of the grassland biome (en) was simulated from ground-based NPP measurements, absorbed photosynthetically active radiation (APAR) and meteorological observations using a new empirical approach. Using coarse-resolution satellite data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), monthly NPP was calculated from 1998 to 2008 over a large grassland region in Kazakhstan. The modelling results were verified against scaled up plot-level observations of grassland biomass and another available NPP data set derived from a field study in a similar grassland biome. The results indicated the reliability of productivity estimates produced by the model for regional monitoring of grassland NPP. The method for simulation of en suggested in this study can be used in grassland regions where no carbon flux measurements are accessible.

Time fractional capital-induced labor migration model

NASA Astrophysics Data System (ADS)

Ali Balcı, Mehmet

2017-07-01

In this study we present a new model of neoclassical economic growth by considering that workers move from regions with lower density of capital to regions with higher density of capital. Since the labor migration and capital flow involves self-similarities in long range time, we use the fractional order derivatives for the time variable. To solve this model we proposed Variational Iteration Method, and studied numerically labor migration flow data from Turkey along with other countries throughout the period of 1966-2014.

A Variational Inverse Model Study of Amazonian Methane Emissions including Observations from the AMAZONICA campaign

NASA Astrophysics Data System (ADS)

Wilson, C. J.; Gloor, M.; Chipperfield, M.; Miller, J. B.; Gatti, L.

2013-12-01

Methane (CH4) is a greenhouse gas which is emitted from a range of anthropogenic and natural sources, and since the industrial revolution its mean atmospheric concentration has climbed dramatically, reaching values unprecedented in at least the past 650,000 years. CH4 produces a relatively high radiative forcing effect upon the Earth's climate, and its atmospheric lifetime of approximately 10 years makes it a more appealing target for the mitigation of climate change over short timescales than long-lived greenhouse gases such as carbon dioxide. However, the spatial and temporal variation of CH4 emissions are still not well understood, though in recent years a number of top-down and bottom-up studies have attempted to construct improved emission budgets. Some top-down studies may suffer from poor observational coverage in tropical regions, however, especially in the planetary boundary layer, where the atmosphere is highly sensitive to emissions. For example, although satellite observations often take a large volume of measurements in tropical regions, these retrievals are not usually sensitive to concentrations at the planet's surface. Methane emissions from Amazon region, in particular, are often poorly constrained. Since emissions form this region, coming mainly from wetland and biomass burning sources, are thought to be relatively high, additional observations in this region would greatly help to constrain the geographical distribution of the global CH4 emission budget. In order to provide such measurements, the AMAZONICA project began to take regular flask measurements of CH4 and other trace gases from aircraft over four Amazonian sites from the year 2010 onwards. We first present a forward modelling study of these observations of Amazonian methane for the year 2010 using the TOMCAT Chemical Transport Model. The model is used to attribute variations at each site to a source type and region, and also to assess the ability of our current CH4 flux estimates to reproduce these observations. Although there is mostly good agreement between the modelled and observed CH4, we find discrepancies between the two at one site in the east of the region, indicating possible errors surrounding the surface fluxes of methane affecting this site. We also present the results of an inverse modelling study of methane emissions for the year 2010, using INVICAT, which is a new variational inverse model based upon TOMCAT. This study represents the first use of the INVICAT scheme to constrain emissions of an atmospheric trace gas. Similarly to many previous inverse model studies, this top-down study assimilates ground-based flask observations of CH4 from the NOAA ground network. However, in order to provide additional constraints of CH4 emissions in the Amazon region, flask observations taken as part of the AMAZONICA campaign are also assimilated. The results of this inversion provide improved Amazonian and global CH4 emission budgets for the year 2010.

Regional climate projections for the MENA-CORDEX domain: analysis of projected temperature and precipitation changes

NASA Astrophysics Data System (ADS)

Hänsler, Andreas; Weber, Torsten; Eggert, Bastian; Saeed, Fahad; Jacob, Daniela

2014-05-01

Within the CORDEX initiative a multi-model suite of regionalized climate change information will be made available for several regions of the world. The German Climate Service Center (CSC) is taking part in this initiative by applying the regional climate model REMO to downscale global climate projections of different coupled general circulation models (GCMs) for several CORDEX domains. Also for the MENA-CORDEX domain, a set of regional climate change projections has been established at the CSC by downscaling CMIP5 projections of the Max-Planck-Institute Earth System Model (MPI-ESM) for the scenarios RCP4.5 and RCP8.5 with the regional model REMO for the time period from 1950 to 2100 to a horizontal resolution of 0.44 degree. In this study we investigate projected changes in future climate conditions over the domain towards the end of the 21st century. Focus in the analysis is given to projected changes in the temperature and rainfall characteristics and their differences for the two scenarios will be highlighted.

Patterns of crop cover under future climates.

PubMed

Porfirio, Luciana L; Newth, David; Harman, Ian N; Finnigan, John J; Cai, Yiyong

2017-04-01

We study changes in crop cover under future climate and socio-economic projections. This study is not only organised around the global and regional adaptation or vulnerability to climate change but also includes the influence of projected changes in socio-economic, technological and biophysical drivers, especially regional gross domestic product. The climatic data are obtained from simulations of RCP4.5 and 8.5 by four global circulation models/earth system models from 2000 to 2100. We use Random Forest, an empirical statistical model, to project the future crop cover. Our results show that, at the global scale, increases and decreases in crop cover cancel each other out. Crop cover in the Northern Hemisphere is projected to be impacted more by future climate than the in Southern Hemisphere because of the disparity in the warming rate and precipitation patterns between the two Hemispheres. We found that crop cover in temperate regions is projected to decrease more than in tropical regions. We identified regions of concern and opportunities for climate change adaptation and investment.

Geoacoustic models of the Donghae-to-Gangneung region in the Korean continental margin of the East Sea

NASA Astrophysics Data System (ADS)

Ryang, Woo Hun; Kim, Seong Pil; Hahn, Jooyoung

2016-04-01

Geoacoustic model is to provide a model of the real seafloor with measured, extrapolated, and predicted values of geoacoustic environmental parameters. It controls acoustic propagation in underwater acoustics. In the Korean continental margin of the East Sea, this study reconstructed geoacoustic models using geoacoustic and marine geologic data of the Donghae-to-Gangneung region (37.4° to 37.8° in latitude). The models were based on the data of the high-resolution subbottom and air-gun seismic profiles with sediment cores. The Donghae region comprised measured P-wave velocities and attenuations of the cores, whereas the Gangneung region comprised regression values using measured values of the adjacent areas. Geoacoustic data of the cores were extrapolated down to a depth of the geoacoustic models. For actual modeling, the P-wave speed of the models was compensated to in situ depth below the sea floor using the Hamilton method. These geoacoustic models of this region probably contribute for geoacoustic and underwater acoustic modelling reflecting vertical and lateral variability of acoustic properties in the Korean continental margin of the western East Sea. Keywords: geoacoustic model, environmental parameter, East Sea, continental margin Acknowledgements: This research was supported by the research grants from the Agency of Defense Development (UD140003DD and UE140033DD).

Predicting ecological flow regime at ungaged sites: A comparison of methods

USGS Publications Warehouse

Murphy, Jennifer C.; Knight, Rodney R.; Wolfe, William J.; Gain, W. Scott

2012-01-01

Nineteen ecologically relevant streamflow characteristics were estimated using published rainfall–runoff and regional regression models for six sites with observed daily streamflow records in Kentucky. The regional regression model produced median estimates closer to the observed median for all but two characteristics. The variability of predictions from both models was generally less than the observed variability. The variability of the predictions from the rainfall–runoff model was greater than that from the regional regression model for all but three characteristics. Eight characteristics predicted by the rainfall–runoff model display positive or negative bias across all six sites; biases are not as pronounced for the regional regression model. Results suggest that a rainfall–runoff model calibrated on a single characteristic is less likely to perform well as a predictor of a range of other characteristics (flow regime) when compared with a regional regression model calibrated individually on multiple characteristics used to represent the flow regime. Poor model performance may misrepresent hydrologic conditions, potentially distorting the perceived risk of ecological degradation. Without prior selection of streamflow characteristics, targeted calibration, and error quantification, the widespread application of general hydrologic models to ecological flow studies is problematic. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

Test of High-resolution Global and Regional Climate Model Projections

NASA Astrophysics Data System (ADS)

Stenchikov, Georgiy; Nikulin, Grigory; Hansson, Ulf; Kjellström, Erik; Raj, Jerry; Bangalath, Hamza; Osipov, Sergey

2014-05-01

In scope of CORDEX project we have simulated the past (1975-2005) and future (2006-2050) climates using the GFDL global high-resolution atmospheric model (HIRAM) and the Rossby Center nested regional model RCA4 for the Middle East and North Africa (MENA) region. Both global and nested runs were performed with roughly the same spatial resolution of 25 km in latitude and longitude, and were driven by the 2°x2.5°-resolution fields from GFDL ESM2M IPCC AR5 runs. The global HIRAM simulations could naturally account for interaction of regional processes with the larger-scale circulation features like Indian Summer Monsoon, which is lacking from regional model setup. Therefore in this study we specifically address the consistency of "global" and "regional" downscalings. The performance of RCA4, HIRAM, and ESM2M is tested based on mean, extreme, trends, seasonal and inter-annual variability of surface temperature, precipitation, and winds. The impact of climate change on dust storm activity, extreme precipitation and water resources is specifically addressed. We found that the global and regional climate projections appear to be quite consistent for the modeled period and differ more significantly from ESM2M than between each other.

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Forecasting future needs and optimal allocation of medical residency positions: the Emilia-Romagna Region case study.

PubMed

Senese, Francesca; Tubertini, Paolo; Mazzocchetti, Angelina; Lodi, Andrea; Ruozi, Corrado; Grilli, Roberto

2015-01-30

Italian regional health authorities annually negotiate the number of residency grants to be financed by the National government and the number and mix of supplementary grants to be funded by the regional budget. This study provides regional decision-makers with a requirement model to forecast the future demand of specialists at the regional level. We have developed a system dynamics (SD) model that projects the evolution of the supply of medical specialists and three demand scenarios across the planning horizon (2030). Demand scenarios account for different drivers: demography, service utilization rates (ambulatory care and hospital discharges) and hospital beds. Based on the SD outputs (occupational and training gaps), a mixed integer programming (MIP) model computes potentially effective assignments of medical specialization grants for each year of the projection. To simulate the allocation of grants, we have compared how regional and national grants can be managed in order to reduce future gaps with respect to current training patterns. The allocation of 25 supplementary grants per year does not appear as effective in reducing expected occupational gaps as the re-modulation of all regional training vacancies.

Aspect of ECMWF downscaled Regional Climate Modeling in simulating Indian summer monsoon rainfall and dependencies on lateral boundary conditions

NASA Astrophysics Data System (ADS)

Ghosh, Soumik; Bhatla, R.; Mall, R. K.; Srivastava, Prashant K.; Sahai, A. K.

2018-03-01

Climate model faces considerable difficulties in simulating the rainfall characteristics of southwest summer monsoon. In this study, the dynamical downscaling of European Centre for Medium-Range Weather Forecast's (ECMWF's) ERA-Interim (EIN15) has been utilized for the simulation of Indian summer monsoon (ISM) through the Regional Climate Model version 4.3 (RegCM-4.3) over the South Asia Co-Ordinated Regional Climate Downscaling EXperiment (CORDEX) domain. The complexities of model simulation over a particular terrain are generally influenced by factors such as complex topography, coastal boundary, and lack of unbiased initial and lateral boundary conditions. In order to overcome some of these limitations, the RegCM-4.3 is employed for simulating the rainfall characteristics over the complex topographical conditions. For reliable rainfall simulation, implementations of numerous lower boundary conditions are forced in the RegCM-4.3 with specific horizontal grid resolution of 50 km over South Asia CORDEX domain. The analysis is considered for 30 years of climatological simulation of rainfall, outgoing longwave radiation (OLR), mean sea level pressure (MSLP), and wind with different vertical levels over the specified region. The dependency of model simulation with the forcing of EIN15 initial and lateral boundary conditions is used to understand the impact of simulated rainfall characteristics during different phases of summer monsoon. The results obtained from this study are used to evaluate the activity of initial conditions of zonal wind circulation speed, which causes an increase in the uncertainty of regional model output over the region under investigation. Further, the results showed that the EIN15 zonal wind circulation lacks sufficient speed over the specified region in a particular time, which was carried forward by the RegCM output and leads to a disrupted regional simulation in the climate model.

Modelling irrigated maize with a combination of coupled-model simulation and uncertainty analysis, in the northwest of China

NASA Astrophysics Data System (ADS)

Li, Y.; Kinzelbach, W.; Zhou, J.; Cheng, G. D.; Li, X.

2012-05-01

The hydrologic model HYDRUS-1-D and the crop growth model WOFOST are coupled to efficiently manage water resources in agriculture and improve the prediction of crop production. The results of the coupled model are validated by experimental studies of irrigated-maize done in the middle reaches of northwest China's Heihe River, a semi-arid to arid region. Good agreement is achieved between the simulated evapotranspiration, soil moisture and crop production and their respective field measurements made under current maize irrigation and fertilization. Based on the calibrated model, the scenario analysis reveals that the most optimal amount of irrigation is 500-600 mm in this region. However, for regions without detailed observation, the results of the numerical simulation can be unreliable for irrigation decision making owing to the shortage of calibrated model boundary conditions and parameters. So, we develop a method of combining model ensemble simulations and uncertainty/sensitivity analysis to speculate the probability of crop production. In our studies, the uncertainty analysis is used to reveal the risk of facing a loss of crop production as irrigation decreases. The global sensitivity analysis is used to test the coupled model and further quantitatively analyse the impact of the uncertainty of coupled model parameters and environmental scenarios on crop production. This method can be used for estimation in regions with no or reduced data availability.

Numerical Study of the Role of Shallow Convection in Moisture Transport and Climate

NASA Technical Reports Server (NTRS)

Seaman, Nelson L.; Stauffer, David R.; Munoz, Ricardo C.

2001-01-01

The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins of the Southern Great Plains (SGP) using a 3-D mesoscale model, the PSU/NCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. At the beginning of the study, it was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having high-quality parameterizations for the key physical processes controlling the water cycle. These included a detailed land-surface parameterization (the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) sub-model of Wetzel and Boone), an advanced boundary-layer parameterization (the 1.5-order turbulent kinetic energy (TKE) predictive scheme of Shafran et al.), and a more complete shallow convection parameterization (the hybrid-closure scheme of Deng et al.) than are available in most current models. PLACE is a product of researchers working at NASA's Goddard Space Flight Center in Greenbelt, MD. The TKE and shallow-convection schemes are the result of model development at Penn State. The long-range goal is to develop an integrated suite of physical sub-models that can be used for regional and perhaps global climate studies of the water budget. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the SGP. These schemes have been tested extensively through the course of this study and the latter two have been improved significantly as a consequence.

Modelling absorbing aerosol with ECHAM-HAM: Insights from regional studies

NASA Astrophysics Data System (ADS)

Tegen, Ina; Heinold, Bernd; Schepanski, Kerstin; Banks, Jamie; Kubin, Anne; Schacht, Jacob

2017-04-01

Quantifying distributions and properties of absorbing aerosol is a basis for investigations of interactions of aerosol particles with radiation and climate. While evaluations of aerosol models by field measurements can be particularly successful at the regional scale, such results need to be put into a global context for climate studies. We present an overview over studies performed at the Leibniz Institute for Tropospheric Research aiming at constraining the properties of mineral dust and soot aerosol in the global aerosol model ECHAM6-HAM2 based on different regional studies. An example is the impact of different sources for dust transported to central Asia, which is influenced, by far-range transport of dust from Arabia and the Sahara together with dust from local sources. Dust types from these different source regions were investigated in the context of the CADEX project and are expected to have different optical properties. For Saharan dust, satellite retrievals from MSG SEVIRI are used to constrain Saharan dust sources and optical properties. In the Arctic region, on one hand dust aerosol is simulated in the framework of the PalMod project. On the other hand aerosol measurements that will be taken during the DFG-funded (AC)3 field campaigns will be used to evaluate the simulated transport pathways of soot aerosol from European, North American and Asian sources, as well as the parameterization of soot ageing processes in ECHAM6-HAM2. Ultimately, results from these studies will improve the representation of aerosol absorption in the global model.

Regional climate modeling over the Maritime Continent: Assessment of RegCM3-BATS1e and RegCM3-IBIS

NASA Astrophysics Data System (ADS)

Gianotti, R. L.; Zhang, D.; Eltahir, E. A.

2010-12-01

Despite its importance to global rainfall and circulation processes, the Maritime Continent remains a region that is poorly simulated by climate models. Relatively few studies have been undertaken using a model with fine enough resolution to capture the small-scale spatial heterogeneity of this region and associated land-atmosphere interactions. These studies have shown that even regional climate models (RCMs) struggle to reproduce the climate of this region, particularly the diurnal cycle of rainfall. This study builds on previous work by undertaking a more thorough evaluation of RCM performance in simulating the timing and intensity of rainfall over the Maritime Continent, with identification of major sources of error. An assessment was conducted of the Regional Climate Model Version 3 (RegCM3) used in a coupled system with two land surface schemes: Biosphere Atmosphere Transfer System Version 1e (BATS1e) and Integrated Biosphere Simulator (IBIS). The model’s performance in simulating precipitation was evaluated against the 3-hourly TRMM 3B42 product, with some validation provided of this TRMM product against ground station meteorological data. It is found that the model suffers from three major errors in the rainfall histogram: underestimation of the frequency of dry periods, overestimation of the frequency of low intensity rainfall, and underestimation of the frequency of high intensity rainfall. Additionally, the model shows error in the timing of the diurnal rainfall peak, particularly over land surfaces. These four errors were largely insensitive to the choice of boundary conditions, convective parameterization scheme or land surface scheme. The presence of a wet or dry bias in the simulated volumes of rainfall was, however, dependent on the choice of convection scheme and boundary conditions. This study also showed that the coupled model system has significant error in overestimation of latent heat flux and evapotranspiration from the land surface, and specifically overestimation of interception loss with concurrent underestimation of transpiration, irrespective of the land surface scheme used. Discussion of the origin of these errors is provided, with some suggestions for improvement.

Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

NASA Technical Reports Server (NTRS)

Zhu, Jiang; Stevens, E.; Zavodsky, B. T.; Zhang, X.; Heinrichs, T.; Broderson, D.

2014-01-01

Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

Effective connectivities of cortical regions for top-down face processing: A Dynamic Causal Modeling study

PubMed Central

Li, Jun; Liu, Jiangang; Liang, Jimin; Zhang, Hongchuan; Zhao, Jizheng; Rieth, Cory A.; Huber, David E.; Li, Wu; Shi, Guangming; Ai, Lin; Tian, Jie; Lee, Kang

2013-01-01

To study top-down face processing, the present study used an experimental paradigm in which participants detected non-existent faces in pure noise images. Conventional BOLD signal analysis identified three regions involved in this illusory face detection. These regions included the left orbitofrontal cortex (OFC) in addition to the right fusiform face area (FFA) and right occipital face area (OFA), both of which were previously known to be involved in both top-down and bottom-up processing of faces. We used Dynamic Causal Modeling (DCM) and Bayesian model selection to further analyze the data, revealing both intrinsic and modulatory effective connectivities among these three cortical regions. Specifically, our results support the claim that the orbitofrontal cortex plays a crucial role in the top-down processing of faces by regulating the activities of the occipital face area, and the occipital face area in turn detects the illusory face features in the visual stimuli and then provides this information to the fusiform face area for further analysis. PMID:20423709

Applying GIPL2.0 Model to assess the permafrost dynamics on the Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

Wu, T.

2017-12-01

The modeling of active layer and permafrost distribution is of great importance to understand the permafrost dynamics of cold regions, especially in those regions where are difficult to approach such as the Qinghai-Tibet Plateau (QTP). In this study we have applied the Geophysical Institute Permafrost Lab model (GIPL2.0) to estimate the active layer thickness and assess the permafrost thermal regime on the QTP. The GIPL 2.0 have been widely applied in the Arctic regions of Alaska, however less on the QTP. The model has been calibrated according to the four active layer in-situ measurement sites which have different underlying surface and soil characteristics. We extended the original GIPL2 model depth to the depth of 18 m. After the calibration of the GIPL2.0 at those four sites, the first-hand single point model is expanded to a regional model. The key permafrost parameters were simulated, including active layer thickness (ALT), mean annual ground temperature (MAGT) at multiple soil layers, and the permafrost classification was also carried out in order to study the permafrost the thermal stability across the QTP. To validate the performance of expanded regional-GIPL2 model, we compare simulated ALT and MAGT at the depth of zero annual amplitude (DZAA) with observed data. It is demonstrated that the modifications regional-GIPL2 model are able to improve the accuracy of permafrost thermal regime simulations greatly on the QTP. The simulated ALT are generally underestimate the observed ones with the MBE value of -0.14 m and the RMSE value of 0.22 m. For the MAGT at the DZAA of all 51 sites, the simulation errors range from - 0.9 ° to 0.9 ° with the RMSE value of 0.41 °. For the whole permafrost area of the QTP, the simulated ALT ranges from 0 to 8 m, with an average of 2.30 m. The simulated results indicate that most of regions were underlain by the sub-stable permafrost and less regions were underlain by the extremely stable permafrost.

Regional variations in mortality rates in England and Wales: an analysis using multi-level modelling.

PubMed

Langford, I H; Bentham, G

1996-03-01

Mortality rates in England and Wales display a persistent regional pattern indicating generally poorer health in the North and West. Some of this is simply a reflection of regional differences in the extent of social deprivation which is known to exert a profound influence on health. Part of the pattern may also be the result of regional differences in urbanization which also affect mortality rates. However, there may be important regional differences over and above these compositional effects. This study attempts to establish the magnitude of such independent regional differences in mortality rates by using the techniques of multi-level modelling. Standardized mortality rates (SMRs) for males and females under 65 for 1989-91 in local authority districts are grouped into categories using the ACORN classification scheme. The Townsend Index is included as a measure of social deprivation. Using a cross-classified multi-level model, it is shown that region accounts for approximately four times more variation in SMRs than is explained by the ACORN classification. Analysis of diagnostic residuals show a clear North-South divide in excess mortality when both regional and socio-economic classification of districts are modelled simultaneously, a possibility allowed for by the use of a multi-level model.

Spatially explicit habitat models for 28 fishes from the Upper Mississippi River System (AHAG 2.0)

USGS Publications Warehouse

Ickes, Brian S.; Sauer, J.S.; Richards, N.; Bowler, M.; Schlifer, B.

2014-01-01

Environmental management actions in the Upper Mississippi River System (UMRS) typically require pre-project assessments of predicted benefits under a range of project scenarios. The U.S. Army Corps of Engineers (USACE) now requires certified and peer-reviewed models to conduct these assessments. Previously, habitat benefits were estimated for fish communities in the UMRS using the Aquatic Habitat Appraisal Guide (AHAG v.1.0; AHAG from hereon). This spreadsheet-based model used a habitat suitability index (HSI) approach that drew heavily upon Habitat Evaluation Procedures (HEP; U.S. Fish and Wildlife Service, 1980) by the U.S. Fish and Wildlife Service (USFWS). The HSI approach requires developing species response curves for different environmental variables that seek to broadly represent habitat. The AHAG model uses species-specific response curves assembled from literature values, data from other ecosystems, or best professional judgment. A recent scientific review of the AHAG indicated that the model’s effectiveness is reduced by its dated approach to large river ecosystems, uncertainty regarding its data inputs and rationale for habitat-species response relationships, and lack of field validation (Abt Associates Inc., 2011). The reviewers made two major recommendations: (1) incorporate empirical data from the UMRS into defining the empirical response curves, and (2) conduct post-project biological evaluations to test pre-project benefits estimated by AHAG. Our objective was to address the first recommendation and generate updated response curves for AHAG using data from the Upper Mississippi River Restoration-Environmental Management Program (UMRR-EMP) Long Term Resource Monitoring Program (LTRMP) element. Fish community data have been collected by LTRMP (Gutreuter and others, 1995; Ratcliff and others, in press) for 20 years from 6 study reaches representing 1,930 kilometers of river and >140 species of fish. We modeled a subset of these data (28 different species; occurrences at sampling sites as observed in day electrofishing samples) using multiple logistic regression with presence/absence responses. Each species’ probability of occurrence, at each sample site, was modeled as a function of 17 environmental variables observed at each sample site by LTRMP standardized protocols. The modeling methods used (1) a forward-selection process to identify the most important predictors and their relative contributions to predictions; (2) partial methods on the predictor set to control variance inflation; and (3) diagnostics for LTRMP design elements that may influence model fits. Models were fit for 28 species, representing 3 habitat guilds (Lentic, Lotic, and Generalist). We intended to develop “systemic models” using data from all six LTRMP study reaches simultaneously; however, this proved impossible. Thus, we “regionalized” the models, creating two models for each species: “Upper Reach” models, using data from Pools 4, 8, and 13; and “Lower Reach” models, using data from Pool 26, the Open River Reach of the Mississippi River, and the La Grange reach of the Illinois River. A total of 56 models were attempted. For any given site-scale prediction, each model used data from the three LTRMP study reaches comprising the regional model to make predictions. For example, a site-scale prediction in Pool 8 was made using data from Pools 4, 8, and 13. This is the fundamental nature and trade-off of regionalizing these models for broad management application. Model fits were deemed “certifiably good” using the Hosmer and Lemeshow Goodness-of-Fit statistic (Hosmer and Lemeshow, 2000). This test post-partitions model predictions into 10 groups and conducts inferential tests on correspondences between observed and expected probability of occurrence across all partitions, under Chi-square distributional assumptions. This permits an inferential test of how well the models fit and a tool for reporting when they did not (and perhaps why). Our goal was to develop regionalized models, and to assess and describe circumstances when a good fit was not possible. Seven fish species composed the Lentic guild. Good fits were achieved for six Upper Reach models. In the Lower Reach, no model produced good fits for the Lentic guild. This was due to (1) lentic species being much less prominent in the Lower Reach study areas, and (2) those that do express greater prominence principally do so only in the La Grange reach of the Illinois River. Thus, developing Lower Reach models for Lentic species will require parsing La Grange from the other two Lower Reach study areas and fitting separate models. We did not do that as part of this study, but it could be done at a later time. Nine species comprised the Lotic guild. Good fits were achieved for seven Upper Reach models and six Lower Reach models. Four species had good fits for both regions (flathead catfish, blue sucker, sauger, and shorthead redhorse). Three species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (blue catfish, rock bass, and skipjack herring). Twelve species comprised the Generalist guild. Good fits were achieved for five Upper Reach models and eight Lower Reach models. Six species had good fits for both regions (brook silverside, emerald shiner, freshwater drum, logperch, longnose gar, and white bass). Two species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (red shiner and blackstripe topminnow). Poorly fit models were almost always due to the diagnostic variable “field station,” a surrogate for river mile. In these circumstances, the residuals for “field station” were non-randomly distributed and often strongly ordered. This indicates either fitting “pool scale” models for these species and regions, or explicitly model covariances between “field station” and the other predictors within the existing modeling framework. Further efforts on these models should seek to resolve these issues using one of these two approaches. In total, nine species, representing two of the three guilds (Lotic and Generalist), produced well-fit models for both regions. These nine species should comprise the basis for AHAG 2.0. Additional work, likely requiring downscaling of the regional models to pool-scale models, will be needed to incorporate additional species. Alternately, a regionalized AHAG could be comprised of those species, per region, that achieved well-fit models. The number of species and the composition of the regional species pools will differ among regions as a consequence. Each of these alternatives has both pros and cons, and managers are encouraged to consider them fully before further advancing this approach to modeling multi-species habitat suitability.

Figure-ground organization and object recognition processes: an interactive account.

PubMed

Vecera, S P; O'Reilly, R C

1998-04-01

Traditional bottom-up models of visual processing assume that figure-ground organization precedes object recognition. This assumption seems logically necessary: How can object recognition occur before a region is labeled as figure? However, some behavioral studies find that familiar regions are more likely to be labeled figure than less familiar regions, a problematic finding for bottom-up models. An interactive account is proposed in which figure-ground processes receive top-down input from object representations in a hierarchical system. A graded, interactive computational model is presented that accounts for behavioral results in which familiarity effects are found. The interactive model offers an alternative conception of visual processing to bottom-up models.

Coronal Heating: Testing Models of Coronal Heating by Forward-Modeling the AIA Emission of the Ansample of Coronal Loops

NASA Astrophysics Data System (ADS)

Malanushenko, A. V.

2015-12-01

We present a systemic exploration of the properties of coronal heating, by forward-modeling the emission of the ensemble of 1D quasi-steady loops. This approximations were used in many theoretical models of the coronal heating. The latter is described in many such models in the form of power laws, relating heat flux through the photosphere or volumetric heating to the strength of the magnetic field and length of a given field line. We perform a large search in the parameter space of these power laws, amongst other variables, and compare the resulting emission of the active region to that observed by AIA. We use a recently developed magnetic field model which uses shapes of coronal loops to guide the magnetic model; the result closely resembles observed structures by design. We take advantage of this, by comparing, in individual sub-regions of the active region, the emission of the active region and its synthetic model. This study allows us to rule out many theoretical models and formulate predictions for the heating models to come.

Evaluating global reanalysis datasets for provision of boundary conditions in regional climate modelling

NASA Astrophysics Data System (ADS)

Moalafhi, Ditiro B.; Evans, Jason P.; Sharma, Ashish

2016-11-01

Regional climate modelling studies often begin by downscaling a reanalysis dataset in order to simulate the observed climate, allowing the investigation of regional climate processes and quantification of the errors associated with the regional model. To date choice of reanalysis to perform such downscaling has been made based either on convenience or on performance of the reanalyses within the regional domain for relevant variables such as near-surface air temperature and precipitation. However, the only information passed from the reanalysis to the regional model are the atmospheric temperature, moisture and winds at the location of the boundaries of the regional domain. Here we present a methodology to evaluate reanalyses derived lateral boundary conditions for an example domain over southern Africa using satellite data. This study focusses on atmospheric temperature and moisture which are easily available. Five commonly used global reanalyses (NCEP1, NCEP2, ERA-I, 20CRv2, and MERRA) are evaluated against the Atmospheric Infrared Sounder satellite temperature and relative humidity over boundaries of two domains centred on southern Africa for the years 2003-2012 inclusive. The study reveals that MERRA is the most suitable for climate mean with NCEP1 the next most suitable. For climate variability, ERA-I is the best followed by MERRA. Overall, MERRA is preferred for generating lateral boundary conditions for this domain, followed by ERA-I. While a "better" LBC specification is not the sole precursor to an improved downscaling outcome, any reduction in uncertainty associated with the specification of LBCs is a step in the right direction.

A comparison of metrics for assessing state-of-the-art climate models and implications for probabilistic projections of climate change

NASA Astrophysics Data System (ADS)

Ring, Christoph; Pollinger, Felix; Kaspar-Ott, Irena; Hertig, Elke; Jacobeit, Jucundus; Paeth, Heiko

2018-03-01

A major task of climate science are reliable projections of climate change for the future. To enable more solid statements and to decrease the range of uncertainty, global general circulation models and regional climate models are evaluated based on a 2 × 2 contingency table approach to generate model weights. These weights are compared among different methodologies and their impact on probabilistic projections of temperature and precipitation changes is investigated. Simulated seasonal precipitation and temperature for both 50-year trends and climatological means are assessed at two spatial scales: in seven study regions around the globe and in eight sub-regions of the Mediterranean area. Overall, 24 models of phase 3 and 38 models of phase 5 of the Coupled Model Intercomparison Project altogether 159 transient simulations of precipitation and 119 of temperature from four emissions scenarios are evaluated against the ERA-20C reanalysis over the 20th century. The results show high conformity with previous model evaluation studies. The metrics reveal that mean of precipitation and both temperature mean and trend agree well with the reference dataset and indicate improvement for the more recent ensemble mean, especially for temperature. The method is highly transferrable to a variety of further applications in climate science. Overall, there are regional differences of simulation quality, however, these are less pronounced than those between the results for 50-year mean and trend. The trend results are suitable for assigning weighting factors to climate models. Yet, the implications for probabilistic climate projections is strictly dependent on the region and season.

A model of regional primary production for use with coarse resolution satellite data

NASA Technical Reports Server (NTRS)

Prince, S. D.

1991-01-01

A model of crop primary production, which was originally developed to relate the amount of absorbed photosynthetically active radiation (APAR) to net production in field studies, is discussed in the context of coarse resolution regional remote sensing of primary production. The model depends on an approximately linear relationship between APAR and the normalized difference vegetation index. A more comprehensive form of the conventional model is shown to be necessary when different physiological types of plants or heterogeneous vegetation types occur within the study area. The predicted variable in the new model is total assimilation (net production plus respiration) rather than net production alone or harvest yield.

Patterns and Trends of Primary Production, Inorganic Carbon and Oxygen and Their Ecosystem Impacts in a Regional Biogeochemical Ocean Model for Atlantic Canada

NASA Astrophysics Data System (ADS)

Fennel, K.; Rutherford, K. E.; Kuhn, A. M.; Zhang, W.; Brennan, C. E.; Zhang, R.

2016-12-01

Representing coastal oceans in global biogeochemical models is a challenge, yet the ecosystems in these regions are most vulnerable to the combined stressors of ocean warming, deoxygenation, acidification, eutrophication and fishing. Coastal regions also have large air-sea fluxes of CO2, making them an important but poorly quantified component of the global carbon cycle, and are the most relevant for human activities. Regional model applications that are nested within large-scale or global models are necessary for detailed studies of coastal regions. We present results from such a regional biogeochemical model for the northwestern North Atlantic shelves and adjacent deep ocean of Atlantic Canada. The model is an implementation of the Regional Ocean Modeling System (ROMS) and includes an NPZD-type nitrogen cycle model with explicit representation of dissolved oxygen and inorganic carbon. The region is at the confluence of the Gulf Stream and Labrador Current making it highly dynamic, a challenge for analysis and prediction, and prone to large changes. Historically a rich fishing ground, coastal ecosystems in Atlantic Canada have undergone dramatic changes including the collapse of several economically important fish stocks and the listing of many species as threatened or endangered. Furthermore it is unclear whether the region is a net source or sink of atmospheric CO2 with estimates of the size and direction of the net air-sea CO2 flux remaining controversial. We will discuss simulated patterns of primary production, inorganic carbon fluxes and oxygen trends in the context of circulation features and shelf residence times for the present ocean state and present future projections.

Regional Climate Modeling and Remote Sensing to Characterize Impacts of Civil War Driven Land Use Change on Regional Hydrology and Climate

NASA Astrophysics Data System (ADS)

Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

2016-12-01

Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are extensive enough. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from an extended civil conflict in Mozambique. Civil war from 1977-1992 in Mozambique led to land use change at a regional scale as a result of the collapse of large herbivore populations due to poaching. Since the war ended, farming has increased, poaching was curtailed, and animal populations were reintroduced. In this study LULC in a region encompassing Gorongosa is classified at three instances between 1977 to 2015 using Landsat imagery. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from conflict-driven land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the civil war. Analysis of the Landsat data shows measurable land cover change from 1977-present as tree cover encroached into grasslands. Initial tests show corresponding sensitivities to different LULC schemes within the WRF model. Preliminary results suggest that the war did indeed impact regional hydroclimate in a significant way via its direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional conflicts are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus)

PubMed Central

Shafapour Tehrany, Mahyat; Solhjouy-fard, Samaneh; Kumar, Lalit

2018-01-01

Aedes albopictus, the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according to the prediction for 2055, for Ae. albopictus expansion. PMID:29576954

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus).

PubMed

Shabani, Farzin; Shafapour Tehrany, Mahyat; Solhjouy-Fard, Samaneh; Kumar, Lalit

2018-01-01

Aedes albopictus , the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus ? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according to the prediction for 2055, for Ae. albopictus expansion.

Biogeographical region and host trophic level determine carnivore endoparasite richness in the Iberian Peninsula.

PubMed

Rosalino, L M; Santos, M J; Fernandes, C; Santos-Reis, M

2011-05-01

We address the question of whether host and/or environmental factors might affect endoparasite richness and distribution, using carnivores as a model. We reviewed studies published in international peer-reviewed journals (34 areas in the Iberian Peninsula), describing parasite prevalence and richness in carnivores, and collected information on site location, host bio-ecology, climate and detected taxa (Helminths, Protozoa and Mycobacterium spp.). Three hypotheses were tested (i) host based, (ii) environmentally based, and (iii) hybrid (combination of environmental and host). Multicollinearity reduced candidate variable number for modelling to 5: host weight, phylogenetic independent contrasts (host weight), mean annual temperature, host trophic level and biogeographical region. General Linear Mixed Modelling was used and the best model was a hybrid model that included biogeographical region and host trophic level. Results revealed that endoparasite richness is higher in Mediterranean areas, especially for the top predators. We suggest that the detected parasites may benefit from mild environmental conditions that occur in southern regions. Top predators have larger home ranges and are likely to be subjected to cascading effects throughout the food web, resulting in more infestation opportunities and potentially higher endoparasite richness. This study suggests that richness may be more affected by historical and regional processes (including climate) than by host ecological processes.

Local soil effects on the Ground Motion Prediction model for the Racha region in Georgia

NASA Astrophysics Data System (ADS)

Jorjiashvili, N.; Shengelia, I.; Otinashvili, M.; Tvaliashvili, A.

2016-12-01

The Caucasus is a region of numerous natural hazards and ensuing disasters. Analysis of the losses due to past disasters indicates those most catastrophic in the region have historically been due to strong earthquakes. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is the peak ground acceleration because this parameter gives useful information for Seismic Hazard Assessment that was selected for the analysis. One of the most important topics that have a significant influence on earthquake records is the site ground conditions that are the main issue of the study because the same earthquake recorded at the same distance may cause different damage according to ground conditions. In the study earthquake records were selected for the Racha region in Georgia which has the highest seismic activity in the region. Next, new GMP models are obtained based on new digital data recorded in the same area. After removing the site effect the earthquake records on the rock site were obtained. Thus, two GMP models were obtained: one for the ground surface and the other for the rock site. At the end, comparison was done for the both models in order to analyze the influence of the local soil conditions on the GMP model.

Hybrid Rigid-Deformable Model for Prediction of Neighboring Intervertebral Disk Loads During Flexion Movement After Lumbar Interbody Fusion at L3-4 Level.

PubMed

Tuan Dao, Tien

2017-03-01

Knowledge of spinal loads in neighboring disks after interbody fusion plays an important role in the clinical decision of this treatment as well as in the elucidation of its effect. However, controversial findings are still noted in the literature. Moreover, there are no existing models for efficient prediction of intervertebral disk stresses within annulus fibrosus (AF) and nucleus pulposus (NP) regions. In this present study, a new hybrid rigid-deformable modeling workflow was established to quantify the mechanical stress behaviors within AF and NP regions of the L1-2, L2-3, and L4-5 disks after interbody fusion at L3-4 level. The changes in spinal loads were compared with results of the intact model without interbody fusion. The fusion outcomes revealed maximal stress changes (10%) in AF region of L1-2 disk and in NP region of L2-3 disk. The minimal stress change (1%) is noted at the NP region of the L1-2 disk. The validation of simulation outcomes of fused and intact lumbar spine models against those of other computational models and in vivo measurements showed good agreements. Thus, this present study may be used as a novel design guideline for a specific implant and surgical scenario of the lumbar spine disorders.

Reduced evoked fos expression in activity-related brain regions in animal models of behavioral depression.

PubMed

Stone, Eric A; Lehmann, Michael L; Lin, Yan; Quartermain, David

2007-08-15

A previous study showed that two mouse models of behavioral depression, immune system activation and depletion of brain monoamines, are accompanied by marked reductions in stimulated neural activity in brain regions involved in motivated behavior. The present study tested whether this effect is common to other depression models by examining the effects of repeated forced swimming, chronic subordination stress or acute intraventricular galanin injection - three additional models - on baseline or stimulated c-fos expression in several brain regions known to be involved in motor or motivational processes (secondary motor, M2, anterior piriform cortex, APIR, posterior cingulate gyrus, CG, nucleus accumbens, NAC). Each of the depression models was found to reduce the fos response stimulated by exposure to a novel cage or a swim stress in all four of these brain areas but not to affect the response of a stress-sensitive region (paraventricular hypothalamus, PVH) that was included for control purposes. Baseline fos expression in these structures was either unaffected or affected in an opposite direction to the stimulated response. Pretreatment with either desmethylimipramine (DMI) or tranylcypromine (tranyl) attenuated these changes. It is concluded that the pattern of a reduced neural function of CNS motor/motivational regions with an increased function of stress areas is common to 5 models of behavioral depression in the mouse and is a potential experimental analog of the neural activity changes occurring in the clinical condition.

Statistical bias correction method applied on CMIP5 datasets over the Indian region during the summer monsoon season for climate change applications

NASA Astrophysics Data System (ADS)

Prasanna, V.

2018-01-01

This study makes use of temperature and precipitation from CMIP5 climate model output for climate change application studies over the Indian region during the summer monsoon season (JJAS). Bias correction of temperature and precipitation from CMIP5 GCM simulation results with respect to observation is discussed in detail. The non-linear statistical bias correction is a suitable bias correction method for climate change data because it is simple and does not add up artificial uncertainties to the impact assessment of climate change scenarios for climate change application studies (agricultural production changes) in the future. The simple statistical bias correction uses observational constraints on the GCM baseline, and the projected results are scaled with respect to the changing magnitude in future scenarios, varying from one model to the other. Two types of bias correction techniques are shown here: (1) a simple bias correction using a percentile-based quantile-mapping algorithm and (2) a simple but improved bias correction method, a cumulative distribution function (CDF; Weibull distribution function)-based quantile-mapping algorithm. This study shows that the percentile-based quantile mapping method gives results similar to the CDF (Weibull)-based quantile mapping method, and both the methods are comparable. The bias correction is applied on temperature and precipitation variables for present climate and future projected data to make use of it in a simple statistical model to understand the future changes in crop production over the Indian region during the summer monsoon season. In total, 12 CMIP5 models are used for Historical (1901-2005), RCP4.5 (2005-2100), and RCP8.5 (2005-2100) scenarios. The climate index from each CMIP5 model and the observed agricultural yield index over the Indian region are used in a regression model to project the changes in the agricultural yield over India from RCP4.5 and RCP8.5 scenarios. The results revealed a better convergence of model projections in the bias corrected data compared to the uncorrected data. The study can be extended to localized regional domains aimed at understanding the changes in the agricultural productivity in the future with an agro-economy or a simple statistical model. The statistical model indicated that the total food grain yield is going to increase over the Indian region in the future, the increase in the total food grain yield is approximately 50 kg/ ha for the RCP4.5 scenario from 2001 until the end of 2100, and the increase in the total food grain yield is approximately 90 kg/ha for the RCP8.5 scenario from 2001 until the end of 2100. There are many studies using bias correction techniques, but this study applies the bias correction technique to future climate scenario data from CMIP5 models and applied it to crop statistics to find future crop yield changes over the Indian region.

One technique for refining the global Earth gravity models

NASA Astrophysics Data System (ADS)

Koneshov, V. N.; Nepoklonov, V. B.; Polovnev, O. V.

2017-01-01

The results of the theoretical and experimental research on the technique for refining the global Earth geopotential models such as EGM2008 in the continental regions are presented. The discussed technique is based on the high-resolution satellite data for the Earth's surface topography which enables the allowance for the fine structure of the Earth's gravitational field without the additional gravimetry data. The experimental studies are conducted by the example of the new GGMplus global gravity model of the Earth with a resolution about 0.5 km, which is obtained by expanding the EGM2008 model to degree 2190 with the corrections for the topograohy calculated from the SRTM data. The GGMplus and EGM2008 models are compared with the regional geoid models in 21 regions of North America, Australia, Africa, and Europe. The obtained estimates largely support the possibility of refining the global geopotential models such as EGM2008 by the procedure implemented in GGMplus, particularly in the regions with relatively high elevation difference.

A study of regional waveform calibration in the eastern Mediterranean

NASA Astrophysics Data System (ADS)

Di Luccio, F.; Pino, N. A.; Thio, H. K.

2003-06-01

We modeled P nl phases from several moderate magnitude earthquakes in the eastern Mediterranean to test methods and develop path calibrations for determining source parameters. The study region, which extends from the eastern part of the Hellenic arc to the eastern Anatolian fault, is dominated by moderate earthquakes that can produce significant damage. Our results are useful for analyzing regional seismicity as well as seismic hazard, because very few broadband seismic stations are available in the selected area. For the whole region we have obtained a single velocity model characterized by a 30 km thick crust, low upper mantle velocities and a very thin lid overlaying a distinct low velocity layer. Our preferred model proved quite reliable for determining focal mechanism and seismic moment across the entire range of selected paths. The source depth is also well constrained, especially for moderate earthquakes.

A climate model diagnostic metric for the Madden-Julian oscillation

NASA Astrophysics Data System (ADS)

Gonzalez, A. O.; Jiang, X.

2016-12-01

Despite its significant impacts on global weather and climate, the Madden-Julian oscillation (MJO) remains a grand challenge for state-of-the-art general circulation models (GCMs). The eastward propagation of the MJO is often poorly simulated in GCMs, represented by a stationary or even westward propagating mode. Recent analyses based on moist static energy processes suggest the horizontal advection of the winter mean moist static energy by the MJO circulation plays a critical role in the observed eastward propagation of the MJO. In this study, we explore relationships between model fidelity in representing the eastward propagation of the MJO and the winter mean lower-tropospheric moisture pattern by analyzing a suite of GCMs from a recent multi-model MJO comparison project. Model capability of reproducing the observed spatial pattern of the 650-900 hPa winter mean specific humidity is a robust indicator of how well they reproduce the MJO's eastward propagation. In particular, model skill in simulating the low-level winter mean specific humidity over the Maritime Continent region (20°S-20°N, 90°-135°E) is highly correlated with model skill of MJO propagation across the 23 GCMs analyzed, with a correlation of about 0.8. Winter mean lower-tropospheric moisture patterns over two other regions, including the western Indian Ocean and an off-equatorial region in the central Indian Ocean, also exhibit high correlations with MJO propagation skill in the model simulations. This study supports recent studies in highlighting the importance of the mean low-level moisture for MJO propagation and it points out a direction for model improvement of the MJO. Meanwhile, it is also suggested that the winter mean low-level moisture pattern over the Indo-Pacific region, particularly over the Maritime Continent region, can serve as a diagnostic metric for the eastward propagation of the MJO in climate model assessments.

Modeling motor connectivity using TMS/PET and structural equation modeling

PubMed Central

Laird, Angela R.; Robbins, Jacob M.; Li, Karl; Price, Larry R.; Cykowski, Matthew D.; Narayana, Shalini; Laird, Robert W.; Franklin, Crystal; Fox, Peter T.

2010-01-01

Structural equation modeling (SEM) was applied to positron emission tomographic (PET) images acquired during transcranial magnetic stimulation (TMS) of the primary motor cortex (M1hand). TMS was applied across a range of intensities, and responses both at the stimulation site and remotely connected brain regions covaried with stimulus intensity. Regions of interest (ROIs) were identified through an activation likelihood estimation (ALE) meta-analysis of TMS studies. That these ROIs represented the network engaged by motor planning and execution was confirmed by an ALE meta-analysis of finger movement studies. Rather than postulate connections in the form of an a priori model (confirmatory approach), effective connectivity models were developed using a model-generating strategy based on improving tentatively specified models. This strategy exploited the experimentally-imposed causal relations: (1) that response variations were caused by stimulation variations, (2) that stimulation was unidirectionally applied to the M1hand region, and (3) that remote effects must be caused, either directly or indirectly, by the M1hand excitation. The path model thus derived exhibited an exceptional level of goodness (χ2=22.150, df = 38, P = 0.981, TLI=1.0). The regions and connections derived were in good agreement with the known anatomy of the human and primate motor system. The model-generating SEM strategy thus proved highly effective and successfully identified a complex set of causal relationships of motor connectivity. PMID:18387823

Land Conversion in Amazonia and Northern South America; Influences on Regional Hydrology and Ecosystem Response

NASA Astrophysics Data System (ADS)

Knox, Ryan Gary

A numerical model of the terrestrial biosphere (Ecosystem Demography Model) is compbined with an atmospheric model (Brazilian Regional Atmospheric Modeling System) to investigate how land conversion in the Amazon and Northern South America have changed the hydrology of the region, and to see if those changes are significant enough to produce an ecological response. Two numerical realizations of the structure and composition of terrestrial vegetation are used as boundary conditions in a simulation of the regional land surface and atmosphere. One realization seeks to capture the present day vegetation condition that includes human deforestation and land-conversion, the other is an estimate of the potential structure and composition of the region without human influence. Model output is assessed for consistent and significant differences in hydrometeorology. Locations that show compelling differences are taken as case studies. The seasonal biases in precipitation at these locations are then used to create perturbations to long-term climate datasets. These perturbations then drive long-term simulations of dynamic vegetation to see if the climate consistent with a potential regional vegetation could elicit a change in the vegetation equilibrium at the site. Results show that South American land conversion has had consistent impacts on the regional patterning of precipitation. At some locations, changes in precipitation are persistent and constitute a significant fraction of total precipitation. Land-conversion has decreased mean continental evaporation and increased mean moisture convergence. Case study simulations of long term vegetation dynamic indicate that a hydrologic climate consistent with regional potential vegetation can indeed have significant influence on ecosystem structure and composition, particularly in water limited growth conditions. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs@mit.edu)

Empirical and model study on Travel-entering China

NASA Astrophysics Data System (ADS)

Han, Xue-Fang; Chen, Qi-Juan; Chang, Hui; He, Da-Ren

2006-03-01

We have done an empirical investigation on the travel-entering China from abroad to 31 regions of Chinese Mainland in recent ten years, including the development of the traveler's number, the traveler's number distribution for the traveler's home regions, the traveler's number distribution for the traveler's destination regions in Chinese mainland, and so on. We also suggest a dynamic model for simulating the competition between the 31 regions in the traveling market by considering two main influence factors, the attracting factor of the travel destinations and the distance between the destination and the home regions of the travelers. The simulation results show a good agreement with the empirical data. We expect the model could suggest some advice and thoughts to the travel-entering management departments in China and may be also for other countries.

Simulating Turbulent Wind Fields for Offshore Turbines in Hurricane-Prone Regions (Poster)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Y.; Damiani, R.; Musial, W.

Extreme wind load cases are one of the most important external conditions in the design of offshore wind turbines in hurricane prone regions. Furthermore, in these areas, the increase in load with storm return-period is higher than in extra-tropical regions. However, current standards have limited information on the appropriate models to simulate wind loads from hurricanes. This study investigates turbulent wind models for load analysis of offshore wind turbines subjected to hurricane conditions. Suggested extreme wind models in IEC 61400-3 and API/ABS (a widely-used standard in oil and gas industry) are investigated. The present study further examines the wind turbinemore » response subjected to Hurricane wind loads. Three-dimensional wind simulator, TurbSim, is modified to include the API wind model. Wind fields simulated using IEC and API wind models are used for an offshore wind turbine model established in FAST to calculate turbine loads and response.« less

Markov chain-incorporated and synthetic data-supported conditional artificial neural network models for forecasting monthly precipitation in arid regions

NASA Astrophysics Data System (ADS)

Aksoy, Hafzullah; Dahamsheh, Ahmad

2018-07-01

For forecasting monthly precipitation in an arid region, the feed forward back-propagation, radial basis function and generalized regression artificial neural networks (ANNs) are used in this study. The ANN models are improved after incorporation of a Markov chain-based algorithm (MC-ANNs) with which the percentage of dry months is forecasted perfectly, thus generation of any non-physical negative precipitation is eliminated. Due to the fact that recorded precipitation time series are usually shorter than the length needed for a proper calibration of ANN models, synthetic monthly precipitation data are generated by Thomas-Fiering model to further improve the performance of forecasting. For case studies from Jordan, it is seen that only a slightly better performance is achieved with the use of MC and synthetic data. A conditional statement is, therefore, established and imbedded into the ANN models after the incorporation of MC and support of synthetic data, to substantially improve the ability of the models for forecasting monthly precipitation in arid regions.

A Regional Climate Model Evaluation System based on Satellite and other Observations

NASA Astrophysics Data System (ADS)

Lean, P.; Kim, J.; Waliser, D. E.; Hall, A. D.; Mattmann, C. A.; Granger, S. L.; Case, K.; Goodale, C.; Hart, A.; Zimdars, P.; Guan, B.; Molotch, N. P.; Kaki, S.

2010-12-01

Regional climate models are a fundamental tool needed for downscaling global climate simulations and projections, such as those contributing to the Coupled Model Intercomparison Projects (CMIPs) that form the basis of the IPCC Assessment Reports. The regional modeling process provides the means to accommodate higher resolution and a greater complexity of Earth System processes. Evaluation of both the global and regional climate models against observations is essential to identify model weaknesses and to direct future model development efforts focused on reducing the uncertainty associated with climate projections. However, the lack of reliable observational data and the lack of formal tools are among the serious limitations to addressing these objectives. Recent satellite observations are particularly useful as they provide a wealth of information on many different aspects of the climate system, but due to their large volume and the difficulties associated with accessing and using the data, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL / UCLA is developing a model evaluation system to help make satellite observations, in conjunction with in-situ, assimilated, and reanalysis datasets, more readily accessible to the modeling community. The system includes a central database to store multiple datasets in a common format and codes for calculating predefined statistical metrics to assess model performance. This allows the time taken to compare model simulations with satellite observations to be reduced from weeks to days. Early results from the use this new model evaluation system for evaluating regional climate simulations over California/western US regions will be presented.

Advances in Applications of Hierarchical Bayesian Methods with Hydrological Models

NASA Astrophysics Data System (ADS)

Alexander, R. B.; Schwarz, G. E.; Boyer, E. W.

2017-12-01

Mechanistic and empirical watershed models are increasingly used to inform water resource decisions. Growing access to historical stream measurements and data from in-situ sensor technologies has increased the need for improved techniques for coupling models with hydrological measurements. Techniques that account for the intrinsic uncertainties of both models and measurements are especially needed. Hierarchical Bayesian methods provide an efficient modeling tool for quantifying model and prediction uncertainties, including those associated with measurements. Hierarchical methods can also be used to explore spatial and temporal variations in model parameters and uncertainties that are informed by hydrological measurements. We used hierarchical Bayesian methods to develop a hybrid (statistical-mechanistic) SPARROW (SPAtially Referenced Regression On Watershed attributes) model of long-term mean annual streamflow across diverse environmental and climatic drainages in 18 U.S. hydrological regions. Our application illustrates the use of a new generation of Bayesian methods that offer more advanced computational efficiencies than the prior generation. Evaluations of the effects of hierarchical (regional) variations in model coefficients and uncertainties on model accuracy indicates improved prediction accuracies (median of 10-50%) but primarily in humid eastern regions, where model uncertainties are one-third of those in arid western regions. Generally moderate regional variability is observed for most hierarchical coefficients. Accounting for measurement and structural uncertainties, using hierarchical state-space techniques, revealed the effects of spatially-heterogeneous, latent hydrological processes in the "localized" drainages between calibration sites; this improved model precision, with only minor changes in regional coefficients. Our study can inform advances in the use of hierarchical methods with hydrological models to improve their integration with stream measurements.

An optimized data fusion method and its application to improve lateral boundary conditions in winter for Pearl River Delta regional PM2.5 modeling, China

NASA Astrophysics Data System (ADS)

Huang, Zhijiong; Hu, Yongtao; Zheng, Junyu; Zhai, Xinxin; Huang, Ran

2018-05-01

Lateral boundary conditions (LBCs) are essential for chemical transport models to simulate regional transport; however they often contain large uncertainties. This study proposes an optimized data fusion approach to reduce the bias of LBCs by fusing gridded model outputs, from which the daughter domain's LBCs are derived, with ground-level measurements. The optimized data fusion approach follows the framework of a previous interpolation-based fusion method but improves it by using a bias kriging method to correct the spatial bias in gridded model outputs. Cross-validation shows that the optimized approach better estimates fused fields in areas with a large number of observations compared to the previous interpolation-based method. The optimized approach was applied to correct LBCs of PM2.5 concentrations for simulations in the Pearl River Delta (PRD) region as a case study. Evaluations show that the LBCs corrected by data fusion improve in-domain PM2.5 simulations in terms of the magnitude and temporal variance. Correlation increases by 0.13-0.18 and fractional bias (FB) decreases by approximately 3%-15%. This study demonstrates the feasibility of applying data fusion to improve regional air quality modeling.

Tsunami Hazard Assessment: Source regions of concern to U.S. interests derived from NOAA Tsunami Forecast Model Development

NASA Astrophysics Data System (ADS)

Eble, M. C.; uslu, B. U.; Wright, L.

2013-12-01

Synthetic tsunamis generated from source regions around the Pacific Basin are analyzed in terms of their relative impact on United States coastal locations.. The region of tsunami origin is as important as the expected magnitude and the predicted inundation for understanding tsunami hazard. The NOAA Center for Tsunami Research has developed high-resolution tsunami models capable of predicting tsunami arrival time and amplitude of waves at each location. These models have been used to conduct tsunami hazard assessments to assess maximum impact and tsunami inundation for use by local communities in education and evacuation map development. Hazard assessment studies conducted for Los Angeles, San Francisco, Crescent City, Hilo, and Apra Harbor are combined with results of tsunami forecast model development at each of seventy-five locations. Complete hazard assessment, identifies every possible tsunami variation from a pre-computed propagation database. Study results indicate that the Eastern Aleutian Islands and Alaska are the most likely regions to produce the largest impact on the West Coast of the United States, while the East Philippines and Mariana trench regions impact Apra Harbor, Guam. Hawaii appears to be impacted equally from South America, Alaska and the Kuril Islands.

Data integrity systems for organ contours in radiation therapy planning.

PubMed

Shah, Veeraj P; Lakshminarayanan, Pranav; Moore, Joseph; Tran, Phuoc T; Quon, Harry; Deville, Curtiland; McNutt, Todd R

2018-06-12

The purpose of this research is to develop effective data integrity models for contoured anatomy in a radiotherapy workflow for both real-time and retrospective analysis. Within this study, two classes of contour integrity models were developed: data driven models and contiguousness models. The data driven models aim to highlight contours which deviate from a gross set of contours from similar disease sites and encompass the following regions of interest (ROI): bladder, femoral heads, spinal cord, and rectum. The contiguousness models, which individually analyze the geometry of contours to detect possible errors, are applied across many different ROI's and are divided into two metrics: Extent and Region Growing over volume. After analysis, we found that 70% of detected bladder contours were verified as suspicious. The spinal cord and rectum models verified that 73% and 80% of contours were suspicious respectively. The contiguousness models were the most accurate models and the Region Growing model was the most accurate submodel. 100% of the detected noncontiguous contours were verified as suspicious, but in the cases of spinal cord, femoral heads, bladder, and rectum, the Region Growing model detected additional two to five suspicious contours that the Extent model failed to detect. When conducting a blind review to detect false negatives, it was found that all the data driven models failed to detect all suspicious contours. The Region Growing contiguousness model produced zero false negatives in all regions of interest other than prostate. With regards to runtime, the contiguousness via extent model took an average of 0.2 s per contour. On the other hand, the region growing method had a longer runtime which was dependent on the number of voxels in the contour. Both contiguousness models have potential for real-time use in clinical radiotherapy while the data driven models are better suited for retrospective use. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

WRF/CMAQ AQMEII3 Simulations of U.S. Regional-Scale Ozone: Sensitivity to Processes and Inputs

EPA Science Inventory

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, performed during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), we perform annual simulations over North America with chemical boundary con...

Methods for reducing biases and errors in regional photochemical model outputs for use in emission reduction and exposure assessments

EPA Science Inventory

In the United States, regional-scale photochemical models are being used to design emission control strategies needed to meet the relevant National Ambient Air Quality Standards (NAAQS) within the framework of the attainment demonstration process. Previous studies have shown that...

Modeling Soil Organic Carbon in a Semiarid Region of Kazakhstan Using EPIC

USDA-ARS?s Scientific Manuscript database

Inappropriate land use and soil mismanagement produced wide-scale soil and environmental degradation to the short-grass steppe ecosystem in the semiarid region of Kazakhstan. We used the Environmental Policy Integrated Climate (EPIC) model to study long-term impacts of land use changes and soil mana...

THE OHIO RIVER BASIN ENERGY FACILITY SITING MODEL. VOLUME II: SITES AND ON-LINE DATES

EPA Science Inventory

The report was prepared as part of the Ohio River Basin Energy Study (ORBES), a multidisciplinary policy research program. The siting model developed for ORBES is specifically designed for regional policy analysis. The region includes 423 counties in an area that consists of all ...

Influence of Boundary Conditions on Regional Air Quality Simulations—Analysis of AQMEII Phase 3 Results

EPA Science Inventory

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, performed during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), we perform annual simulations over North America with chemical boundary con...

Use of NARCCAP data to characterize regional climate uncertainty in the impact of global climate change on large river fish population: Missouri River sturgeon example

NASA Astrophysics Data System (ADS)

Anderson, C. J.; Wildhaber, M. L.; Wikle, C. K.; Moran, E. H.; Franz, K. J.; Dey, R.

2012-12-01

Climate change operates over a broad range of spatial and temporal scales. Understanding the effects of change on ecosystems requires accounting for the propagation of information and uncertainty across these scales. For example, to understand potential climate change effects on fish populations in riverine ecosystems, climate conditions predicted by course-resolution atmosphere-ocean global climate models must first be translated to the regional climate scale. In turn, this regional information is used to force watershed models, which are used to force river condition models, which impact the population response. A critical challenge in such a multiscale modeling environment is to quantify sources of uncertainty given the highly nonlinear nature of interactions between climate variables and the individual organism. We use a hierarchical modeling approach for accommodating uncertainty in multiscale ecological impact studies. This framework allows for uncertainty due to system models, model parameter settings, and stochastic parameterizations. This approach is a hybrid between physical (deterministic) downscaling and statistical downscaling, recognizing that there is uncertainty in both. We use NARCCAP data to determine confidence the capability of climate models to simulate relevant processes and to quantify regional climate variability within the context of the hierarchical model of uncertainty quantification. By confidence, we mean the ability of the regional climate model to replicate observed mechanisms. We use the NCEP-driven simulations for this analysis. This provides a base from which regional change can be categorized as either a modification of previously observed mechanisms or emergence of new processes. The management implications for these categories of change are significantly different in that procedures to address impacts from existing processes may already be known and need adjustment; whereas, an emergent processes may require new management strategies. The results from hierarchical analysis of uncertainty are used to study the relative change in weights of the endangered Missouri River pallid sturgeon (Scaphirhynchus albus) under a 21st century climate scenario.

Cage Regional Energy Budgets from the GLAS 4TH Order Model

NASA Technical Reports Server (NTRS)

Herman, G. F.; Alexder, M. A.; Shubert, S. D.

1984-01-01

The status and future plans of a study to (1) assess the accuracy of regional energy balance calculations obtained from the 4th-order model, (2) determine the impact of satellite data on the calculations, and (3) determine their utility for ocean energy transport studies are discussed. An equation is presented which models the vertically-integrated, time and areally-averaged total energy content of a region of the atmosphere extending from the surface to the top of the atmosphere. All of the terms of the equation were evaluated using early versions of the GLAS FGGE IIIb analysis, and analysis with satellite data deleted. Results show that the budget is dominated by the surface fluxes, net radiation, and horizontal atmospoheric divergence.

NASA Experimental Program to Stimulate Competitive Research: South Carolina

NASA Technical Reports Server (NTRS)

Sutton, Michael A.

2004-01-01

The use of an appropriate relationship model is critical for reliable prediction of future urban growth. Identification of proper variables and mathematic functions and determination of the weights or coefficients are the key tasks for building such a model. Although the conventional logistic regression model is appropriate for handing land use problems, it appears insufficient to address the issue of interdependency of the predictor variables. This study used an alternative approach to simulation and modeling urban growth using artificial neural networks. It developed an operational neural network model trained using a robust backpropagation method. The model was applied in the Myrtle Beach region of South Carolina, and tested with both global datasets and areal datasets to examine the strength of both regional models and areal models. The results indicate that the neural network model not only has many theoretic advantages over other conventional mathematic models in representing the complex urban systems, but also is practically superior to the logistic model in its capability to predict urban growth with better - accuracy and less variation. The neural network model is particularly effective in terms of successfully identifying urban patterns in the rural areas where the logistic model often falls short. It was also found from the area-based tests that there are significant intra-regional differentiations in urban growth with different rules and rates. This suggests that the global modeling approach, or one model for the entire region, may not be adequate for simulation of a urban growth at the regional scale. Future research should develop methods for identification and subdivision of these areas and use a set of area-based models to address the issues of multi-centered, intra- regionally differentiated urban growth.

Emission-line diagnostics of nearby H II regions including interacting binary populations

NASA Astrophysics Data System (ADS)

Xiao, Lin; Stanway, Elizabeth R.; Eldridge, J. J.

2018-06-01

We present numerical models of the nebular emission from H II regions around young stellar populations over a range of compositions and ages. The synthetic stellar populations include both single stars and interacting binary stars. We compare these models to the observed emission lines of 254 H II regions of 13 nearby spiral galaxies and 21 dwarf galaxies drawn from archival data. The models are created using the combination of the BPASS (Binary Population and Spectral Synthesis) code with the photoionization code CLOUDY to study the differences caused by the inclusion of interacting binary stars in the stellar population. We obtain agreement with the observed emission line ratios from the nearby star-forming regions and discuss the effect of binary-star evolution pathways on the nebular ionization of H II regions. We find that at population ages above 10 Myr, single-star models rapidly decrease in flux and ionization strength, while binary-star models still produce strong flux and high [O III]/H β ratios. Our models can reproduce the metallicity of H II regions from spiral galaxies, but we find higher metallicities than previously estimated for the H II regions from dwarf galaxies. Comparing the equivalent width of H β emission between models and observations, we find that accounting for ionizing photon leakage can affect age estimates for H II regions. When it is included, the typical age derived for H II regions is 5 Myr from single-star models, and up to 10 Myr with binary-star models. This is due to the existence of binary-star evolution pathways, which produce more hot Wolf-Rayet and helium stars at older ages. For future reference, we calculate new BPASS binary maximal starburst lines as a function of metallicity, and for the total model population, and present these in Appendix A.

Offshore Wind Jobs and Economic Development Impacts in the United States: Four Regional Scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tegen, S.; Keyser, D.; Flores-Espino, F.

This report uses the offshore wind Jobs and Economic Development Impacts (JEDI) model and provides four case studies of potential offshore deployment scenarios in different regions of the United States: the Southeast, the Great Lakes, the Gulf Coast, and the Mid-Atlantic. Researchers worked with developers and industry representatives in each region to create potential offshore wind deployment and supply chain growth scenarios, specific to their locations. These scenarios were used as inputs into the offshore JEDI model to estimate jobs and other gross economic impacts in each region.

Recent Progress in Measuring and Modeling Patterns of Biomass and Soil Carbon Pools Across the Amazon Basin

NASA Technical Reports Server (NTRS)

Potter, Christopher; Malhi, Yadvinder

2004-01-01

Ever more detailed representations of above-ground biomass and soil carbon pools have been developed during the LBA project. Environmental controls such as regional climate, land cover history, secondary forest regrowth, and soil fertility are now being taken into account in regional inventory studies. This paper will review the evolution of measurement-extrapolation approaches, remote sensing, and simulation modeling techniques for biomass and soil carbon pools, which together help constrain regional carbon budgets and enhance in our understanding of uncertainty at the regional level.

Relationship between Pulmonary Airflow and Resistance in Patients with Airway Narrowing Using An 1-D Network Resistance and Compliance Model

NASA Astrophysics Data System (ADS)

Choi, Sanghun; Choi, Jiwoong; Hoffman, Eric; Lin, Ching-Long

2016-11-01

To predict the proper relationship between airway resistance and regional airflow, we proposed a novel 1-D network model for airway resistance and acinar compliance. First, we extracted 1-D skeletons at inspiration images, and generated 1-D trees of CT unresolved airways with a volume filling method. We used Horsfield order with random heterogeneity to create diameters of the generated 1-D trees. We employed a resistance model that accounts for kinetic energy and viscous dissipation (Model A). The resistance model is further coupled with a regional compliance model estimated from two static images (Model B). For validation, we applied both models to a healthy subject. The results showed that Model A failed to provide airflows consistent with air volume change, whereas Model B provided airflows consistent with air volume change. Since airflows shall be regionally consistent with air volume change in patients with normal airways, Model B was validated. Then, we applied Model B to severe asthmatic subjects. The results showed that regional airflows were significantly deviated from air volume change due to airway narrowing. This implies that airway resistance plays a major role in determining regional airflows of patients with airway narrowing. Support for this study was provided, in part, by NIH Grants U01 HL114494, R01 HL094315, R01 HL112986, and S10 RR022421.

Defining Scenarios: Linking Integrated Models, Regional Concerns, and Stakeholders

NASA Astrophysics Data System (ADS)

Hartmann, H. C.; Stewart, S.; Liu, Y.; Mahmoud, M.

2007-05-01

Scenarios are important tools for long-term planning, and there is great interest in using integrated models in scenario studies. However, scenario definition and assessment are creative, as well as scientific, efforts. Using facilitated creative processes, we have worked with stakeholders to define regionally significant scenarios that encompass a broad range of hydroclimatic, socioeconomic, and institutional dimensions. The regional scenarios subsequently inform the definition of local scenarios that work with context-specific integrated models that, individually, can address only a subset of overall regional complexity. Based on concerns of stakeholders in the semi-arid US Southwest, we prioritized three dimensions that are especially important, yet highly uncertain, for long-term planning: hydroclimatic conditions (increased variability, persistent drought), development patterns (urban consolidation, distributed rural development), and the nature of public institutions (stressed, proactive). Linking across real-world decision contexts and integrated modeling efforts poses challenges of creatively connecting the conceptual models held by both the research and stakeholder communities.

Effects of Sediment Loading in Northern Europe During the Last Glacial

NASA Astrophysics Data System (ADS)

van der Wal, W.; IJpelaar, M.

2014-12-01

Over the years the framework of GIA modelling has been subject to continuous improvements, e.g. the addition of time dependent coastal margins and rotational feedback. The latest addition to this framework is the incorporation of sediment as a time-varying surface load while accounting for sea-level variations associated with the sediment transport (Dalca et al., GJI 2013). The effects of sediment loading during a glacial cycle have not been extensively investigated even though it is known that large sediment transport took place, for example in the Barents Sea region and Fennoscandia. This study investigates the effect of sediment transport on relative sea level change and present-day rates of gravity and vertical deformation in those regions. While the ice sheet history during the last glacial period has been modelled extensively there are no full-scale models of paleo-erosion and -deposition rates for regions such as Fennoscandia. Here we create end-member paleo-sedimentary models by combining geological observations of continuous erosion and deposition and large scale failure events. These models, in combination with the ICE-5G ice sheet history, serve as an input for a GIA model for a spherically symmetric incompressible Earth with the full sea-level equation. The results from this model, i.e. (rates of) relative sea level change and crustal deformation, are obtained for different viscosity models fitting best with the local rheology of Fennoscandia. By comparing GPS measurements, GRACE observations and relative sea level records with these modelled predictions the effects of sedimentary isostasy in the Fennoscandian region are studied. The sediment load does not significantly affect the modelled relative sea level curves, nor vertical deformation rates at the location of GPS measurements. However, gravity rates over the Barents Sea region are influenced significantly

Consistent earthquake catalog derived from changing network configurations: Application to the Rawil Depression in the southwestern Helvetic Alps

NASA Astrophysics Data System (ADS)

Lee, Timothy; Diehl, Tobias; Kissling, Edi; Wiemer, Stefan

2017-04-01

Earthquake catalogs derived from several decades of observations are often biased by network geometries, location procedures, and data quality changing with time. To study the long-term spatio-temporal behavior of seismogenic fault zones at high-resolution, a consistent homogenization and improvement of earthquake catalogs is required. Assuming that data quality and network density generally improves with time, procedures are needed, which use the best available data to homogeneously solve the coupled hypocenter - velocity structure problem and can be as well applied to earlier network configurations in the same region. A common approach to uniformly relocate earthquake catalogs is the calculation of a so-called "minimum 1D" model, which is derived from the simultaneous inversion for hypocenters and 1D velocity structure, including station specific delay-time corrections. In this work, we will present strategies using the principles of the "minimum 1D" model to consistently relocate hypocenters recorded by the Swiss Seismological Service (SED) in the Swiss Alps over a period of 17 years in a region, which is characterized by significant changes in network configurations. The target region of this study is the Rawil depression, which is located between the Aar and Mont Blanc massifs in southwestern Switzerland. The Rhone-Simplon Fault is located to the south of the Rawil depression and is considered as a dextral strike-slip fault representing the dominant tectonic boundary between Helvetic nappes to the north and Penninic nappes to the south. Current strike-slip earthquakes, however, occur predominantly in a narrow, east-west striking cluster located in the Rawil depression north of the Rhone-Simplon Fault. Recent earthquake swarms near Sion and Sierre in 2011 and 2016, on the other hand, indicate seismically active dextral faults close to the Rhone valley. The region north and south of the Rhone-Simplon Fault is one of the most seismically active regions in Switzerland and therefore a prime target to study the mechanics of active fault zones in the Swiss Alps. In the presented study, existing travel-time data from the SED bulletin from the entire instrumental era (1984-today) are used to calculate a "minimum 1D" model for the region. The dataset is complemented by data of three broadband stations, recently installed to further densify the seismic network of the SED in the Rawil area. The new model is compared to previous local and regional 1D and 3D models. The derived model is used for systematic relocation of the seismicity in the Rawil region and will be used as reference model for high-resolution 3D models imaging the velocity structure of the Rawil fault zone in a next step. The presented procedure is of relevance for similar studies planned in other regions of the Alps, which have been densified by AlpArray stations.

Using a composite grid approach in a complex coastal domain to estimate estuarine residence time

USGS Publications Warehouse

Warner, John C.; Geyer, W. Rockwell; Arango, Herman G.

2010-01-01

We investigate the processes that influence residence time in a partially mixed estuary using a three-dimensional circulation model. The complex geometry of the study region is not optimal for a structured grid model and so we developed a new method of grid connectivity. This involves a novel approach that allows an unlimited number of individual grids to be combined in an efficient manner to produce a composite grid. We then implemented this new method into the numerical Regional Ocean Modeling System (ROMS) and developed a composite grid of the Hudson River estuary region to investigate the residence time of a passive tracer. Results show that the residence time is a strong function of the time of release (spring vs. neap tide), the along-channel location, and the initial vertical placement. During neap tides there is a maximum in residence time near the bottom of the estuary at the mid-salt intrusion length. During spring tides the residence time is primarily a function of along-channel location and does not exhibit a strong vertical variability. This model study of residence time illustrates the utility of the grid connectivity method for circulation and dispersion studies in regions of complex geometry.

Regional modeling of wind erosion in the North West and South West of Iran

NASA Astrophysics Data System (ADS)

Mirmousavi, S. H.

2016-08-01

About two-thirds of the Iran's area is located in the arid and semiarid region. Lack of soil moisture and vegetation is poor in most areas can lead to soil erosion caused by wind. So that the annual suffered severe damage to large areas of rich soils. Modeling studies of wind erosion in Iran is very low and incomplete. Therefore, this study aimed to wind erosion modeling, taking into three factors: wind speed, vegetation and soil types have been done. Wind erosion sensitivity was modeled using the key factors of soil sensitivity, vegetation cover and wind erodibility as proxies. These factors were first estimated separately by factor sensitivity maps and later combined by fuzzy logic into a regional-scale wind erosion sensitivity map. Large areas were evaluated by using publicly available datasets of remotely sensed vegetation information, soil maps and meteorological data on wind speed. The resulting estimates were verified by field studies and examining the economic losses from wind erosion as compensated by the state insurance company. The spatial resolution of the resulting sensitivity map is suitable for regional applications, as identifying sensitive areas is the foundation for diverse land development control measures and implementing management activities.

Regional and Global Climate Response to Anthropogenic SO2 Emissions from China in Three Climate Models

NASA Technical Reports Server (NTRS)

Kasoar, M.; Voulgarakis, Apostolos; Lamarque, Jean-Francois; Shindell, Drew T.; Bellouin, Nicholas; Collins, William J.; Faluvegi, Greg; Tsigaridis, Kostas

2016-01-01

We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions from China. We find that the models differ by up to a factor of 6 in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating that total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against observations.

On the appropriate definition of soil profile configuration and initial conditions for land surface-hydrology models in cold regions

NASA Astrophysics Data System (ADS)

Sapriza-Azuri, Gonzalo; Gamazo, Pablo; Razavi, Saman; Wheater, Howard S.

2018-06-01

Arctic and subarctic regions are amongst the most susceptible regions on Earth to global warming and climate change. Understanding and predicting the impact of climate change in these regions require a proper process representation of the interactions between climate, carbon cycle, and hydrology in Earth system models. This study focuses on land surface models (LSMs) that represent the lower boundary condition of general circulation models (GCMs) and regional climate models (RCMs), which simulate climate change evolution at the global and regional scales, respectively. LSMs typically utilize a standard soil configuration with a depth of no more than 4 m, whereas for cold, permafrost regions, field experiments show that attention to deep soil profiles is needed to understand and close the water and energy balances, which are tightly coupled through the phase change. To address this gap, we design and run a series of model experiments with a one-dimensional LSM, called CLASS (Canadian Land Surface Scheme), as embedded in the MESH (Modélisation Environmentale Communautaire - Surface and Hydrology) modelling system, to (1) characterize the effect of soil profile depth under different climate conditions and in the presence of parameter uncertainty; (2) assess the effect of including or excluding the geothermal flux in the LSM at the bottom of the soil column; and (3) develop a methodology for temperature profile initialization in permafrost regions, where the system has an extended memory, by the use of paleo-records and bootstrapping. Our study area is in Norman Wells, Northwest Territories of Canada, where measurements of soil temperature profiles and historical reconstructed climate data are available. Our results demonstrate a dominant role for parameter uncertainty, that is often neglected in LSMs. Considering such high sensitivity to parameter values and dependency on the climate condition, we show that a minimum depth of 20 m is essential to adequately represent the temperature dynamics. We further show that our proposed initialization procedure is effective and robust to uncertainty in paleo-climate reconstructions and that more than 300 years of reconstructed climate time series are needed for proper model initialization.

Effect of LES models on the entrainment of a passive scalar in a turbulent planar jet

NASA Astrophysics Data System (ADS)

Chambel Lopes, Diogo; da Silva, Carlos; Reis, Ricardo; Raman, Venkat

2011-11-01

Direct and large-eddy simulations (DNS/LES) of turbulent planar jets are used to study the role of subgrid-scale models in the integral characteristics of the passive scalar mixing in a jet. Specifically the effect of subgrid-scale models in the jet spreading rate and centreline passive scalar decay rates are assessed and compared. The modelling of the subgrid-scale fluxes is particularly challenging in the turbulent/nonturbulent (T/NT) region that divides the two regions in the jet flow: the outer region where the flow is irrotational and the inner region where the flow is turbulent. It has been shown that important Reynolds stresses exist near the T/NT interface and that these stresses determine in part the mixing and combustion rates in jets. The subgrid scales of motion near the T/NT interface are far from equilibrium and contain an important fraction of the total kinetic energy. Model constants used in several subgrid-scale models such as the Smagorinsky and the gradient models need to be corrected near the jet edge. The procedure used to obtain the dynamic Smagorinsky constant is not able to cope with the intermittent nature of this region.

Investigation of error sources in regional inverse estimates of greenhouse gas emissions in Canada

NASA Astrophysics Data System (ADS)

Chan, E.; Chan, D.; Ishizawa, M.; Vogel, F.; Brioude, J.; Delcloo, A.; Wu, Y.; Jin, B.

2015-08-01

Inversion models can use atmospheric concentration measurements to estimate surface fluxes. This study is an evaluation of the errors in a regional flux inversion model for different provinces of Canada, Alberta (AB), Saskatchewan (SK) and Ontario (ON). Using CarbonTracker model results as the target, the synthetic data experiment analyses examined the impacts of the errors from the Bayesian optimisation method, prior flux distribution and the atmospheric transport model, as well as their interactions. The scaling factors for different sub-regions were estimated by the Markov chain Monte Carlo (MCMC) simulation and cost function minimization (CFM) methods. The CFM method results are sensitive to the relative size of the assumed model-observation mismatch and prior flux error variances. Experiment results show that the estimation error increases with the number of sub-regions using the CFM method. For the region definitions that lead to realistic flux estimates, the numbers of sub-regions for the western region of AB/SK combined and the eastern region of ON are 11 and 4 respectively. The corresponding annual flux estimation errors for the western and eastern regions using the MCMC (CFM) method are -7 and -3 % (0 and 8 %) respectively, when there is only prior flux error. The estimation errors increase to 36 and 94 % (40 and 232 %) resulting from transport model error alone. When prior and transport model errors co-exist in the inversions, the estimation errors become 5 and 85 % (29 and 201 %). This result indicates that estimation errors are dominated by the transport model error and can in fact cancel each other and propagate to the flux estimates non-linearly. In addition, it is possible for the posterior flux estimates having larger differences than the prior compared to the target fluxes, and the posterior uncertainty estimates could be unrealistically small that do not cover the target. The systematic evaluation of the different components of the inversion model can help in the understanding of the posterior estimates and percentage errors. Stable and realistic sub-regional and monthly flux estimates for western region of AB/SK can be obtained, but not for the eastern region of ON. This indicates that it is likely a real observation-based inversion for the annual provincial emissions will work for the western region whereas; improvements are needed with the current inversion setup before real inversion is performed for the eastern region.

[Potentials in the regionalization of health indicators using small-area estimation methods : Exemplary results based on the 2009, 2010 and 2012 GEDA studies].

PubMed

Kroll, Lars Eric; Schumann, Maria; Müters, Stephan; Lampert, Thomas

2017-12-01

Nationwide health surveys can be used to estimate regional differences in health. Using traditional estimation techniques, the spatial depth for these estimates is limited due to the constrained sample size. So far - without special refreshment samples - results have only been available for larger populated federal states of Germany. An alternative is regression-based small-area estimation techniques. These models can generate smaller-scale data, but are also subject to greater statistical uncertainties because of the model assumptions. In the present article, exemplary regionalized results based on the studies "Gesundheit in Deutschland aktuell" (GEDA studies) 2009, 2010 and 2012, are compared to the self-rated health status of the respondents. The aim of the article is to analyze the range of regional estimates in order to assess the usefulness of the techniques for health reporting more adequately. The results show that the estimated prevalence is relatively stable when using different samples. Important determinants of the variation of the estimates are the achieved sample size on the district level and the type of the district (cities vs. rural regions). Overall, the present study shows that small-area modeling of prevalence is associated with additional uncertainties compared to conventional estimates, which should be taken into account when interpreting the corresponding findings.

Hybridized Kibble-Zurek scaling in the driven critical dynamics across an overlapping critical region

NASA Astrophysics Data System (ADS)

Zhai, Liang-Jun; Wang, Huai-Yu; Yin, Shuai

2018-04-01

The conventional Kibble-Zurek scaling describes the scaling behavior in the driven dynamics across a single critical region. In this paper, we study the driven dynamics across an overlapping critical region, in which a critical region (Region A) is overlaid by another critical region (Region B). We develop a hybridized Kibble-Zurek scaling (HKZS) to characterize the scaling behavior in the driven process. According to the HKZS, the driven dynamics in the overlapping region can be described by the critical theories for both Region A and Region B simultaneously. This results in a constraint on the scaling function in the overlapping critical region. We take the quantum Ising chain in an imaginary longitudinal field as an example. In this model, the critical region of the Yang-Lee edge singularity and the critical region of the ferromagnetic-paramagnetic phase transition overlap with each other. We numerically confirm the HKZS by simulating the driven dynamics in this overlapping critical region. The HKZSs in other models are also discussed.

Simulation of Relationship between ENSO and winter precipitation over Western Himalayas: Application of Regional climate model (RegT-Band)

NASA Astrophysics Data System (ADS)

Tiwari, P. R.; Mohanty, U. C.; Dey, S.; Acharaya, N.; Sinha, P.

2012-12-01

Precipitation over the Western Himalayas region during winter is mainly associated with the passage of midlatitude synoptic systems known as western disturbances (WDs). Recently, many observational and modeling studies reported that the relationship of the Indian southwest monsoon rainfall with El Niño- Southern Oscillation (ENSO) has weakened since around 1980. But, in contrast, only very few observational studies are reported so far to examine the relationship between ENSO and the winter precipitation over the Western Himalayas region from December to February (DJF). But there is a huge gap of modeling this phenomenon. So keeping in view of the absence of modeling studies, an attempt is made to simulate the relationship between wintertime precipitations associated with large scale global forcing of ENSO over the Western Himalayas. In the present study, RegT-Band, a tropical band version of the regional climate model RegCM4 is integrated for a set of 5 El Niño (1986-87, 1991-92, 1997-98, 2002-03, 2009-10) and 4 La Niña (1984-85, 1988-89, 1999-2000, 2007-08) years with the observed sea-surface temperature and lateral boundary condition. The domain extends from 50° S to 50° N and covers the entire tropics at a grid spacing of about 45 km, i.e. it includes lateral boundary forcing only at the southern and northern boundaries. The performance evaluation of the model in capturing the large scale fields followed by ENSO response with wintertime precipitation over the Western Himalayas region has been carried out by using National Center for Environmental Prediction (NCEP)-Department of Energy (DOE) reanalysis 2 (NNRP2) data (2.5° x 2.5°) and Aphrodite precipitation data (0.25° x 0.25°). The model is able to delineate the mean circulation associated with ENSO over the region during DJF reasonably well and shows strong southwesterly to northwesterly wind flow, which is there in verification analysis also. The vertical structure of the low as well as upper level air circulation for the ENSO regimes has been also studied. For this purpose, a longitudional cross-section of the seasonal sectorial mean of the zonal and meridional winds is analyzed form NNRP2 and RegT-Band model simulations. The model simulated zonal wind is in good agreement with verification analysis however core speed of subtropical Westerly Jet Stream in upper level (around 150 hPa) is overestimated by the model. Further, the sectorial cross section of meridional wind indicates that the wind around 200 hPa is stronger during ENSO years, and this feature is emphasized well in the model simulation. So the upper and lower level sartorial components of wind supports the argument of strengthening of circulation associated with ENSO, and hence enhanced precipitation during ENSO-winter precipitation relationship. So our preliminary study indicates that the tropical band version of the regional climate model can be effectively used for the better understanding of these large scale global forcing's. This can improve the predictability of precipitation over this region and so it might help to come out with better socio-economic tools. Key words: Winter precipitation, El-Nino-southern oscillation, RegCM4, ENSO response and RegT-Band.

Regional-specific Stochastic Simulation of Spatially-distributed Ground-motion Time Histories using Wavelet Packet Analysis

NASA Astrophysics Data System (ADS)

Huang, D.; Wang, G.

2014-12-01

Stochastic simulation of spatially distributed ground-motion time histories is important for performance-based earthquake design of geographically distributed systems. In this study, we develop a novel technique to stochastically simulate regionalized ground-motion time histories using wavelet packet analysis. First, a transient acceleration time history is characterized by wavelet-packet parameters proposed by Yamamoto and Baker (2013). The wavelet-packet parameters fully characterize ground-motion time histories in terms of energy content, time- frequency-domain characteristics and time-frequency nonstationarity. This study further investigates the spatial cross-correlations of wavelet-packet parameters based on geostatistical analysis of 1500 regionalized ground motion data from eight well-recorded earthquakes in California, Mexico, Japan and Taiwan. The linear model of coregionalization (LMC) is used to develop a permissible spatial cross-correlation model for each parameter group. The geostatistical analysis of ground-motion data from different regions reveals significant dependence of the LMC structure on regional site conditions, which can be characterized by the correlation range of Vs30 in each region. In general, the spatial correlation and cross-correlation of wavelet-packet parameters are stronger if the site condition is more homogeneous. Using the regional-specific spatial cross-correlation model and cokriging technique, wavelet packet parameters at unmeasured locations can be best estimated, and regionalized ground-motion time histories can be synthesized. Case studies and blind tests demonstrated that the simulated ground motions generally agree well with the actual recorded data, if the influence of regional-site conditions is considered. The developed method has great potential to be used in computational-based seismic analysis and loss estimation in a regional scale.

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China

PubMed Central

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-01-01

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%–19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides. PMID:27187430

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

PubMed

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-05-11

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

A note on the efficiencies of sampling strategies in two-stage Bayesian regional fine mapping of a quantitative trait.

PubMed

Chen, Zhijian; Craiu, Radu V; Bull, Shelley B

2014-11-01

In focused studies designed to follow up associations detected in a genome-wide association study (GWAS), investigators can proceed to fine-map a genomic region by targeted sequencing or dense genotyping of all variants in the region, aiming to identify a functional sequence variant. For the analysis of a quantitative trait, we consider a Bayesian approach to fine-mapping study design that incorporates stratification according to a promising GWAS tag SNP in the same region. Improved cost-efficiency can be achieved when the fine-mapping phase incorporates a two-stage design, with identification of a smaller set of more promising variants in a subsample taken in stage 1, followed by their evaluation in an independent stage 2 subsample. To avoid the potential negative impact of genetic model misspecification on inference we incorporate genetic model selection based on posterior probabilities for each competing model. Our simulation study shows that, compared to simple random sampling that ignores genetic information from GWAS, tag-SNP-based stratified sample allocation methods reduce the number of variants continuing to stage 2 and are more likely to promote the functional sequence variant into confirmation studies. © 2014 WILEY PERIODICALS, INC.

INTERCOMPARISON STUDY OF ATMOSPHERIC MERCURY MODELS: 2. MODELING RESULTS VS. LONG-TERM OBSERVATIONS AND COMPARISON OF COUNTRY ATMOSPHERIC BALANCES

EPA Science Inventory

Five regional scale models with a horizontal domain covering the European continent and its surrounding seas, two hemispheric and one global scale model participated in the atmospheric Hg modelling intercomparison study. The models were compared between each other and with availa...

An assessment of precipitation and surface air temperature over China by regional climate models

NASA Astrophysics Data System (ADS)

Wang, Xueyuan; Tang, Jianping; Niu, Xiaorui; Wang, Shuyu

2016-12-01

An analysis of a 20-year summer time simulation of present-day climate (1989-2008) over China using four regional climate models coupled with different land surface models is carried out. The climatic means, interannual variability, linear trends, and extremes are examined, with focus on precipitation and near surface air temperature. The models are able to reproduce the basic features of the observed summer mean precipitation and temperature over China and the regional detail due to topographic forcing. Overall, the model performance is better for temperature than that of precipitation. The models reasonably grasp the major anomalies and standard deviations over China and the five subregions studied. The models generally reproduce the spatial pattern of high interannual variability over wet regions, and low variability over the dry regions. The models also capture well the variable temperature gradient increase to the north by latitude. Both the observed and simulated linear trend of precipitation shows a drying tendency over the Yangtze River Basin and wetting over South China. The models capture well the relatively small temperature trends in large areas of China. The models reasonably simulate the characteristics of extreme precipitation indices of heavy rain days and heavy precipitation fraction. Most of the models also performed well in capturing both the sign and magnitude of the daily maximum and minimum temperatures over China.

Development and comparison of metrics for evaluating climate models and estimation of projection uncertainty

NASA Astrophysics Data System (ADS)

Ring, Christoph; Pollinger, Felix; Kaspar-Ott, Irena; Hertig, Elke; Jacobeit, Jucundus; Paeth, Heiko

2017-04-01

The COMEPRO project (Comparison of Metrics for Probabilistic Climate Change Projections of Mediterranean Precipitation), funded by the Deutsche Forschungsgemeinschaft (DFG), is dedicated to the development of new evaluation metrics for state-of-the-art climate models. Further, we analyze implications for probabilistic projections of climate change. This study focuses on the results of 4-field matrix metrics. Here, six different approaches are compared. We evaluate 24 models of the Coupled Model Intercomparison Project Phase 3 (CMIP3), 40 of CMIP5 and 18 of the Coordinated Regional Downscaling Experiment (CORDEX). In addition to the annual and seasonal precipitation the mean temperature is analysed. We consider both 50-year trend and climatological mean for the second half of the 20th century. For the probabilistic projections of climate change A1b, A2 (CMIP3) and RCP4.5, RCP8.5 (CMIP5,CORDEX) scenarios are used. The eight main study areas are located in the Mediterranean. However, we apply our metrics to globally distributed regions as well. The metrics show high simulation quality of temperature trend and both precipitation and temperature mean for most climate models and study areas. In addition, we find high potential for model weighting in order to reduce uncertainty. These results are in line with other accepted evaluation metrics and studies. The comparison of the different 4-field approaches reveals high correlations for most metrics. The results of the metric-weighted probabilistic density functions of climate change are heterogeneous. We find for different regions and seasons both increases and decreases of uncertainty. The analysis of global study areas is consistent with the regional study areas of the Medeiterrenean.

The morphology of flare phenomena, magnetic fields, and electric currents in active regions. I - Introduction and methods

NASA Technical Reports Server (NTRS)

Canfield, Richard C.; De La Beaujardiere, J.-F.; Fan, Yuhong; Leka, K. D.; Mcclymont, A. N.; Metcalf, Thomas R.; Mickey, Donald L.; Wuelser, Jean-Pierre; Lites, Bruce W.

1993-01-01

Electric current systems in solar active regions and their spatial relationship to sites of electron precipitation and high-pressure in flares were studied with the purpose of providing observational evidence for or against the flare models commonly discussed in the literature. The paper describes the instrumentation, the data used, and the data analysis methods, as well as improvements made upon earlier studies. Several flare models are overviewed, and the predictions yielded by each model for the relationships of flares to the vertical current systems are discussed.

A probabilistic method for streamflow projection and associated uncertainty analysis in a data sparse alpine region

NASA Astrophysics Data System (ADS)

Ren, Weiwei; Yang, Tao; Shi, Pengfei; Xu, Chong-yu; Zhang, Ke; Zhou, Xudong; Shao, Quanxi; Ciais, Philippe

2018-06-01

Climate change imposes profound influence on regional hydrological cycle and water security in many alpine regions worldwide. Investigating regional climate impacts using watershed scale hydrological models requires a large number of input data such as topography, meteorological and hydrological data. However, data scarcity in alpine regions seriously restricts evaluation of climate change impacts on water cycle using conventional approaches based on global or regional climate models, statistical downscaling methods and hydrological models. Therefore, this study is dedicated to development of a probabilistic model to replace the conventional approaches for streamflow projection. The probabilistic model was built upon an advanced Bayesian Neural Network (BNN) approach directly fed by the large-scale climate predictor variables and tested in a typical data sparse alpine region, the Kaidu River basin in Central Asia. Results show that BNN model performs better than the general methods across a number of statistical measures. The BNN method with flexible model structures by active indicator functions, which reduce the dependence on the initial specification for the input variables and the number of hidden units, can work well in a data limited region. Moreover, it can provide more reliable streamflow projections with a robust generalization ability. Forced by the latest bias-corrected GCM scenarios, streamflow projections for the 21st century under three RCP emission pathways were constructed and analyzed. Briefly, the proposed probabilistic projection approach could improve runoff predictive ability over conventional methods and provide better support to water resources planning and management under data limited conditions as well as enable a facilitated climate change impact analysis on runoff and water resources in alpine regions worldwide.

Biogeochemical Trends and Their Ecosystem Impacts in Atlantic Canada

NASA Astrophysics Data System (ADS)

Fennel, Katja; Rutherford, Krysten; Kuhn, Angela; Zhang, Wenxia; Brennan, Katie; Zhang, Rui

2017-04-01

The representation of coastal oceans in global biogeochemical models is a challenge, yet the ecosystems in these regions are most vulnerable to the combined stressors of ocean warming, deoxygenation, acidification, eutrophication and fishing. Coastal regions also have large air-sea fluxes of CO2, making them an important but poorly quantified component of the global carbon cycle, and are the most relevant for human activities. Regional model applications that are nested within large-scale or global models are necessary for detailed studies of coastal regions. We present results from such a regional biogeochemical model for the northwestern North Atlantic shelves and adjacent deep ocean of Atlantic Canada. The model is an implementation of the Regional Ocean Modeling System (ROMS) and includes an NPZD-type nitrogen cycle model with explicit representation of dissolved oxygen and inorganic carbon. The region is at the confluence of the Gulf Stream and Labrador Current making it highly dynamic, a challenge for analysis and prediction, and prone to large changes. Historically a rich fishing ground, coastal ecosystems in Atlantic Canada have undergone dramatic changes including the collapse of several economically important fish stocks and the listing of many species as threatened or endangered. Furthermore it is unclear whether the region is a net source or sink of atmospheric CO2 with estimates of the size and direction of the net air-sea CO2 flux remaining controversial. We will discuss simulated patterns of primary production, inorganic carbon fluxes and oxygen trends in the context of circulation features and shelf residence times for the present ocean state and present future projections.

Two case studies on NARCCAP precipitation extremes

NASA Astrophysics Data System (ADS)

Weller, Grant B.; Cooley, Daniel; Sain, Stephan R.; Bukovsky, Melissa S.; Mearns, Linda O.

2013-09-01

We introduce novel methodology to examine the ability of six regional climate models (RCMs) in the North American Regional Climate Change Assessment Program (NARCCAP) ensemble to simulate past extreme precipitation events seen in the observational record over two different regions and seasons. Our primary objective is to examine the strength of daily correspondence of extreme precipitation events between observations and the output of both the RCMs and the driving reanalysis product. To explore this correspondence, we employ methods from multivariate extreme value theory. These methods require that we account for marginal behavior, and we first model and compare climatological quantities which describe tail behavior of daily precipitation for both the observations and model output before turning attention to quantifying the correspondence of the extreme events. Daily precipitation in a West Coast region of North America is analyzed in two seasons, and it is found that the simulated extreme events from the reanalysis-driven NARCCAP models exhibit strong daily correspondence to extreme events in the observational record. Precipitation over a central region of the United States is examined, and we find some daily correspondence between winter extremes simulated by reanalysis-driven NARCCAP models and those seen in observations, but no such correspondence is found for summer extremes. Furthermore, we find greater discrepancies among the NARCCAP models in the tail characteristics of the distribution of daily summer precipitation over this region than seen in precipitation over the West Coast region. We find that the models which employ spectral nudging exhibit stronger tail dependence to observations in the central region.

Historical Maps from Modern Images: Using Remote Sensing to Model and Map Century-Long Vegetation Change in a Fire-Prone Region

PubMed Central

Callister, Kate E.; Griffioen, Peter A.; Avitabile, Sarah C.; Haslem, Angie; Kelly, Luke T.; Kenny, Sally A.; Nimmo, Dale G.; Farnsworth, Lisa M.; Taylor, Rick S.; Watson, Simon J.; Bennett, Andrew F.; Clarke, Michael F.

2016-01-01

Understanding the age structure of vegetation is important for effective land management, especially in fire-prone landscapes where the effects of fire can persist for decades and centuries. In many parts of the world, such information is limited due to an inability to map disturbance histories before the availability of satellite images (~1972). Here, we describe a method for creating a spatial model of the age structure of canopy species that established pre-1972. We built predictive neural network models based on remotely sensed data and ecological field survey data. These models determined the relationship between sites of known fire age and remotely sensed data. The predictive model was applied across a 104,000 km2 study region in semi-arid Australia to create a spatial model of vegetation age structure, which is primarily the result of stand-replacing fires which occurred before 1972. An assessment of the predictive capacity of the model using independent validation data showed a significant correlation (rs = 0.64) between predicted and known age at test sites. Application of the model provides valuable insights into the distribution of vegetation age-classes and fire history in the study region. This is a relatively straightforward method which uses widely available data sources that can be applied in other regions to predict age-class distribution beyond the limits imposed by satellite imagery. PMID:27029046

Regional regression models of watershed suspended-sediment discharge for the eastern United States

NASA Astrophysics Data System (ADS)

Roman, David C.; Vogel, Richard M.; Schwarz, Gregory E.

2012-11-01

SummaryEstimates of mean annual watershed sediment discharge, derived from long-term measurements of suspended-sediment concentration and streamflow, often are not available at locations of interest. The goal of this study was to develop multivariate regression models to enable prediction of mean annual suspended-sediment discharge from available basin characteristics useful for most ungaged river locations in the eastern United States. The models are based on long-term mean sediment discharge estimates and explanatory variables obtained from a combined dataset of 1201 US Geological Survey (USGS) stations derived from a SPAtially Referenced Regression on Watershed attributes (SPARROW) study and the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES) database. The resulting regional regression models summarized for major US water resources regions 1-8, exhibited prediction R2 values ranging from 76.9% to 92.7% and corresponding average model prediction errors ranging from 56.5% to 124.3%. Results from cross-validation experiments suggest that a majority of the models will perform similarly to calibration runs. The 36-parameter regional regression models also outperformed a 16-parameter national SPARROW model of suspended-sediment discharge and indicate that mean annual sediment loads in the eastern United States generally correlates with a combination of basin area, land use patterns, seasonal precipitation, soil composition, hydrologic modification, and to a lesser extent, topography.

Regional regression models of watershed suspended-sediment discharge for the eastern United States

USGS Publications Warehouse

Roman, David C.; Vogel, Richard M.; Schwarz, Gregory E.

2012-01-01

Estimates of mean annual watershed sediment discharge, derived from long-term measurements of suspended-sediment concentration and streamflow, often are not available at locations of interest. The goal of this study was to develop multivariate regression models to enable prediction of mean annual suspended-sediment discharge from available basin characteristics useful for most ungaged river locations in the eastern United States. The models are based on long-term mean sediment discharge estimates and explanatory variables obtained from a combined dataset of 1201 US Geological Survey (USGS) stations derived from a SPAtially Referenced Regression on Watershed attributes (SPARROW) study and the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES) database. The resulting regional regression models summarized for major US water resources regions 1–8, exhibited prediction R2 values ranging from 76.9% to 92.7% and corresponding average model prediction errors ranging from 56.5% to 124.3%. Results from cross-validation experiments suggest that a majority of the models will perform similarly to calibration runs. The 36-parameter regional regression models also outperformed a 16-parameter national SPARROW model of suspended-sediment discharge and indicate that mean annual sediment loads in the eastern United States generally correlates with a combination of basin area, land use patterns, seasonal precipitation, soil composition, hydrologic modification, and to a lesser extent, topography.

Short-Range Prediction of Monsoon Precipitation by NCMRWF Regional Unified Model with Explicit Convection

NASA Astrophysics Data System (ADS)

Mamgain, Ashu; Rajagopal, E. N.; Mitra, A. K.; Webster, S.

2018-03-01

There are increasing efforts towards the prediction of high-impact weather systems and understanding of related dynamical and physical processes. High-resolution numerical model simulations can be used directly to model the impact at fine-scale details. Improvement in forecast accuracy can help in disaster management planning and execution. National Centre for Medium Range Weather Forecasting (NCMRWF) has implemented high-resolution regional unified modeling system with explicit convection embedded within coarser resolution global model with parameterized convection. The models configurations are based on UK Met Office unified seamless modeling system. Recent land use/land cover data (2012-2013) obtained from Indian Space Research Organisation (ISRO) are also used in model simulations. Results based on short-range forecast of both the global and regional models over India for a month indicate that convection-permitting simulations by the high-resolution regional model is able to reduce the dry bias over southern parts of West Coast and monsoon trough zone with more intense rainfall mainly towards northern parts of monsoon trough zone. Regional model with explicit convection has significantly improved the phase of the diurnal cycle of rainfall as compared to the global model. Results from two monsoon depression cases during study period show substantial improvement in details of rainfall pattern. Many categories in rainfall defined for operational forecast purposes by Indian forecasters are also well represented in case of convection-permitting high-resolution simulations. For the statistics of number of days within a range of rain categories between `No-Rain' and `Heavy Rain', the regional model is outperforming the global model in all the ranges. In the very heavy and extremely heavy categories, the regional simulations show overestimation of rainfall days. Global model with parameterized convection have tendency to overestimate the light rainfall days and underestimate the heavy rain days compared to the observation data.

Upscaling

NASA Astrophysics Data System (ADS)

Vandenbulcke, Luc; Barth, Alexander

2017-04-01

In the present European operational oceanography context, global and basin-scale models are run daily at different Monitoring and Forecasting Centers from the Copernicus Marine component (CMEMS). Regional forecasting centers, which run outside of CMEMS, then use these forecasts as initial conditions and/or boundary conditions for high-resolution or coastal forecasts. However, these improved simulations are lost to the basin-scale models (i.e. there is no feedback). Therefore, some potential improvements inside (and even outside) the areas covered by regional models are lost, and the risk for discrepancy between basin-scale and regional model remains high. The objective of this study is to simulate two-way nesting by extracting pseudo-observations from the regional models and assimilating them in the basin-scale models. The proposed method is called "upscaling". A ensemble of 100 one-way nested NEMO models of the Mediterranean Sea (Med) (1/16°) and the North-Western Med (1/80°) is implemented to simulate the period 2014-2015. Each member has perturbed initial conditions, atmospheric forcing fields and river discharge data. The Med model uses climatological Rhone river data, while the nested model uses measured daily discharges. The error of the pseudo-observations can be estimated by analyzing the ensemble of nested models. The pseudo-observations are then assimilated in the parent model by means of an Ensemble Kalman Filter. The experiments show that the proposed method improves different processes in the Med model, such as the position of the Northern Current and its incursion (or not) on the Gulf of Lions, the cold water mass on the shelf, and the position of the Rhone river plume. Regarding areas where no operational regional models exist, (some variables of) the parent model can still be improved by relating some resolved parameters to statistical properties of a higher-resolution simulation. This is the topic of a complementary study also presented at the EGU 2017 (Barth et al).

Projection of wave conditions in response to climate change: A community approach to global and regional wave downscaling

USGS Publications Warehouse

Erikson, Li H.; Hemer, M.; Lionello, Piero; Mendez, Fernando J.; Mori, Nobuhito; Semedo, Alvaro; Wang, Xiaolan; Wolf, Judith

2015-01-01

Future changes in wind-wave climate have broad implications for coastal geomorphology and management. General circulation models (GCM) are now routinely used for assessing climatological parameters, but generally do not provide parameterizations of ocean wind-waves. To fill this information gap, a growing number of studies use GCM outputs to independently downscale wave conditions to global and regional levels. To consolidate these efforts and provide a robust picture of projected changes, we present strategies from the community-derived multi-model ensemble of wave climate projections (COWCLIP) and an overview of regional contributions. Results and strategies from one contributing regional study concerning changes along the eastern North Pacific coast are presented.

Physics based model of D-region variability related to VLF propagation effects

NASA Astrophysics Data System (ADS)

Chakravarty, S. C.

2012-07-01

D-region (~60-85 km) electron density profiles measured using large number of sounding rocket experiments carried out from two Indian low latitude stations show large variations with solar zenith angle, season and solar activity. Similarly the ground based multi frequency radio wave absorption technique has provided continuous data on the morphology of the hourly electron density variations. However suitable models of the D-region electron density profile variations both during quiet and disturbed solar conditions over the Indian region are lacking. The renewed interest in the study of the VLF/LF propagation anomalies taking place through perturbations in the D-region electron densities due to various geophysical phenomena requires the availability of a baseline D-region model over low latitudes. The purpose of this paper is to critically review the physical processes of D-region production and loss of free electrons, dynamical coupling due to variety of vertically propagating atmospheric waves, sudden changes brought about by the solar energetic events like CMEs and different categories of X-ray flares. Low latitude region is not likely to be affected by the PMSE or PCA type of events but the changes due to lightning induced mesospheric red sprites and LEPs need to be considered. Based on this analysis, a preliminary low latitude D-region electron density profile model development is proposed. Sample results would illustrate key requirements from such a model in terms of its effectiveness to simulate the low latitude observations of VLF/LF amplitude and phase variations using waveguide propagation models like LWPC.

Structural differences between the avian and human H7N9 hemagglutinin proteins are attributable to modifications in salt bridge formation: a computational study with implications in viral evolution.

PubMed

Cueno, Marni E; Imai, Kenichi; Tamura, Muneaki; Ochiai, Kuniyasu

2013-01-01

Influenza A hemagglutinin (HA) is a homotrimeric glycoprotein composed of a fibrous globular stem supporting a globular head containing three sialic acid binding sites responsible for infection. The H7N9 strain has consistently infected an avian host, however, the novel 2013 strain is now capable of infecting a human host which would imply that the HA in both strains structurally differ. A better understanding of the structural differences between the avian and human H7N9 strains may shed light into viral evolution and transmissibility. In this study, we elucidated the structural differences between the avian and human H7N9 strains. Throughout the study, we generated HA homology models, verified the quality of each model, superimposed HA homology models to determine structural differences, and, likewise, elucidated the probable cause for these structural differences. We detected two different types of structural differences between the novel H7N9 human and representative avian strains, wherein, one type (Pattern-1) showed three non-overlapping regions while the other type (Pattern-2) showed only one non-overlapping region. In addition, we found that superimposed HA homology models exhibiting Pattern-1 contain three non-overlapping regions designated as: Region-1 (S1571-A1601); Region-3 (R2621-S2651); and Region-4 (S2701-D2811), whereas, superimposed HA homology models showing Pattern-2 only contain one non-overlapping region designated as Region-2 (S1371-S1451). We attributed the two patterns we observed to either the presence of salt bridges involving the E1141 residue or absence of the R1411:D771 salt bridge. Interestingly, comparison between the human H7N7 and H7N9 HA homology models showed high structural similarity. We propose that the putative absence of the R1411:D771 salt bridge coupled with the putative presence of the E1141:R2621 and E1141:K2641 salt bridges found in the 2013 H7N9 HA homology model is associated to human-type receptor binding. This highlights the possible significance of HA salt bridge formation modifications in viral infectivity, immune escape, transmissibility and evolution.

Future projections of temperature and precipitation climatology for CORDEX-MENA domain using RegCM4.4

NASA Astrophysics Data System (ADS)

Ozturk, Tugba; Turp, M. Tufan; Türkeş, Murat; Kurnaz, M. Levent

2018-07-01

In this study, we investigate changes in seasonal temperature and precipitation climatology of CORDEX Middle East and North Africa (MENA) region for three periods of 2010-2040, 2040-2070 and 2070-2100 with respect to the control period of 1970-2000 by using regional climate model simulations. Projections of future climate conditions are modeled by forcing Regional Climate Model, RegCM4.4 of the International Centre for Theoretical Physics (ICTP) with two different CMIP5 global climate models. HadGEM2-ES global climate model of the Met Office Hadley Centre and MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology were used to generate 50 km resolution data for the Coordinated Regional Climate Downscaling Experiment (CORDEX) Region 13. We test the seasonal time-scale performance of RegCM4.4 in simulating the observed climatology over domain of the MENA by using the output of two different global climate models. The projection results show relatively high increase of average temperatures from 3 °C up to 9 °C over the domain for far future (2070-2100). A strong decrease in precipitation is projected in almost all parts of the domain according to the output of the regional model forced by scenario outputs of two global models. Therefore, warmer and drier than present climate conditions are projected to occur more intensely over the CORDEX-MENA domain.

Air quality modeling for the urban Jackson, Mississippi Region using a high resolution WRF/Chem model.

PubMed

Yerramilli, Anjaneyulu; Dodla, Venkata B; Desamsetti, Srinivas; Challa, Srinivas V; Young, John H; Patrick, Chuck; Baham, Julius M; Hughes, Robert L; Yerramilli, Sudha; Tuluri, Francis; Hardy, Mark G; Swanier, Shelton J

2011-06-01

In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi) region using an online WRF/Chem (Weather Research and Forecasting-Chemistry) model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators.

Impacts of agricultural land use on biological integrity: A causal analysis

USGS Publications Warehouse

Riseng, C.M.; Wiley, M.J.; Black, R.W.; Munn, M.D.

2011-01-01

Agricultural land use has often been linked to nutrient enrichment, habitat degradation, hydrologic alteration, and loss of biotic integrity in streams. The U.S. Geological Survey's National Water Quality Assessment Program sampled 226 stream sites located in eight agriculture-dominated study units across the United States to investigate the geographic variability and causes of agricultural impacts on stream biotic integrity. In this analysis we used structural equation modeling (SEM) to develop a national and set of regional causal models linking agricultural land use to measured instream conditions. We then examined the direct, indirect, and total effects of agriculture on biotic integrity as it acted through multiple water quality and habitat pathways. In our nation-wide model, cropland affected benthic communities by both altering structural habitats and by imposing water quality-related stresses. Regionspecific modeling demonstrated that geographic context altered the relative importance of causal pathways through which agricultural activities affected stream biotic integrity. Cropland had strong negative total effects on the invertebrate community in the national, Midwest, and Western models, but a very weak effect in the Eastern Coastal Plain model. In theWestern Arid and Eastern Coastal Plain study regions, cropland impacts were transmitted primarily through dissolved water quality contaminants, but in the Midwestern region, they were transmitted primarily through particulate components of water quality. Habitat effects were important in the Western Arid model, but negligible in the Midwest and Eastern Coastal Plain models. The relative effects of riparian forested wetlands also varied regionally, having positive effects on biotic integrity in the Eastern Coastal Plain andWestern Arid region models, but no statistically significant effect in the Midwest. These differences in response to cropland and riparian cover suggest that best management practices and planning for the mitigation of agricultural land use impacts on stream ecosystems should be regionally focused. ?? 2011 by the Ecological Society of America.

Assessing Hydrological and Energy Budgets in Amazonia through Regional Downscaling, and Comparisons with Global Reanalysis Products

NASA Astrophysics Data System (ADS)

Nunes, A.; Ivanov, V. Y.

2014-12-01

Although current global reanalyses provide reasonably accurate large-scale features of the atmosphere, systematic errors are still found in the hydrological and energy budgets of such products. In the tropics, precipitation is particularly challenging to model, which is also adversely affected by the scarcity of hydrometeorological datasets in the region. With the goal of producing downscaled analyses that are appropriate for a climate assessment at regional scales, a regional spectral model has used a combination of precipitation assimilation with scale-selective bias correction. The latter is similar to the spectral nudging technique, which prevents the departure of the regional model's internal states from the large-scale forcing. The target area in this study is the Amazon region, where large errors are detected in reanalysis precipitation. To generate the downscaled analysis, the regional climate model used NCEP/DOE R2 global reanalysis as the initial and lateral boundary conditions, and assimilated NOAA's Climate Prediction Center (CPC) MORPHed precipitation (CMORPH), available at 0.25-degree resolution, every 3 hours. The regional model's precipitation was successfully brought closer to the observations, in comparison to the NCEP global reanalysis products, as a result of the impact of a precipitation assimilation scheme on cumulus-convection parameterization, and improved boundary forcing achieved through a new version of scale-selective bias correction. Water and energy budget terms were also evaluated against global reanalyses and other datasets.

Climate model uncertainty in impact assessments for agriculture: A multi-ensemble case study on maize in sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Dale, Amy; Fant, Charles; Strzepek, Kenneth; Lickley, Megan; Solomon, Susan

2017-03-01

We present maize production in sub-Saharan Africa as a case study in the exploration of how uncertainties in global climate change, as reflected in projections from a range of climate model ensembles, influence climate impact assessments for agriculture. The crop model AquaCrop-OS (Food and Agriculture Organization of the United Nations) was modified to run on a 2° × 2° grid and coupled to 122 climate model projections from multi-model ensembles for three emission scenarios (Coupled Model Intercomparison Project Phase 3 [CMIP3] SRES A1B and CMIP5 Representative Concentration Pathway [RCP] scenarios 4.5 and 8.5) as well as two "within-model" ensembles (NCAR CCSM3 and ECHAM5/MPI-OM) designed to capture internal variability (i.e., uncertainty due to chaos in the climate system). In spite of high uncertainty, most notably in the high-producing semi-arid zones, we observed robust regional and sub-regional trends across all ensembles. In agreement with previous work, we project widespread yield losses in the Sahel region and Southern Africa, resilience in Central Africa, and sub-regional increases in East Africa and at the southern tip of the continent. Spatial patterns of yield losses corresponded with spatial patterns of aridity increases, which were explicitly evaluated. Internal variability was a major source of uncertainty in both within-model and between-model ensembles and explained the majority of the spatial distribution of uncertainty in yield projections. Projected climate change impacts on maize production in different regions and nations ranged from near-zero or positive (upper quartile estimates) to substantially negative (lower quartile estimates), highlighting a need for risk management strategies that are adaptive and robust to uncertainty.

A Pilot Study Assesing Climate Change Impacts on Cereals

NASA Astrophysics Data System (ADS)

Topcu, Sevilay; Sen, Burak; Turkes, Murat

2010-05-01

The spatial and temporal impacts of climate change on the growth and yield of major cereals (first and second-crop corn) as well as wheat grown in Cukurova Region in the southern Turkey have been assessed, by combining the outputs from a regional climate model with a crop growth simulation model. With its 1.1 million ha of agricultural land, the Cukurova Region is one of the major agricultural production regions in Turkey. Wheat dominates in rain-fed areas while corn crops are grown in more than 50 % of the irrigated land in the region. Thus, the Region is providing half of the country's total cereal production. Since the region has a typical Mediterranean climate with almost no rain and high temperatures during the summer months, agricultural production is vulnerable to changes in climate in terms of decreasing rainfall and increasing temperatures and consequently shortage of water resources. To predict the future climate for the period 2070-2100, the regional climate model RegCM3 conditions was performed using IPCC's SRESS-A2 scenario, and climatic parameter such as daily mean, maximum and minimum temperatures, radiation as well as total annual precipitation were selected for the simulation study. Data for the period 1961 to 1990 were used as historical reference. The WOFOST model was used to simulate cereal growths and yields for two different water availability senarios: 1) potential production and 2) water-limited production conditions. Potential growth represents the conditions where no limiting factor such as water and nutrients is present, however due to the water-limited production situation, water for irrigation is limited as a consequence of water shortage. The detailed results of previous field experiments carried out with three cereal crops in different locations with different regional soil and climate conditions were used for the verification of the WOFOST model. According to the verification results, the model simulated the yield with less than 5% deviation for all three cereal crops. According to projections of the regional climate model RegCM3, the annual average temperature will likely increase by 3.4 to 4.8 °C, while approximately a 25% decrease in rainfall amounts is expected in the Cukurova Region during the period 2071-2100. Similar results for temperatures were estimated for entire country, however predicted changes in rainfall varies in a wide range for the country. The study showed that with climate change, wheat yield could decrease drastically in rainfed areas, however supplemental irrigation could help to sustain the yield on the current level. Yields of first and second-crop corn are expected to decrease by 58% and 43.4%, respectively, compared to the reference value under water shortages.

Modeling Seasonal Influenza Transmission and Its Association with Climate Factors in Thailand Using Time-Series and ARIMAX Analyses.

PubMed

Chadsuthi, Sudarat; Iamsirithaworn, Sopon; Triampo, Wannapong; Modchang, Charin

2015-01-01

Influenza is a worldwide respiratory infectious disease that easily spreads from one person to another. Previous research has found that the influenza transmission process is often associated with climate variables. In this study, we used autocorrelation and partial autocorrelation plots to determine the appropriate autoregressive integrated moving average (ARIMA) model for influenza transmission in the central and southern regions of Thailand. The relationships between reported influenza cases and the climate data, such as the amount of rainfall, average temperature, average maximum relative humidity, average minimum relative humidity, and average relative humidity, were evaluated using cross-correlation function. Based on the available data of suspected influenza cases and climate variables, the most appropriate ARIMA(X) model for each region was obtained. We found that the average temperature correlated with influenza cases in both central and southern regions, but average minimum relative humidity played an important role only in the southern region. The ARIMAX model that includes the average temperature with a 4-month lag and the minimum relative humidity with a 2-month lag is the appropriate model for the central region, whereas including the minimum relative humidity with a 4-month lag results in the best model for the southern region.

A HTAP Multi-Model Assessment of the Influence of Regional Anthropogenic Emission Reductions on Aerosol Direct Radiative Forcing and the Role of Intercontinental Transport

NASA Technical Reports Server (NTRS)

Yu, Hongbin; Chin, Mian; West, J. Jason; Atherton, Cynthia S.; Bellouin, Nicolas; Bergmann, Dan; Bey, Isabelle; Bian, Huisheng; Diehl, Thomas; Forberth, Gerd;

River catchment rainfall series analysis using additive Holt-Winters method

NASA Astrophysics Data System (ADS)

Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

2016-03-01

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

The Impact of Chemical Mechanism Design on Simulated Surface Ozone in CAM-Chem

NASA Astrophysics Data System (ADS)

Schwantes, R.; Emmons, L. K.; Orlando, J. J.; Tyndall, G. S.

2017-12-01

Many regions in the United States have poor air quality because of high levels of ozone. Global and regional chemical transport models are important tools for recommending regulatory policy directions to efficiently reduce ozone. Ozone is intrinsically hard to simulate in global and regional models because the amount of ozone present is controlled by large non-linear sources and sinks. Recent field campaigns have concluded that monoterpene chemistry is particularly important for the NOx budget and thereby O3 formation. However, many regional and global models have none or heavily reduced monoterpene chemical schemes. In this study, the chemical mechanism for isoprene and monoterpene oxidation will be significantly improved and updated in CAM-Chem (Community Atmosphere Model with chemistry), which is a component of the Community Earth System Model (CESM). In particular, the updates will focus on accurately portraying organic nitrate formation and fate. The impact of various uncertainties (e.g., nitrate yields, later generation chemistry, loss of organic nitrates to aerosols via hydrolysis, etc.) on ozone formation will be tested. This study will both improve the chemistry in CAM-Chem and reveal lingering uncertainties that have the largest impact on ozone formation.

From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder

PubMed Central

Venkataraman, Archana; Kubicki, Marek; Golland, Polina

2014-01-01

We propose a novel approach to identify the foci of a neurological disorder based on anatomical and functional connectivity information. Specifically, we formulate a generative model that characterizes the network of abnormal functional connectivity emanating from the affected foci. This allows us to aggregate pairwise connectivity changes into a region-based representation of the disease. We employ the variational expectation-maximization algorithm to fit the model and subsequently identify both the afflicted regions and the differences in connectivity induced by the disorder. We demonstrate our method on a population study of schizophrenia. PMID:23864168

Tagging Water Sources in Atmospheric Models

NASA Technical Reports Server (NTRS)

Bosilovich, M.

2003-01-01

Tagging of water sources in atmospheric models allows for quantitative diagnostics of how water is transported from its source region to its sink region. In this presentation, we review how this methodology is applied to global atmospheric models. We will present several applications of the methodology. In one example, the regional sources of water for the North American Monsoon system are evaluated by tagging the surface evaporation. In another example, the tagged water is used to quantify the global water cycling rate and residence time. We will also discuss the need for more research and the importance of these diagnostics in water cycle studies.

Peak-flow characteristics of Virginia streams

USGS Publications Warehouse

Austin, Samuel H.; Krstolic, Jennifer L.; Wiegand, Ute

2011-01-01

Peak-flow annual exceedance probabilities, also called probability-percent chance flow estimates, and regional regression equations are provided describing the peak-flow characteristics of Virginia streams. Statistical methods are used to evaluate peak-flow data. Analysis of Virginia peak-flow data collected from 1895 through 2007 is summarized. Methods are provided for estimating unregulated peak flow of gaged and ungaged streams. Station peak-flow characteristics identified by fitting the logarithms of annual peak flows to a Log Pearson Type III frequency distribution yield annual exceedance probabilities of 0.5, 0.4292, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005, and 0.002 for 476 streamgaging stations. Stream basin characteristics computed using spatial data and a geographic information system are used as explanatory variables in regional regression model equations for six physiographic regions to estimate regional annual exceedance probabilities at gaged and ungaged sites. Weighted peak-flow values that combine annual exceedance probabilities computed from gaging station data and from regional regression equations provide improved peak-flow estimates. Text, figures, and lists are provided summarizing selected peak-flow sites, delineated physiographic regions, peak-flow estimates, basin characteristics, regional regression model equations, error estimates, definitions, data sources, and candidate regression model equations. This study supersedes previous studies of peak flows in Virginia.

A Multi-Tiered Approach for Building Capacity in Hydrologic Modeling for Water Resource Management in Developing Regions

NASA Astrophysics Data System (ADS)

Markert, K. N.; Limaye, A. S.; Rushi, B. R.; Adams, E. C.; Anderson, E.; Ellenburg, W. L.; Mithieu, F.; Griffin, R.

2017-12-01

Water resource management is the process by which governments, businesses and/or individuals reach and implement decisions that are intended to address the future quantity and/or quality of water for societal benefit. The implementation of water resource management typically requires the understanding of the quantity and/or timing of a variety of hydrologic variables (e.g. discharge, soil moisture and evapotranspiration). Often times these variables for management are simulated using hydrologic models particularly in data sparse regions. However, there are several large barriers to entry in learning how to use models, applying best practices during the modeling process, and selecting and understanding the most appropriate model for diverse applications. This presentation focuses on a multi-tiered approach to bring the state-of-the-art hydrologic modeling capabilities and methods to developing regions through the SERVIR program, a joint NASA and USAID initiative that builds capacity of regional partners and their end users on the use of Earth observations for environmental decision making. The first tier is a series of trainings on the use of multiple hydrologic models, including the Variable Infiltration Capacity (VIC) and Ensemble Framework For Flash Flood Forecasting (EF5), which focus on model concepts and steps to successfully implement the models. We present a case study for this in a pilot area, the Nyando Basin in Kenya. The second tier is focused on building a community of practice on applied hydrology modeling aimed at creating a support network for hydrologists in SERVIR regions and promoting best practices. The third tier is a hydrologic inter-comparison project under development in the SERVIR regions. The objective of this step is to understand model performance under specific decision-making scenarios, and to share knowledge among hydrologists in SERVIR regions. The results of these efforts include computer programs, training materials, and new scientific understanding, all of which are shared in an open and collaborative environment for transparency and subsequent capacity building in SERVIR regions and beyond. The outcome of this work is increased awareness and capacity on the use of hydrologic models in developing regions to support water resource management and water security.

USGS Regional Groundwater Availability Studies: Quantifying Aquifer Response

NASA Astrophysics Data System (ADS)

Reeves, H. W.

2017-12-01

The U.S. Geological Survey (USGS) identified six challenges in determining groundwater availability: 1) limited direct measurement, 2) varying response times for different systems, 3) varying spatial scales for different availability questions and aquifer systems, 4) varying tolerance to changes in water levels or outflows, 5) redistribution of stresses and potential return-flow of water pumped from the system, and 6) varying chemical quality of groundwater and the role of quality in determining suitability for different uses. USGS Regional groundwater availability studies are designed to address these challenges. USGS regional groundwater availability studies focus on quantifying the groundwater budget for principal aquifers and determining how this budget has changed in response to pumping or variations in climate. This focus requires relating limited measurements to a quantitative understanding of the temporal and spatial response of regional aquifers. For most principal aquifer studies, aquifer response is quantified using regional groundwater flow models, and USGS regional groundwater availability studies have provided test cases for the development and application of advanced modeling techniques and methods. Results from regional studies from the Lake Michigan Basin and Northern Atlantic Coastal Plain illustrate how different parts of these systems respond differently to pumping with some areas showing large drawdowns and others having much less drawdown but greater capture of discharge. The Central Valley and Mississippi Embayment studies show how extensive pumping and transfer of water have resulted in much more groundwater moving through the aquifer system under current conditions compared to pre-development. These and other results from regional studies will be explored to illustrate how regional groundwater availability and related studies address the six challenges to determining groundwater availability.

More robust regional precipitation projection from selected CMIP5 models based on multiple-dimensional metrics

NASA Astrophysics Data System (ADS)

Qian, Y.; Wang, L.; Leung, L. R.; Lin, G.; Lu, J.; Gao, Y.; Zhang, Y.

2017-12-01

Projecting precipitation changes is challenging because of incomplete understanding of the climate system and biases and uncertainty in climate models. In East Asia where summer precipitation is dominantly influenced by the monsoon circulation and the global models from Coupled Model Intercomparison Project Phase 5 (CMIP5), however, give various projection of precipitation change for 21th century. It is critical for community to know which models' projection are more reliable in response to natural and anthropogenic forcings. In this study we defined multiple-dimensional metrics, measuring the model performance in simulating the present-day of large-scale circulation, regional precipitation and relationship between them. The large-scale circulation features examined in this study include the lower tropospheric southwesterly winds, the western North Pacific subtropical high, the South China Sea Subtropical High, and the East Asian westerly jet in the upper troposphere. Each of these circulation features transport moisture to East Asia, enhancing the moist static energy and strengthening the Meiyu moisture front that is the primary mechanism for precipitation generation in eastern China. Based on these metrics, 30 models in CMIP5 ensemble are classified into three groups. Models in the top performing group projected regional precipitation patterns that are more similar to each other than the bottom or middle performing group and consistently projected statistically significant increasing trends in two of the large-scale circulation indices and precipitation. In contrast, models in the bottom or middle performing group projected small drying or no trends in precipitation. We also find the models that only reasonably reproduce the observed precipitation climatology does not guarantee more reliable projection of future precipitation because good simulation skill could be achieved through compensating errors from multiple sources. Herein the potential for more robust projections of precipitation changes at regional scale is demonstrated through the use of discriminating metric to subsample the multi-model ensemble. The results from this study provides insights for how to select models from CMIP ensemble to project regional climate and hydrological cycle changes.

Hydrogeologic settings and groundwater-flow simulations for regional investigations of the transport of anthropogenic and natural contaminants to public-supply wells—Investigations begun in 2004

USGS Publications Warehouse

Eberts, Sandra M.

2011-01-01

A study of the Transport of Anthropogenic and Natural Contaminants to public-supply wells (TANC study) was begun in 2001 as part of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program. The study was designed to shed light on factors that affect the vulnerability of groundwater and, more specifically, water from public-supply wells to contamination to provide a context for the NAWQA Program's earlier finding of mixtures of contaminants at low concentrations in groundwater near the water table in urban areas across the Nation. The TANC study has included investigations at both the regional (tens to thousands of square kilometers) and local (generally less than 25 square kilometers) scales. At the regional scale, the approach to investigation involves refining conceptual models of groundwater flow in hydrologically distinct settings and then constructing or updating a groundwater-flow model with particle tracking for each setting to help quantify regional water budgets, public-supply well contributing areas (areas contributing recharge to wells and zones of contribution for wells), and traveltimes from recharge areas to selected wells. A great deal of information about each contributing area is captured from the model output, including values for 170 variables that describe physical and (or) geochemical characteristics of the contributing areas. The information is subsequently stored in a relational database. Retrospective water-quality data from monitoring, domestic, and many of the public-supply wells, as well as data from newly collected samples at selected public-supply wells, also are stored in the database and are used with the model output to help discern the more important factors affecting vulnerability in many, if not most, settings. The study began with investigations in seven regional areas, and it benefits from being conducted as part of the NAWQA Program, in which consistent methods are used so that meaningful comparisons can be made. The hydrogeologic settings and regional-scale groundwater-flow models from the initial seven regional areas are documented in Chapter A of this U.S. Geological Survey Professional Paper. Also documented in Chapter A are the methods used to collect and compile the water-quality data, determine contributing areas of the public-supply wells, and characterize the oxidation-reduction (redox) conditions in each setting. A data dictionary for the database that was designed to enable joint storage and access to water-quality data and groundwater-flow model particle-tracking output is included as Appendix 1 of Chapter A. This chapter, Chapter B, documents modifications to the study methods and presents descriptions of two regional areas that were added to the TANC study in 2004.

Assessment of CMIP5 historical simulations of rainfall over Southeast Asia

NASA Astrophysics Data System (ADS)

Raghavan, Srivatsan V.; Liu, Jiandong; Nguyen, Ngoc Son; Vu, Minh Tue; Liong, Shie-Yui

2018-05-01

We present preliminary analyses of the historical (1986-2005) climate simulations of a ten-member subset of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) global climate models over Southeast Asia. The objective of this study was to evaluate the general circulation models' performance in simulating the mean state of climate over this less-studied climate vulnerable region, with a focus on precipitation. Results indicate that most of the models are unable to reproduce the observed state of climate over Southeast Asia. Though the multi-model ensemble mean is a better representation of the observations, the uncertainties in the individual models are far high. There is no particular model that performed well in simulating the historical climate of Southeast Asia. There seems to be no significant influence of the spatial resolutions of the models on the quality of simulation, despite the view that higher resolution models fare better. The study results emphasize on careful consideration of models for impact studies and the need to improve the next generation of models in their ability to simulate regional climates better.

Methods for freshwater riverine input into regional ocean models

NASA Astrophysics Data System (ADS)

Herzfeld, M.

2015-06-01

The input of freshwater at the coast in regional models is a non-trivial exercise that has been studied extensively in the past. Several issues are of relevance; firstly, estuaries process water properties along their length, so that while freshwater may enter at the estuary head, it is no longer fresh at the mouth. Secondly, models create a numerical response that results in excessive upstream or offshore transport compared to what is typically observed. The cause of this has been traced to the lack of landward flow at the coast where freshwater is input. In this study we assess the performance of various methods of freshwater input in coarse resolution regional models where the estuary cannot be explicitly resolved, and present a formulation that attempts to account for upstream flow in the salt wedge and in-estuary mixing that elevates salinity at the mouth.

Empirical estimates to reduce modeling uncertainties of soil organic carbon in permafrost regions: a review of recent progress and remaining challenges

USGS Publications Warehouse

Mishra, U.; Jastrow, J.D.; Matamala, R.; Hugelius, G.; Koven, C.D.; Harden, Jennifer W.; Ping, S.L.; Michaelson, G.J.; Fan, Z.; Miller, R.M.; McGuire, A.D.; Tarnocai, C.; Kuhry, P.; Riley, W.J.; Schaefer, K.; Schuur, E.A.G.; Jorgenson, M.T.; Hinzman, L.D.

2013-01-01

The vast amount of organic carbon (OC) stored in soils of the northern circumpolar permafrost region is a potentially vulnerable component of the global carbon cycle. However, estimates of the quantity, decomposability, and combustibility of OC contained in permafrost-region soils remain highly uncertain, thereby limiting our ability to predict the release of greenhouse gases due to permafrost thawing. Substantial differences exist between empirical and modeling estimates of the quantity and distribution of permafrost-region soil OC, which contribute to large uncertainties in predictions of carbon–climate feedbacks under future warming. Here, we identify research challenges that constrain current assessments of the distribution and potential decomposability of soil OC stocks in the northern permafrost region and suggest priorities for future empirical and modeling studies to address these challenges.

Forecasting the regional distribution and sufficiency of physicians in Japan with a coupled system dynamics-geographic information system model.

PubMed

Ishikawa, Tomoki; Fujiwara, Kensuke; Ohba, Hisateru; Suzuki, Teppei; Ogasawara, Katsuhiko

2017-09-12

In Japan, the shortage of physicians has been recognized as a major medical issue. In our previous study, we reported that the absolute shortage will be resolved in the long term, but maldistribution among specialties will persist. To address regional shortage, several Japanese medical schools increased existing quota and established "regional quotas." This study aims to assist policy makers in designing effective policies; we built a model for forecasting physician numbers by region to evaluate future physician supply-demand balances. For our case study, we selected Hokkaido Prefecture in Japan, a region displaying disparities in healthcare services availability between urban and rural areas. We combined a system dynamics (SD) model with geographic information system (GIS) technology to analyze the dynamic change in spatial distribution of indicators. For Hokkaido overall and for each secondary medical service area (SMSA) within the prefecture, we analyzed the total number of practicing physicians. For evaluating absolute shortage and maldistribution, we calculated sufficiency levels and Gini coefficient. Our study covered the period 2010-2030 in 5-year increments. According to our forecast, physician shortage in Hokkaido Prefecture will largely be resolved by 2020. Based on current policies, we forecast that four SMSAs in Hokkaido will continue to experience physician shortages past that date, but only one SMSA would still be understaffed in 2030. The results show the possibility that diminishing imbalances between SMSAs would not necessarily mean that regional maldistribution would be eliminated, as seen from the sufficiency levels of the various SMSAs. Urgent steps should be taken to place doctors in areas where our forecasting model predicts that physician shortages could occur in the future.

An experimental and numerical study of diffusion flames in cross-flow and quiescent environment at smoke point condition

NASA Astrophysics Data System (ADS)

Goh, Sien Fong

An experimental and numerical study of a turbulent smoke point diffusion flame in a quiescent and cross-flow condition was performed. The fuel mass flow rate of a turbulent smoke point flame was determined at a quiescent condition and in cross-flow with velocity ranging from 2 to 4 m/s. This fuel mass flow rate is defined as the Critical Fuel Mass Flow Rate (CFMFR). At a fuel mass flow rate below the CFMFR the flame produces smoke. In the dilution study, an amount of inert gas (nitrogen) was added to the fuel stream to achieve the smoke point condition for ten different fractions of CFMFR. From this dilution study, three regions were defined, the chemically-dominated region, transition region, and momentum-dominated region. The first objective of this study was to determine the factors behind the distinction of these three regions. The second objective was to understand the effect of cross-flow velocity on the smoke point flame structure. The flame temperature, radiation, geometrical dimension of flame, velocity, and global emissions and in-flame species concentration were measured. The third objective was to study a numerical model that can simulate the turbulent smoke point flame structure. The dilution study showed that the flames in quiescent condition and in the 3.5 and 4 m/s cross-flow condition had the chemically-dominated region at 5% to 20% CFMFR, the transition region at 20% to 40% CFMFR, and the momentum-dominated region at 40% to 100% CFMFR. On the other hand, the flame in cross-flow of 2 to 3 m/s showed the chemically-dominated region at 5% to 10% CFMFR, the transition region at 10% to 30% CFMFR, and the momentum-dominated region at 30% to 100% CFMFR. The chemically-dominated flame had a sharp dual-peak structure for the flame temperature, CO2 and NO concentration profiles at 25% and 50% flame length. However, the momentum-dominated region flame exhibited a dual peak structure only at 25% flame length. The decrease of flow rate from 30% to 10% CFMFR showed an increase of flame length. The LII study showed that the soot concentration increased with the decrease of the turbulence intensity in the momentum dominated region (tested on the 100% and 60% CFMFR). The cross-flow velocity had a non-monotonic effects on the flame. The evidences could be observed from the flame length and the soot concentration results. The flame length showed a decrease when the cross-flow velocity increased from 2 to 3 m/s. The numerical model was fairly adequate in qualitatively predicting a smoke point turbulent diffusion flame structure in a cross-flow and quiescent condition. The model failed in the prediction of a laminar flame. The model showed a good agreement between experimental and numerical results for O 2 concentration and flame temperature. (Abstract shortened by UMI.)

The Hydrodynamical Models of the Cometary Compact HII Region

NASA Astrophysics Data System (ADS)

Zhu, Feng-Yao; Zhu, Qing-Feng; Li, Juan; Zhang, Jiang-Shui; Wang, Jun-Zhi

2015-10-01

We have developed a full numerical method to study the gas dynamics of cometary ultracompact H ii regions, and associated photodissociation regions (PDRs). The bow-shock and champagne-flow models with a 40.9/21.9 M⊙ star are simulated. In the bow-shock models, the massive star is assumed to move through dense (n = 8000 cm-3) molecular material with a stellar velocity of 15 km s-1. In the champagne-flow models, an exponential distribution of density with a scale height of 0.2 pc is assumed. The profiles of the [Ne ii] 12.81 μm and H2 S(2) lines from the ionized regions and PDRs are compared for two sets of models. In champagne-flow models, emission lines from the ionized gas clearly show the effect of acceleration along the direction toward the tail due to the density gradient. The kinematics of the molecular gas inside the dense shell are mainly due to the expansion of the H ii region. However, in bow-shock models the ionized gas mainly moves in the same direction as the stellar motion. The kinematics of the molecular gas inside the dense shell simply reflects the motion of the dense shell with respect to the star. These differences can be used to distinguish two sets of models.

A Preliminary Synthesis of Modeled Climate Change Impacts on U.S. Regional Ozone Concentrations

EPA Science Inventory

This paper provides a synthesis of results that have emerged from recent modeling studies of the potential sensitivity of U.S. regional ozone (O₃) concentrations to global climate change (c. 2050). This research has been carried out under the auspices of an ongoing U....

Death Valley regional groundwater flow system, Nevada and California-Hydrogeologic framework and transient groundwater flow model

USGS Publications Warehouse

Belcher, Wayne R.; Sweetkind, Donald S.

2010-01-01

A numerical three-dimensional (3D) transient groundwater flow model of the Death Valley region was developed by the U.S. Geological Survey for the U.S. Department of Energy programs at the Nevada Test Site and at Yucca Mountain, Nevada. Decades of study of aspects of the groundwater flow system and previous less extensive groundwater flow models were incorporated and reevaluated together with new data to provide greater detail for the complex, digital model. A 3D digital hydrogeologic framework model (HFM) was developed from digital elevation models, geologic maps, borehole information, geologic and hydrogeologic cross sections, and other 3D models to represent the geometry of the hydrogeologic units (HGUs). Structural features, such as faults and fractures, that affect groundwater flow also were added. The HFM represents Precambrian and Paleozoic crystalline and sedimentary rocks, Mesozoic sedimentary rocks, Mesozoic to Cenozoic intrusive rocks, Cenozoic volcanic tuffs and lavas, and late Cenozoic sedimentary deposits of the Death Valley regional groundwater flow system (DVRFS) region in 27 HGUs. Information from a series of investigations was compiled to conceptualize and quantify hydrologic components of the groundwater flow system within the DVRFS model domain and to provide hydraulic-property and head-observation data used in the calibration of the transient-flow model. These studies reevaluated natural groundwater discharge occurring through evapotranspiration (ET) and spring flow; the history of groundwater pumping from 1913 through 1998; groundwater recharge simulated as net infiltration; model boundary inflows and outflows based on regional hydraulic gradients and water budgets of surrounding areas; hydraulic conductivity and its relation to depth; and water levels appropriate for regional simulation of prepumped and pumped conditions within the DVRFS model domain. Simulation results appropriate for the regional extent and scale of the model were provided by acquiring additional data, by reevaluating existing data using current technology and concepts, and by refining earlier interpretations to reflect the current understanding of the regional groundwater flow system. Groundwater flow in the Death Valley region is composed of several interconnected, complex groundwater flow systems. Groundwater flow occurs in three subregions in relatively shallow and localized flow paths that are superimposed on deeper, regional flow paths. Regional groundwater flow is predominantly through a thick Paleozoic carbonate rock sequence affected by complex geologic structures from regional faulting and fracturing that can enhance or impede flow. Spring flow and ET are the dominant natural groundwater discharge processes. Groundwater also is withdrawn for agricultural, commercial, and domestic uses. Groundwater flow in the DVRFS was simulated using MODFLOW-2000, the U.S. Geological Survey 3D finitedifference modular groundwater flow modeling code that incorporates a nonlinear least-squares regression technique to estimate aquifer parameters. The DVRFS model has 16 layers of defined thickness, a finite-difference grid consisting of 194 rows and 160 columns, and uniform cells 1,500 meters (m) on each side. Prepumping conditions (before 1913) were used as the initial conditions for the transient-state calibration. The model uses annual stress periods with discrete recharge and discharge components. Recharge occurs mostly from infiltration of precipitation and runoff on high mountain ranges and from a small amount of underflow from adjacent basins. Discharge occurs primarily through ET and spring discharge (both simulated as drains) and water withdrawal by pumping and, to a lesser amount, by underflow to adjacent basins simulated by constant-head boundaries. All parameter values estimated by the regression are reasonable and within the range of expected values. The simulated hydraulic heads of the final calibrated transient mode

Do Online Learning Patterns Exhibit Regional and Demographic Differences?

ERIC Educational Resources Information Center

Hsieh, Tsui-Chuan; Yang, Chyan

2012-01-01

This paper used a multi-level latent class model to evaluate whether online learning patterns exhibit regional differences and demographics. This study discovered that the Internet learning pattern consists of five segments, and the region of Taiwan is divided into two segments and further found that both the user and the regional segments are…

Stochastic Earthquake Rupture Modeling Using Nonparametric Co-Regionalization

NASA Astrophysics Data System (ADS)

Lee, Kyungbook; Song, Seok Goo

2017-09-01

Accurate predictions of the intensity and variability of ground motions are essential in simulation-based seismic hazard assessment. Advanced simulation-based ground motion prediction methods have been proposed to complement the empirical approach, which suffers from the lack of observed ground motion data, especially in the near-source region for large events. It is important to quantify the variability of the earthquake rupture process for future events and to produce a number of rupture scenario models to capture the variability in simulation-based ground motion predictions. In this study, we improved the previously developed stochastic earthquake rupture modeling method by applying the nonparametric co-regionalization, which was proposed in geostatistics, to the correlation models estimated from dynamically derived earthquake rupture models. The nonparametric approach adopted in this study is computationally efficient and, therefore, enables us to simulate numerous rupture scenarios, including large events ( M > 7.0). It also gives us an opportunity to check the shape of true input correlation models in stochastic modeling after being deformed for permissibility. We expect that this type of modeling will improve our ability to simulate a wide range of rupture scenario models and thereby predict ground motions and perform seismic hazard assessment more accurately.

Modeling wind energy potential in a data-poor region: A geographic information systems model for Iraq

NASA Astrophysics Data System (ADS)

Khayyat, Abdulkareem Hawta Abdullah Kak Ahmed

Scope and Method of Study: Most developing countries, including Iraq, have very poor wind data. Existing wind speed measurements of poor quality may therefore be a poor guide to where to look for the best wind resources. The main focus of this study is to examine how effectively a GIS spatial model estimates wind power potential in regions where high-quality wind data are very scarce, such as Iraq. The research used a mixture of monthly and hourly wind data from 39 meteorological stations. The study applied spatial analysis statistics and GIS techniques in modeling wind power potential. The model weighted important human, environmental and geographic factors that impact wind turbine siting, such as roughness length, land use⪉nd cover type, airport locations, road access, transmission lines, slope and aspect. Findings and Conclusions: The GIS model provided estimations for wind speed and wind power density and identified suitable areas for wind power projects. Using a high resolution (30*30m) digital elevation model DEM improved the GIS wind suitability model. The model identified areas suitable for wind farm development on different scales. The model showed that there are many locations available for large-scale wind turbines in the southern part of Iraq. Additionally, there are many places in central and northern parts (Kurdistan Region) for smaller scale wind turbine placement.

AgMIP Coordinated Global and Regional Assessments for 1.5°C and 2.0°C

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2017-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study performs a proof-of-concept of the CGRA to demonstrate advantages and challenges of the framework. This effort responds to the request by UNFCCC for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), HAPPI and CMIP5 ensemble scenarios, global gridded crop models, global agricultural economic models, site-based crop models, and within-country regional economic models. CGRA results show that at the global scale, mixed areas of positive and negative simulated yield changes, with declines in some breadbasket regions led to overall declines in productivity at both 1.5°C and 2.0°C. These projected global yield changes resulted in increases in prices of major commodities in a global economic model. Simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on region and crop, but with more negative effects on productivity at 2.0°C than at 1.5°C for the most part. In conjunction with price changes from the global economics models, these productivity declines resulted generally in small positive effects on regional farm livelihoods, showing that farming systems should continue to be viable under high mitigation scenarios. CGRA protocols focus on how mitigation actions and effects differ across scales, with main mechanisms studied in the integrated assessment models being policies and technologies that reduce direct non-CO2 emissions from agriculture, reduce CO2 emissions from land use change and forest sink enhancement, and utilize biomass for energy production. At regional scales, increasing soil organic carbon (SOC) is of active interest.

Regionalizing Africa: Patterns of Precipitation Variability in Observations and Global Climate Models

NASA Technical Reports Server (NTRS)

Badr, Hamada S.; Dezfuli, Amin K.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.

2016-01-01

Many studies have documented dramatic climatic and environmental changes that have affected Africa over different time scales. These studies often raise questions regarding the spatial extent and regional connectivity of changes inferred from observations and proxies and/or derived from climate models. Objective regionalization offers a tool for addressing these questions. To demonstrate this potential, applications of hierarchical climate regionalizations of Africa using observations and GCM historical simulations and future projections are presented. First, Africa is regionalized based on interannual precipitation variability using Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data for the period 19812014. A number of data processing techniques and clustering algorithms are tested to ensure a robust definition of climate regions. These regionalization results highlight the seasonal and even month-to-month specificity of regional climate associations across the continent, emphasizing the need to consider time of year as well as research question when defining a coherent region for climate analysis. CHIRPS regions are then compared to those of five GCMs for the historic period, with a focus on boreal summer. Results show that some GCMs capture the climatic coherence of the Sahel and associated teleconnections in a manner that is similar to observations, while other models break the Sahel into uncorrelated subregions or produce a Sahel-like region of variability that is spatially displaced from observations. Finally, shifts in climate regions under projected twenty-first-century climate change for different GCMs and emissions pathways are examined. A projected change is found in the coherence of the Sahel, in which the western and eastern Sahel become distinct regions with different teleconnections. This pattern is most pronounced in high-emissions scenarios.

Modeling of Trans-boundary Transport of Air Pollutants in the California-Mexico Border Region during Cal-Mex 2010

NASA Astrophysics Data System (ADS)

Bei, N.; Zavala, M. A.; Lei, W.; Li, G.; Molina, L. T.

2010-12-01

The US and Mexico share a common air basin along the ~200 km border between California and Baja California. The economical activities in this region are heavily influenced by the international trade and commerce between Mexico and the US that mainly occurs through the borders of the sister cities of San Diego-Tijuana and Calexico-Mexicali. The diversity and differences in the characteristics of emissions sources of air pollutants in the California-Mexico border region make this an important area for the study of the chemistry and trans-boundary transport of air pollutants. During May-June of 2010, the Cal-Mex 2010 field campaign included a series of measurements aimed at characterizing the emissions from major sources in the California-Mexico border region and assessing the possible impacts of these emissions on local and regional air quality. In this work we will present the results of the use of the Comprehensive Air quality model with extensions (CAMx) in a modeling domain that includes the sister cities of San Diego-Tijuana and Calexico-Mexicali for studying events of trans-boundary transport of air pollutants during Cal-Mex 2010. The measurements obtained during the Cal-Mex 2010 field campaign are used in the evaluation of the model performance and in the design of air quality improvement policies in the California-Mexico border region.

Simulation of Boreal Ecosystem Carbon and Water Budgets: Scaling from Local to Regional Extents

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1997-01-01

A coupled water and energy balance model is developed. This model can predict the partitioning of water and energy between major source, sink and storage elements within the Boreal-Ecosystem-Atmospheric Study (BOREAS) areas. The results of testing the model against data collected at BOREAS tower sites during Intensive Field Campaigns and remotely sensed data collected across the BOREAS region are presented.

Disagreement between Hydrological and Land Surface models on the water budgets in the Arctic: why is this and which of them is right?

NASA Astrophysics Data System (ADS)

Blyth, E.; Martinez-de la Torre, A.; Ellis, R.; Robinson, E.

2017-12-01

The fresh-water budget of the Artic region has a diverse range of impacts: the ecosystems of the region, ocean circulation response to Arctic freshwater, methane emissions through changing wetland extent as well as the available fresh water for human consumption. But there are many processes that control the budget including a seasonal snow packs building and thawing, freezing soils and permafrost, extensive organic soils and large wetland systems. All these processes interact to create a complex hydrological system. In this study we examine a suite of 10 models that bring all those processes together in a 25 year reanalysis of the global water budget. We assess their performance in the Arctic region. There are two approaches to modelling fresh-water flows at large scales, referred to here as `Hydrological' and `Land Surface' models. While both approaches include a physically based model of the water stores and fluxes, the Land Surface models links the water flows to an energy-based model for processes such as snow melt and soil freezing. This study will analyse the impact of that basic difference on the regional patterns of evapotranspiration, runoff generation and terrestrial water storage. For the evapotranspiration, the Hydrological models tend to have a bigger spatial range in the model bias (difference to observations), implying greater errors compared to the Land-Surface models. For instance, some regions such as Eastern Siberia have consistently lower Evaporation in the Hydrological models than the Land Surface models. For the Runoff however, the results are the other way round with a slightly higher spatial range in bias for the Land Surface models implying greater errors than the Hydrological models. A simple analysis would suggest that Hydrological models are designed to get the runoff right, while Land Surface models designed to get the evapotranspiration right. Tracing the source of the difference suggests that the difference comes from the treatment of snow and evapotranspiration. The study reveals that expertise in the role of snow on runoff generation and evapotranspiration in Hydrological and Land Surface could be combined to improve the representation of the fresh water flows in the Arctic in both approaches. Improved observations are essential to make these modelling advances possible.

Modeling Hydrological Processes in New Mexico-Texas-Mexico Border Region

NASA Astrophysics Data System (ADS)

Samimi, M.; Jahan, N. T.; Mirchi, A.

2017-12-01

Efficient allocation of limited water resources to competing use sectors is becoming increasingly critical for water-scarce regions. Understanding natural and anthropogenic processes affecting hydrological processes is key for efficient water management. We used Soil and Water Assessment Tool (SWAT) to model governing hydrologic processes in New Mexico-Texas-Mexico border region. Our study area includes the Elephant Butte Irrigation District (EBID), which manages water resources to support irrigated agriculture. The region is facing water resources challenges associated with chronic water scarcity, over-allocation, diminishing water supply, and growing water demand. Agricultural activities rely on conjunctive use of Rio Grande River water supply and groundwater withdrawal. The model is calibrated and validated under baseline conditions in the arid and semi-arid climate in order to evaluate potential impacts of climate change on the agricultural sector and regional water availability. We highlight the importance of calibrating the crop growth parameters, evapotranspiration, and groundwater recharge to provide a realistic representation of the hydrological processes and water availability in the region. Furthermore, limitations of the model and its utility to inform stakeholders will be discussed.

Comparison of liquid rocket engine base region heat flux computations using three turbulence models

NASA Technical Reports Server (NTRS)

Kumar, Ganesh N.; Griffith, Dwaine O., II; Prendergast, Maurice J.; Seaford, C. M.

1993-01-01

The flow in the base region of launch vehicles is characterized by flow separation, flow reversals, and reattachment. Computation of the convective heat flux in the base region and on the nozzle external surface of Space Shuttle Main Engine and Space Transportation Main Engine (STME) is an important part of defining base region thermal environments. Several turbulence models were incorporated in a CFD code and validated for flow and heat transfer computations in the separated and reattaching regions associated with subsonic and supersonic flows over backward facing steps. Heat flux computations in the base region of a single STME engine and a single S1C engine were performed using three different wall functions as well as a renormalization-group based k-epsilon model. With the very limited data available, the computed values are seen to be of the right order of magnitude. Based on the validation comparisons, it is concluded that all the turbulence models studied have predicted the reattachment location and the velocity profiles at various axial stations downstream of the step very well.

MODIS land cover uncertainty in regional climate simulations

NASA Astrophysics Data System (ADS)

Li, Xue; Messina, Joseph P.; Moore, Nathan J.; Fan, Peilei; Shortridge, Ashton M.

2017-12-01

MODIS land cover datasets are used extensively across the climate modeling community, but inherent uncertainties and associated propagating impacts are rarely discussed. This paper modeled uncertainties embedded within the annual MODIS Land Cover Type (MCD12Q1) products and propagated these uncertainties through the Regional Atmospheric Modeling System (RAMS). First, land cover uncertainties were modeled using pixel-based trajectory analyses from a time series of MCD12Q1 for Urumqi, China. Second, alternative land cover maps were produced based on these categorical uncertainties and passed into RAMS. Finally, simulations from RAMS were analyzed temporally and spatially to reveal impacts. Our study found that MCD12Q1 struggles to discriminate between grasslands and croplands or grasslands and barren in this study area. Such categorical uncertainties have significant impacts on regional climate model outputs. All climate variables examined demonstrated impact across the various regions, with latent heat flux affected most with a magnitude of 4.32 W/m2 in domain average. Impacted areas were spatially connected to locations of greater land cover uncertainty. Both biophysical characteristics and soil moisture settings in regard to land cover types contribute to the variations among simulations. These results indicate that formal land cover uncertainty analysis should be included in MCD12Q1-fed climate modeling as a routine procedure.

A multiscale quantum mechanics/electromagnetics method for device simulations.

PubMed

Yam, ChiYung; Meng, Lingyi; Zhang, Yu; Chen, GuanHua

2015-04-07

Multiscale modeling has become a popular tool for research applying to different areas including materials science, microelectronics, biology, chemistry, etc. In this tutorial review, we describe a newly developed multiscale computational method, incorporating quantum mechanics into electronic device modeling with the electromagnetic environment included through classical electrodynamics. In the quantum mechanics/electromagnetics (QM/EM) method, the regions of the system where active electron scattering processes take place are treated quantum mechanically, while the surroundings are described by Maxwell's equations and a semiclassical drift-diffusion model. The QM model and the EM model are solved, respectively, in different regions of the system in a self-consistent manner. Potential distributions and current densities at the interface between QM and EM regions are employed as the boundary conditions for the quantum mechanical and electromagnetic simulations, respectively. The method is illustrated in the simulation of several realistic systems. In the case of junctionless field-effect transistors, transfer characteristics are obtained and a good agreement between experiments and simulations is achieved. Optical properties of a tandem photovoltaic cell are studied and the simulations demonstrate that multiple QM regions are coupled through the classical EM model. Finally, the study of a carbon nanotube-based molecular device shows the accuracy and efficiency of the QM/EM method.

Tectonic stress pattern in the Chinese Mainland from the inversion of focal mechanism data

NASA Astrophysics Data System (ADS)

Wei, Ju; Weifeng, Sun; Xiaojing, Ma

2017-04-01

The tectonic stress pattern in the Chinese Mainland and kinematic models have been subjected to much debate. In the past several decades, several tectonic stress maps have been figured out; however, they generally suffer a poor time control. In the present study, 421 focal mechanism data up to January 2010 were compiled from the Global/Harvard CMT catalogue, and 396 of them were grouped into 23 distinct regions in function of geographic proximity. Reduced stress tensors were obtained from formal stress inversion for each region. The results indicated that, in the Chinese Mainland, the directions of maximum principal stress were ˜NE-SW-trending in the northeastern region, ˜NEE-SWW-trending in the North China region, ˜N-S-trending in western Xinjiang, southern Tibet and the southern Yunnan region, ˜NNE-SSW-trending in the northern Tibet and Qinghai region, ˜NW-SE-trending in Gansu region, and ˜E-W-trending in the western Sichuan region. The average tectonic stress regime was strike-slip faulting (SS) in the eastern Chinese Mainland and northern Tibet region, normal faulting (NF) in the southern Tibet, western Xinjiang and Yunnan region, and thrust faulting (TF) in most regions of Xinjiang, Qinghai and Gansu. The results of the present study combined with GPS velocities in the Chinese Mainland supported and could provide new insights into previous tectonic models (e.g., the extrusion model). From the perspective of tectonics, the mutual actions among the Eurasian plate, Pacific plate and Indian plate caused the present-day tectonic stress field in the Chinese Mainland.

Influence of different abutment diameter of implants on the peri-implant stress in the crestal bone: A three-dimensional finite element analysis--In vitro study.

PubMed

Aradya, Anupama; Kumar, U Krishna; Chowdhary, Ramesh

2016-01-01

The study was designed to evaluate and compare stress distribution in transcortical section of bone with normal abutment and platform switched abutment under vertical and oblique forces in posterior mandible region. A three-dimensional finite element model was designed using ANSYS 13.0 software. The type of bone selection for the model was made of type II mandibular bone, having cortical bone thickness ranging from 0.595 mm to 1.515 mm with the crestal region measuring 1.5 mm surrounding dense trabecular bone. The implant will be modulated at 5 mm restorative platform and tapering down to 4.5 mm wide at the threads, 13 mm long with an abutment 3 mm in height. The models will be designed for two situations: (1) An implant with a 5 mm diameter abutment representing a standard platform in the posterior mandible region. (2) An implant with a 4.5 mm diameter abutment representing platform switching in the posterior mandible region. Force application was performed in both oblique and vertical conditions using 100 N as a representative masticatory force. For oblique loading, a force of 100 N was applied at 15° from the vertical axis. von Mises stress analysis was evaluated. The results of the study showed cortical stress in the conventional and platform switching model under oblique forces were 59.329 MPa and 39.952 MPa, respectively. Cortical stress in the conventional and platform switching model under vertical forces was 13.914 MPa and 12.793 MPa, respectively. Results from this study showed the platform switched abutment led to relative decrease in von Mises stress in transcortical section of bone compared to normal abutment under vertical and oblique forces in posterior mandible region.

Sensitivity experiments of a regional climate model to the different convective schemes over Central Africa

NASA Astrophysics Data System (ADS)

Armand J, K. M.

2017-12-01

In this study, version 4 of the regional climate model (RegCM4) is used to perform 6 years simulation including one year for spin-up (from January 2001 to December 2006) over Central Africa using four convective schemes: The Emmanuel scheme (MIT), the Grell scheme with Arakawa-Schulbert closure assumption (GAS), the Grell scheme with Fritsch-Chappell closure assumption (GFC) and the Anthes-Kuo scheme (Kuo). We have investigated the ability of the model to simulate precipitation, surface temperature, wind and aerosols optical depth. Emphasis in the model results were made in December-January-February (DJF) and July-August-September (JAS) periods. Two subregions have been identified for more specific analysis namely: zone 1 which corresponds to the sahel region mainly classified as desert and steppe and zone 2 which is a region spanning the tropical rain forest and is characterised by a bimodal rain regime. We found that regardless of periods or simulated parameters, MIT scheme generally has a tendency to overestimate. The GAS scheme is more suitable in simulating the aforementioned parameters, as well as the diurnal cycle of precipitations everywhere over the study domain irrespective of the season. In JAS, model results are similar in the representation of regional wind circulation. Apart from the MIT scheme, all the convective schemes give the same trends in aerosols optical depth simulations. Additional experiment reveals that the use of BATS instead of Zeng scheme to calculate ocean flux appears to improve the quality of the model simulations.

Changes in the carbon cycle of northern Eurasia simulated by process models

NASA Astrophysics Data System (ADS)

Rawlins, M. A.

2013-12-01

Pronounced warming across the northern high latitudes is impacting water and carbon cycles and raising concern over possible feedbacks to global climate. Recent model studied point toward a weakening of the terrestrial land carbon sink across the northern high latitudes, one notable manifestation of a warming Arctic. We explore links between regional climate and the carbon cycle using data from models participating in the Vulnerability of Permafrost Carbon Research Coordination Network (RCN). The domain of interest is the drainage basin within the Northern Eurasia Earth Science Partnership Initiative (NEESPI) region. Model outputs examined include gross primary production (GPP), heterotrophic respiration (RH), net ecosystem exchange (NEE), and total soil carbon storage. Mean flux budgets and their changes over the period 1960-2009 are calculated from the model estimates for the entire NEESPI region and for each major land cover category within the region. Use of an independent model, which captures well the spatial pattern in soil freeze/thaw dynamics, indicates that the reduction in permafrost extent over the NEESPI basin was 4-6% over recent decades. Modeled influences of permafrost thaw on the region's water and carbon cycles are evaluated in the context of recent measurements. Estimates of the flux of CO2 due to fire are also examined in order to better understand how these disturbances are altering regional carbon sink/source dynamics.

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M.; Palchak, Joseph D; McBennett, Brendan

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinatedmore » operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: -To better anticipate, understand, and mitigate system constraints that could affect RE integration; and - To provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission expansion pathways. The model developed for this study provides a rigorous framework for future work and can be updated with the characteristics of new capacity as more information on the future power system is known.« less

Tectonic controls on magmatism in the Geysers-Clear Lake region: Evidence from new geophysical models

USGS Publications Warehouse

Stanley, W.D.; Benz, H.M.; Walters, M.A.; Villasenor, A.; Rodriguez, B.D.

1998-01-01

In order to study magmatism and geothermal systems in The Geysers-Clear Lake region, we developed a detailed three-dimensional tomographic velocity model based on local earthquakes. This high-resolution model resolves the velocity structure of the crust in the region to depths of approximately 12 km. The most significant velocity contrasts in The Geysers-Clear Lake region occur in the steam production area, where high velocities are associated with a Quaternary granitic pluton, and in the Mount Hannah region, where low velocities occur in a 5-km-thick section of Mesozoic argillites. In addition, a more regional tomographic model was developed using traveltimes from earthquakes covering most of northern California. This regional model sampled the whole crust, but at a lower resolution than the local model. The regional model outlines low velocities at depths of 8-12 km in The Geysers-Clear Lake area, which extend eastward to the Coast Range thrust. These low velocities are inferred to be related to unmetamorphosed Mesozoic sedimentary rocks. In addition, the regional velocity model indicates high velocities in the lower crust beneath the Clear Lake volcanic field, which we interpret to be associated with mafic underplating. No large silicic magma chamber is noted in either the local or regional tomographic models. A three-dimensional gravity model also has been developed in the area of the tomographic imaging. Our gravity model demonstrates that all density contrasts can be accounted for in the upper 5-7 km of the crust. Two-dimensional magnetotelluric models of data from a regional, east-west profile indicate high resistivities associated with the granitic pluton in The Geysers production area and low resistivities in the low-velocity section of Mesozoic argillites near Mount Hannah. No indication of midcrustal magma bodies is present in the magnetotelluric data. On the basis of heat flow and geologic evidence, Holocene intrusive activity is thought to have occurred near the Northwest Geysers, Mount Hannah, Sulphur Bank Mine, and perhaps other areas. The geophysical data provide no conclusive evidence for such activity, but the detailed velocity model is suggestive of intrusive activity near Mount Hannah similar to that in the 'felsite' of The Geysers production area. The geophysical models, seismicity patterns, distribution of volcanic vents, heat flow, and other data indicate that small, young intrusive bodies that were injected along a northeast trend from The Geysers to Clear Lake probably control the thermal regime.

Impact of high resolution land surface initialization in Indian summer monsoon simulation using a regional climate model

NASA Astrophysics Data System (ADS)

Unnikrishnan, C. K.; Rajeevan, M.; Rao, S. Vijaya Bhaskara

2016-06-01

The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years over Indian summer monsoon region is investigated. Two sets of regional climate model simulations are performed, one with a coarse resolution land surface initial conditions and second one used a high resolution land surface data for initial condition. The results show that all monsoon years respond differently to the high resolution land surface initialization. The drought monsoon year 2009 and extended break periods were more sensitive to the high resolution land surface initialization. These results suggest that the drought monsoon year predictions can be improved with high resolution land surface initialization. Result also shows that there are differences in the response to the land surface initialization within the monsoon season. Case studies of heat wave and a monsoon depression simulation show that, the model biases were also improved with high resolution land surface initialization. These results show the need for a better land surface initialization strategy in high resolution regional models for monsoon forecasting.

Regional modelling of polycyclic aromatic hydrocarbons: WRF-Chem-PAH model development and East Asia case studies

NASA Astrophysics Data System (ADS)

Mu, Qing; Lammel, Gerhard; Gencarelli, Christian N.; Hedgecock, Ian M.; Chen, Ying; Přibylová, Petra; Teich, Monique; Zhang, Yuxuan; Zheng, Guangjie; van Pinxteren, Dominik; Zhang, Qiang; Herrmann, Hartmut; Shiraiwa, Manabu; Spichtinger, Peter; Su, Hang; Pöschl, Ulrich; Cheng, Yafang

2017-10-01

Polycyclic aromatic hydrocarbons (PAHs) are hazardous pollutants, with increasing emissions in pace with economic development in East Asia, but their distribution and fate in the atmosphere are not yet well understood. We extended the regional atmospheric chemistry model WRF-Chem (Weather Research Forecast model with Chemistry module) to comprehensively study the atmospheric distribution and the fate of low-concentration, slowly degrading semivolatile compounds. The WRF-Chem-PAH model reflects the state-of-the-art understanding of current PAHs studies with several new or updated features. It was applied for PAHs covering a wide range of volatility and hydrophobicity, i.e. phenanthrene, chrysene and benzo[a]pyrene, in East Asia. Temporally highly resolved PAH concentrations and particulate mass fractions were evaluated against observations. The WRF-Chem-PAH model is able to reasonably well simulate the concentration levels and particulate mass fractions of PAHs near the sources and at a remote outflow region of East Asia, in high spatial and temporal resolutions. Sensitivity study shows that the heterogeneous reaction with ozone and the homogeneous reaction with the nitrate radical significantly influence the fate and distributions of PAHs. The methods to implement new species and to correct the transport problems can be applied to other newly implemented species in WRF-Chem.

Study on embodied CO2 transfer between the Jing-Jin-Ji region and other regions in China: a quantification using an interregional input-output model.

PubMed

Chen, Mengmeng; Wu, Sanmang; Lei, Yalin; Li, Shantong

2018-05-01

Jing-Jin-Ji region (i.e., Beijing, Tianjin, and Hebei) is China's key development region, but it is also the leading and most serious air pollution region in China. High fossil fuel consumption is the major source of both carbon dioxide (CO 2 ) emissions and air pollutants. Therefore, it is important to reveal the source of CO 2 emissions to control the air pollution in the Jing-Jin-Ji region. In this study, an interregional input-output model was applied to quantitatively estimate the embodied CO 2 transfer between Jing-Jin-Ji region and other region in China using China's interregional input-output data in 2010. The results indicated that there was a significant difference in the production-based CO 2 emissions in China, and furthermore, the Jing-Jin-Ji region and its surrounding regions were the main regions of the production-based CO 2 emissions in China. Hebei Province exported a large amount of embodied CO 2 to meet the investment, consumption, and export demands of Beijing and Tianjin. The Jing-Jin-Ji regions exported a great deal of embodied CO 2 to the coastal provinces of southeast China and imported it from neighboring provinces.

Study of a mixed dispersal population dynamics model

DOE PAGES

Chugunova, Marina; Jadamba, Baasansuren; Kao, Chiu -Yen; ...

2016-08-27

In this study, we consider a mixed dispersal model with periodic and Dirichlet boundary conditions and its corresponding linear eigenvalue problem. This model describes the time evolution of a population which disperses both locally and non-locally. We investigate how long time dynamics depend on the parameter values. Furthermore, we study the minimization of the principal eigenvalue under the constraints that the resource function is bounded from above and below, and with a fixed total integral. Biologically, this minimization problem is motivated by the question of determining the optimal spatial arrangement of favorable and unfavorable regions for the species to diemore » out more slowly or survive more easily. Our numerical simulations indicate that the optimal favorable region tends to be a simply-connected domain. Numerous results are shown to demonstrate various scenarios of optimal favorable regions for periodic and Dirichlet boundary conditions.« less

A study of long-term trends in mineral dust aerosol distributions in Asia using a general circulation model

NASA Astrophysics Data System (ADS)

Mukai, Makiko; Nakajima, Teruyuki; Takemura, Toshihiko

2004-10-01

Dust events have been observed in Japan with high frequency since 2000. On the other hand, the frequency of dust storms is said to have decreased in the desert regions of China since about the middle of the 1970s. This study simulates dust storms and transportation of mineral dust aerosols in the east Asia region from 1981 to 2001 using an aerosol transport model, Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS), implemented in the Center for Climate System Research/National Institute for Environmental Studies atmospheric global circulation model, in order to investigate the main factors that control a dust event and its long-term variation. The model was forced to simulate a real atmospheric condition by a nudging technique using European Centre for Medium-Range Weather Forecasts reanalysis data on wind velocities, temperature, specific humidity, soil wetness, and snow depth. From a comparison between the long-term change in the dust emission and model parameters, it is found that the wind speed near the surface level had a significant influence on the dust emission, and snow is also an important factor in the early spring dust emission. The simulated results suggested that dust emissions from northeast China have a great impact on dust mass concentration in downwind regions, such as the cities of northeastern China, Korea, and Japan. When the frequency of dust events was high in Japan, a low-pressure system tended to develop over the northeast China region that caused strong winds. From 2000 to 2001 the simulated dust emission flux decreased in the Taklimakan desert and the northwestern part of China, while it increased in the Gobi desert and the northeastern part of China. Consequently, dust particles seem to be transported more from the latter region by prevailing westerlies in the springtime to downwind areas as actually observed. In spite of the similarity, however, there is still a large disagreement between observed and simulated dust frequencies and concentrations. A more realistic land surface and uplift mechanism of dust particles should be modeled to improve the model simulation. Desertification of the northeastern China region may be another reason for this disagreement.

Snow mass and river flows modelled using GRACE total water storage observations

NASA Astrophysics Data System (ADS)

Wang, S.

2017-12-01

Snow mass and river flow measurements are difficult and less accurate in cold regions due to the hash environment. Floods in cold regions are commonly a result of snowmelt during the spring break-up. Flooding is projected to increase with climate change in many parts of the world. Forecasting floods from snowmelt remains a challenge due to scarce and quality issues in basin-scale snow observations and lack of knowledge for cold region hydrological processes. This study developed a model for estimating basin-level snow mass (snow water equivalent SWE) and river flows using the total water storage (TWS) observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. The SWE estimation is based on mass balance approach which is independent of in situ snow gauge observations, thus largely eliminates the limitations and uncertainties with traditional in situ or remote sensing snow estimates. The model forecasts river flows by simulating surface runoff from snowmelt and the corresponding baseflow from groundwater discharge. Snowmelt is predicted using a temperature index model. Baseflow is predicted using a modified linear reservoir model. The model also quantifies the hysteresis between the snowmelt and the streamflow rates, or the lump time for water travel in the basin. The model was applied to the Red River Basin, the Mackenzie River Basin, and the Hudson Bay Lowland Basins in Canada. The predicted river flows were compared with the observed values at downstream hydrometric stations. The results were also compared to that for the Lower Fraser River obtained in a separate study to help better understand the roles of environmental factors in determining flood and their variations with different hydroclimatic conditions. This study advances the applications of space-based time-variable gravity measurements in cold region snow mass estimation, river flow and flood forecasting. It demonstrates a relatively simple method that only needs GRACE TWS and temperature data for river flow or flood forecasting. The model can be particularly useful for regions with spare observation networks, and can be used in combination with other available methods to help improve the accuracy in river flow and flood forecasting over cold regions.

Reconstructing a spatially heterogeneous epidemic: Characterising the geographic spread of 2009 A/H1N1pdm infection in England

NASA Astrophysics Data System (ADS)

Birrell, Paul J.; Zhang, Xu-Sheng; Pebody, Richard G.; Gay, Nigel J.; de Angelis, Daniela

2016-07-01

Understanding how the geographic distribution of and movements within a population influence the spatial spread of infections is crucial for the design of interventions to curb transmission. Existing knowledge is typically based on results from simulation studies whereas analyses of real data remain sparse. The main difficulty in quantifying the spatial pattern of disease spread is the paucity of available data together with the challenge of incorporating optimally the limited information into models of disease transmission. To address this challenge the role of routine migration on the spatial pattern of infection during the epidemic of 2009 pandemic influenza in England is investigated here through two modelling approaches: parallel-region models, where epidemics in different regions are assumed to occur in isolation with shared characteristics; and meta-region models where inter-region transmission is expressed as a function of the commuter flux between regions. Results highlight that the significantly less computationally demanding parallel-region approach is sufficiently flexible to capture the underlying dynamics. This suggests that inter-region movement is either inaccurately characterized by the available commuting data or insignificant once its initial impact on transmission has subsided.

An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)

NASA Astrophysics Data System (ADS)

Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain

2003-12-01

Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright

Computational complexity of symbolic dynamics at the onset of chaos

NASA Astrophysics Data System (ADS)

Lakdawala, Porus

1996-05-01

In a variety of studies of dynamical systems, the edge of order and chaos has been singled out as a region of complexity. It was suggested by Wolfram, on the basis of qualitative behavior of cellular automata, that the computational basis for modeling this region is the universal Turing machine. In this paper, following a suggestion of Crutchfield, we try to show that the Turing machine model may often be too powerful as a computational model to describe the boundary of order and chaos. In particular we study the region of the first accumulation of period doubling in unimodal and bimodal maps of the interval, from the point of view of language theory. We show that in relation to the ``extended'' Chomsky hierarchy, the relevant computational model in the unimodal case is the nested stack automaton or the related indexed languages, while the bimodal case is modeled by the linear bounded automaton or the related context-sensitive languages.

Vertically inhomogeneous models of the upper crust for the seismoactive region of western Bohemia

NASA Astrophysics Data System (ADS)

Malek, J.; Jansky, J.; Novotny, O.; Rossler, D.

2003-04-01

In the framework of the CELEBRATION 2000 seismic refraction experiment, one international profile crossed the region of earthquake swarms in West-Bohemia/Vogtland. In addition to this main profile, two shorter supplementary profiles and a semicircle were proposed to study the epicentral area in greater detail. Moreover, the shots were also recorded at permanent stations in the region. The observed travel times of the first arrivals are used here to derive vertically inhomogeneous velocity models of the upper crust. After a polynomial or rational smoothing of the observed data, the Wiechert-Herglotz method is used to compute the velocity models. Typical features of the derived models, as opposed to many previous models, are low surface velocities and a prominent velocity increase within the uppermost crust to a depth of about one kilometre. The scatter of observed travel times is discussed in terms of lateral inhomogeneities and anisotropy. In particular, significant differences have been revealed between the Saxothuringian (northern) and adjacent southern parts of the studied area.

A regional test of global models for flow, rheology, and seismic anisotropy at the base of the mantle

NASA Astrophysics Data System (ADS)

Ford, Heather A.; Long, Maureen D.

2015-08-01

The study of flow patterns and seismic anisotropy in the lowermost mantle is fraught with uncertainties, given the limitations in our understanding of the physical properties of the lowermost mantle and the relationships between deformation and anisotropy. Here we use a set of SKS, SKKS, and ScS splitting measurements that sample the eastern edge of the African Large Low Shear Velocity Province to test predictions of seismic anisotropy derived from previously published 3D global mantle flow models and anisotropy modeling (Walker et al., 2011). The observations can be fit by a model that invokes flow directed to the southwest with a component of downwelling in our study region, and slip that occurs along the (0 1 0) plane of post-perovskite. Most importantly, we demonstrate the ability of a regional shear wave splitting data set to test the robustness of models for flow and deformation in the lowermost mantle.

Final Report on Hierarchical Coupled Modeling and Prediction of Regional Climate Change in the Atlantic Sector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saravanan, Ramalingam

2011-10-30

During the course of this project, we have accomplished the following: a) Carried out studies of climate changes in the past using a hierarchy of intermediate coupled models (Chang et al., 2008; Wan et al 2009; Wen et al., 2010a,b) b) Completed the development of a Coupled Regional Climate Model (CRCM; Patricola et al., 2011a,b) c) Carried out studies testing hypotheses testing the origin of systematic errors in the CRCM (Patricola et al., 2011a,b) d) Carried out studies of the impact of air-sea interaction on hurricanes, in the context of barrier layer interactions (Balaguru et al)

Net primary productivity distribution in the BOREAS region from a process model using satellite and surface data

NASA Astrophysics Data System (ADS)

Liu, J.; Chen, J. M.; Cihlar, J.; Chen, W.

1999-11-01

The purpose of this paper is to upscale tower measurements of net primary productivity (NPP) to the Boreal Ecosystem-Atmosphere Study (BOREAS) study region by means of remote sensing and modeling. The Boreal Ecosystem Productivity Simulator (BEPS) with a new daily canopy photosynthesis model was first tested in one coniferous and one deciduous site. The simultaneous CO2 flux measurements above and below the tree canopy made it possible to isolate daily net primary productivity of the tree canopy for model validation. Soil water holding capacity and gridded daily meteorological data for the region were used as inputs to BEPS, in addition to 1 km resolution land cover and leaf area index (LAI) maps derived from the advanced very high resolution radiometer (AVHRR) data. NPP statistics for the various cover types in the BOREAS region and in the southern study area (SSA) and the northern study area (NSA) are presented. Strong dependence of NPP on LAI was found for the three major cover types: coniferous forest, deciduous forest and cropland. Since BEPS can compute total photosynthetically active radiation absorbed by the canopy in each pixel, light use efficiencies for NPP and gross primary productivity could also be analyzed. From the model results, the following area-averaged statistics were obtained for 1994: (1) mean NPP for the BOREAS region of 217 g C m-2 yr-1; (2) mean NPP of forests (excluding burnt areas in the region) equal to 234 g C m-2 yr-1; (3) mean NPP for the SSA and the NSA of 297 and 238 g C m-2 yr-1, respectively; and (4) mean light use efficiency for NPP equal to 0.40, 0.20, and 0.33 g C (MJ APAR)-1 for deciduous forest, coniferous forest, and crops, respectively.

Urban impact on air quality in RegCM/CAMx couple for MEGAPOLI project - high resolution sensitivity study

NASA Astrophysics Data System (ADS)

Halenka, T.; Huszar, P.; Belda, M.

2010-09-01

Recent studies show considerable effect of atmospheric chemistry and aerosols on climate on regional and local scale. For the purpose of qualifying and quantifying the magnitude of climate forcing due to atmospheric chemistry/aerosols on regional scale, the development of coupling of regional climate model and chemistry/aerosol model was started on the Department of Meteorology and Environmental Protection, Charles University, Prague, for the EC FP6 Project QUANTIFY and EC FP6 Project CECILIA. For this coupling, existing regional climate model and chemistry transport model have been used at very high resolution of 10km grid. Climate is calculated using RegCM while chemistry is solved by CAMx. The experiments with the couple have been prepared for EC FP7 project MEGAPOLI assessing the impact of the megacities and industrialized areas on climate. Meteorological fields generated by RCM drive CAMx transport, chemistry and a dry/wet deposition. A preprocessor utility was developed for transforming RegCM provided fields to CAMx input fields and format. New domain have been settled for MEGAPOLI purpose in 10km resolution including all the European "megacities" regions, i.e. London metropolitan area, Paris region, industrialized Ruhr area, Po valley etc. There is critical issue of the emission inventories available for 10km resolution including the urban hot-spots, TNO emissions are adopted for this sensitivity study in 10km resolution for comparison of the results with the simulation based on merged TNO emissions, i.e. basically original EMEP emissions at 50 km grid. The sensitivity test to switch on/off Paris area emissions is analysed as well. Preliminary results for year 2005 are presented and discussed to reveal whether the concept of effective emission indices could help to parameterize the urban plume effects in lower resolution models. Interactive coupling is compared to study the potential of possible impact of urban air-pollution to the urban area climate.

Application of Modified Particle Swarm Optimization Method for Parameter Extraction of 2-D TEC Mapping

NASA Astrophysics Data System (ADS)

Toker, C.; Gokdag, Y. E.; Arikan, F.; Arikan, O.

2012-04-01

Ionosphere is a very important part of Space Weather. Modeling and monitoring of ionospheric variability is a major part of satellite communication, navigation and positioning systems. Total Electron Content (TEC), which is defined as the line integral of the electron density along a ray path, is one of the parameters to investigate the ionospheric variability. Dual-frequency GPS receivers, with their world wide availability and efficiency in TEC estimation, have become a major source of global and regional TEC modeling. When Global Ionospheric Maps (GIM) of International GPS Service (IGS) centers (http://iono.jpl.nasa.gov/gim.html) are investigated, it can be observed that regional ionosphere along the midlatitude regions can be modeled as a constant, linear or a quadratic surface. Globally, especially around the magnetic equator, the TEC surfaces resemble twisted and dispersed single centered or double centered Gaussian functions. Particle Swarm Optimization (PSO) proved itself as a fast converging and an effective optimization tool in various diverse fields. Yet, in order to apply this optimization technique into TEC modeling, the method has to be modified for higher efficiency and accuracy in extraction of geophysical parameters such as model parameters of TEC surfaces. In this study, a modified PSO (mPSO) method is applied to regional and global synthetic TEC surfaces. The synthetic surfaces that represent the trend and small scale variability of various ionospheric states are necessary to compare the performance of mPSO over number of iterations, accuracy in parameter estimation and overall surface reconstruction. The Cramer-Rao bounds for each surface type and model are also investigated and performance of mPSO are tested with respect to these bounds. For global models, the sample points that are used in optimization are obtained using IGS receiver network. For regional TEC models, regional networks such as Turkish National Permanent GPS Network (TNPGN-Active) receiver sites are used. The regional TEC models are grouped into constant (one parameter), linear (two parameters), and quadratic (six parameters) surfaces which are functions of latitude and longitude. Global models require seven parameters for single centered Gaussian and 13 parameters for double centered Gaussian function. The error criterion is the normalized percentage error for both the surface and the parameters. It is observed that mPSO is very successful in parameter extraction of various regional and global models. The normalized reconstruction error varies from 10-4 for constant surfaces to 10-3 for quadratic surfaces in regional models, sampled with regional networks. Even for the cases of a severe geomagnetic storm that affects measurements globally, with IGS network, the reconstruction error is on the order of 10-1 even though individual parameters have higher normalized errors. The modified PSO technique proved itself to be a useful tool for parameter extraction of more complicated TEC models. This study is supported by TUBITAK EEEAG under Grant No: 109E055.

Simulating Dust Regional Impact on the Middle East Climate and the Red Sea

NASA Astrophysics Data System (ADS)

Osipov, Sergey; Stenchikov, Georgiy

2017-04-01

Dust is one of the most abundant aerosols, however, currently only a few regional climate downscalings account for dust. This study focuses on the Middle East and the Red Sea regional climate response to the dust aerosol radiative forcing. The Red Sea is located between North Africa and Arabian Peninsula, which are first and third largest source regions of dust, respectively. MODIS and SEVIRI satellite observations show extremely high dust optical depths in the region, especially over the southern Red Sea during the summer season. The significant north-to-south gradient of the dust optical depth over the Red Sea persists throughout the entire year. Modeled atmospheric radiative forcing at the surface, top of the atmosphere and absorption in the atmospheric column indicate that dust significantly perturbs radiative balance. Top of the atmosphere modeled forcing is validated against independently derived GERB satellite product. Due to strong radiative forcing at the sea surface (daily mean forcing during summer reaches -32 Wm-2 and 10 Wm-2 in SW and LW, respectively), using uncoupled ocean model with prescribed atmospheric boundary conditions would result in an unrealistic ocean response. Therefore, here we employ the Regional Ocean Modeling system (ROMS) fully coupled with the Weather Research and Forecasting (WRF) model to study the impact of dust on the Red Sea thermal regime and circulation. The WRF was modified to interactively account for the radiative effect of dust. Daily spectral optical properties of dust are computed using Mie, T-matrix, and geometric optics approaches, and are based on the SEVIRI climatological optical depth. The WRF model parent and nested domains are configured over the Middle East and North Africa (MENA) region and over the Red Sea with 30 and 10 km resolution, respectively. The ROMS model over the Red Sea has 2 km grid spacing. The simulations show that, in the equilibrium response, dust causes 0.3-0.5 K cooling of the Red Sea surface waters, and weakens the overturning circulation in the Red Sea. The salinity distribution, freshwater, and heat budgets are significantly perturbed. This indicates that dust plays an important role in the formation of the Red Sea energy balance and circulation regimes, and has to be thoroughly accounted for in future modeling studies.

Regionalizing muscle activity causes changes to the magnitude and direction of the force from whole muscles-a modeling study.

PubMed

Rahemi, Hadi; Nigam, Nilima; Wakeling, James M

2014-01-01

Skeletal muscle can contain neuromuscular compartments that are spatially distinct regions that can receive relatively independent levels of activation. This study tested how the magnitude and direction of the force developed by a whole muscle would change when the muscle activity was regionalized within the muscle. A 3D finite element model of a muscle with its bounding aponeurosis was developed for the lateral gastrocnemius, and isometric contractions were simulated for a series of conditions with either a uniform activation pattern, or regionally distinct activation patterns: in all cases the mean activation from all fibers within the muscle reached 10%. The models showed emergent features of the fiber geometry that matched physiological characteristics: with fibers shortening, rotating to greater pennation, adopting curved trajectories in 3D and changes in the thickness and width of the muscle belly. Simulations were repeated for muscle with compliant, normal and stiff aponeurosis and the aponeurosis stiffness affected the changes to the fiber geometry and the resultant muscle force. Changing the regionalization of the activity resulted to changes in the magnitude, direction and center of the force vector from the whole muscle. Regionalizing the muscle activity resulted in greater muscle force than the simulation with uniform activity across the muscle belly. The study shows how the force from a muscle depends on the complex interactions between the muscle fibers and connective tissues and the region of muscle that is active.

Single-wall nanohorn structure and distribution of incorporated materials

NASA Astrophysics Data System (ADS)

Maigne, Alan; Gloter, Alexandre; Ajima, Kumiko; Colliex, Christian; Iijima, Sumio

2005-03-01

Single-wall carbon nanohorns (SWNHs) are unique spherical-aggregates of single-wall carbon quasi-nanotubes. So far, the observable area has been limited to the aggregate surfaces. We studied core-region structure with TEM using thickness measurement method, EELS, and EDS, and found that carbon density was uniform over the whole aggregate. This result allows to modelize the core-region and to clarify previous models of SWNHs. We used same tools to investigate the incorporation of materials such as fullerenes or platinium compounds. We found that particles can even be incorporated in the core-region and that their distribution in the aggregate depends on their concentration. The information available with these models should be useful in the study of SWNH applications to, for example, drug delivery system.

A Refined Sample of Lyman Excess H II Regions

NASA Astrophysics Data System (ADS)

Marshall, Brandon; Kerton, C. R.

2018-05-01

A large number (67) of the compact/ultra-compact H II regions identified in the CORNISH catalogue were determined to be powered by a Lyman continuum flux in excess of what was expected given their corresponding luminosity. In this study we attempt to reasonably explain away this Lyman excess phenomenon in as many of the 67 H II regions as possible through a variety of observational and astrophysical means including new luminosity estimates, new Herschel photometry, new distance determinations, the use of different models for dust and ionized gas covering factors, and the use of different stellar calibrations. This phenomenon has been observed before; however, the objects shown to exhibit this behavior in the literature have decidedly different physical properties than the regions in our sample, and thus the origin of the excess is not the same. We find that the excess can be reproduced using OB stellar atmosphere models that have been slightly modified in the extreme ultraviolet. Though the exact mechanism producing the excess is still uncertain, we do find that a scaled up magnetospheric accretion model, often used to explain similar emission from T Tauri stars, is unable to match our observations. Our results suggest that the Lyman excess may be associated with younger H II regions, and that it is more commonly found in early B-type stars. Our refined sample of 24 Lyman excess H II regions provides an ideal sample for comparative studies with regular H II regions, and can act as the basis for the further detailed study of individual regions.

Delineation of colluvial soils in different soil regions

NASA Astrophysics Data System (ADS)

Zádorová, Tereza; Penížek, Vít; Vašát, Radim

2015-04-01

Colluvial soils are considered to be the direct result of accelerated soil erosion in agricultural landscape, resulting in accumulation of humus-rich soil material in terrain depressions and toe slopes. They represent an important soil cover element in landscapes influenced by soil erosion and form an important soil organic carbon (SOC) pool. Delineation of colluvial soils can identify areas with high sediment input and potential deep organic carbon storage and thus improve our knowledge on soil mass and SOC stock redistribution in dissected landscapes. Different prediction methods (ordinary kriging, multiple linear regression, supervised fuzzy classification, artificial neural network, support vector machines) for colluvial soils delineation have been tested in three different soil regions (Cambisol, Luvisol and Chernozem) at two scales (plot and watershed) in the Czech Republic. The approach is based on exploitation of relationship between soil and terrain units and assumes that colluvial soil can be defined by particular range of terrain attributes values. Terrain attributes derived from precise DEMs were used as predictors in applied models. The soil-terrain relationship was assessed using a large dataset of field investigations (300 cores at each plot and 100 cores at each watershed). Models were trained at plot scale (15-33 ha) and the best performing model was then calibrated and validated at watershed scale (25-55 km2). The study proved high potential of terrain variables as predictors in colluvial soil delineation. Support vector machines method was the best performing method for colluvial soil occurrence prediction at all the three sites. However, significant differences in performance have been identified among the studied plots. The best results were obtained in Luvisol region where both determination coefficient and prediction accuracy reached the highest values. The model performance was satisfactory also in Chernozem region. The model showed its limitations in the Cambisol region, where a high uncertainty and low prediction accuracy resulted from generally weak soil-terrain relationship given by low redistribution of the soil material. Different terrain attributes were applied as predictors in the models at each study region. In the Chernozem region, the colluvial area is defined by extreme values of slope and topographic position index. In Luvisol and Cambisol regions, colluvial soil area is related mostly to specific values of plan curvature and topographic wetness index. Role of colluvial soils given by theirs spatial extent differs in the studied sites. Colluvial soil in the Chernozem region represents an important soil cover part (13% from the total area). Moderate importance of colluvial soils was determined in the Luvisol region (8 %) and low in the Cambisol region (3%). Spatial extent of colluvial soils corresponds to the intensity of soil mass redistribution. At the three sites with similar environmental settings (terrain, land management, climate), it is mostly soil characteristics and profile development typical for each classification unit that resulted in different importance of colluvial soil in each study site. The study was supported by grant nr. 13-07516P of the Czech science foundation and by grant nr. QJ1230319 of the Ministry of Agriculture.

Modeling of a historical earthquake in Erzincan, Turkey (Ms 7.8, in 1939) using regional seismological information obtained from a recent event

NASA Astrophysics Data System (ADS)

Karimzadeh, Shaghayegh; Askan, Aysegul

2018-04-01

Located within a basin structure, at the conjunction of North East Anatolian, North Anatolian and Ovacik Faults, Erzincan city center (Turkey) is one of the most hazardous regions in the world. Combination of the seismotectonic and geological settings of the region has resulted in series of significant seismic activities including the 1939 (Ms 7.8) as well as the 1992 (Mw = 6.6) earthquakes. The devastative 1939 earthquake occurred in the pre-instrumental era in the region with no available local seismograms. Thus, a limited number of studies exist on that earthquake. However, the 1992 event, despite the sparse local network at that time, has been studied extensively. This study aims to simulate the 1939 Erzincan earthquake using available regional seismic and geological parameters. Despite several uncertainties involved, such an effort to quantitatively model the 1939 earthquake is promising, given the historical reports of extensive damage and fatalities in the area. The results of this study are expressed in terms of anticipated acceleration time histories at certain locations, spatial distribution of selected ground motion parameters and felt intensity maps in the region. Simulated motions are first compared against empirical ground motion prediction equations derived with both local and global datasets. Next, anticipated intensity maps of the 1939 earthquake are obtained using local correlations between peak ground motion parameters and felt intensity values. Comparisons of the estimated intensity distributions with the corresponding observed intensities indicate a reasonable modeling of the 1939 earthquake.

Global modeling of the low- and middle-latitude ionospheric D and lower E regions and implications for HF radio wave absorption

NASA Astrophysics Data System (ADS)

Siskind, David E.; Zawdie, K. A.; Sassi, F.; Drob, D.; Friedrich, M.

2017-01-01

We compare D and lower E region ionospheric model calculations driven by the Whole Atmosphere Community Climate Model (WACCM) with a selection of electron density profiles made by sounding rockets over the past 50 years. The WACCM model, in turn, is nudged by winds and temperatures from the Navy Operational Global Atmospheric Prediction System-Advanced Level Physics High Altitude (NOGAPS-ALPHA). This nudging has been shown to greatly improve the representation of key neutral constituents, such as nitric oxide (NO), that are used as inputs to the ionospheric model. We show that with this improved representation, we greatly improve the comparison between calculated and observed electron densities relative to older studies. At midlatitudes, for both winter and equinoctal conditions, the model agrees well with the data. At tropical latitudes, our results confirm a previous suggestion that there is a model deficit in the calculated electron density in the lowermost D region. We then apply the calculated electron densities to examine the variation of HF absorption with altitude, latitude, and season and from 2008 to 2009. For low latitudes, our results agree with recent studies showing a primary peak absorption in the lower E region with a secondary peak below 75 km. For midlatitude to high latitude, the absorption contains a significant contribution from the middle D region where ionization of NO drives the ion chemistry. The difference in middle- to high-latitude absorption from 2008 to 2009 is due to changes in the NO abundance near 80 km from changes in the wintertime mesospheric residual circulation.

A Study of Regional Waveform Calibration in the Eastern Mediterranean Region.

NASA Astrophysics Data System (ADS)

di Luccio, F.; Pino, A.; Thio, H.

2002-12-01

We modeled Pnl phases from several moderate magnitude events in the eastern Mediterranean to test methods and to develop path calibrations for source determination. The study region spanning from the eastern part of the Hellenic arc to the eastern Anatolian fault is mostly interested by moderate earthquakes, that can produce relevant damages. The selected area consists of several tectonic environment, which produces increased level of difficulty in waveform modeling. The results of this study are useful for the analysis of regional seismicity and for seismic hazard as well, in particular because very few broadband seismic stations are available in the selected area. The obtained velocity model gives a 30 km crustal tickness and low upper mantle velocities. The applied inversion procedure to determine the source mechanism has been successful, also in terms of discrimination of depth, for the entire range of selected paths. We conclude that using the true calibration of the seismic structure and high quality broadband data, it is possible to determine the seismic source in terms of mechanism, even with a single station.

Mapping Regional Impervious Surface Distribution from Night Time Light: The Variability across Global Cities

NASA Astrophysics Data System (ADS)

Lin, M.; Yang, Z.; Park, H.; Qian, S.; Chen, J.; Fan, P.

2017-12-01

Impervious surface area (ISA) has become an important indicator for studying urban environments, but mapping ISA at the regional or global scale is still challenging due to the complexity of impervious surface features. The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light data is (NTL) and Resolution Imaging Spectroradiometer (MODIS) are the major remote sensing data source for regional ISA mapping. A single regression relationship between fractional ISA and NTL or various index derived based on NTL and MODIS vegetation index (NDVI) data was established in many previous studies for regional ISA mapping. However, due to the varying geographical, climatic, and socio-economic characteristics of different cities, the same regression relationship may vary significantly across different cities in the same region in terms of both fitting performance (i.e. R2) and the rate of change (Slope). In this study, we examined the regression relationship between fractional ISA and Vegetation Adjusted Nighttime light Urban Index (VANUI) for 120 randomly selected cities around the world with a multilevel regression model. We found that indeed there is substantial variability of both the R2 (0.68±0.29) and slopes (0.64±0.40) among individual regressions, which suggests that multilevel/hierarchical models are needed for accuracy improvement of future regional ISA mapping .Further analysis also let us find the this substantial variability are affected by climate conditions, socio-economic status, and urban spatial structures. However, all these effects are nonlinear rather than linear, thus could not modeled explicitly in multilevel linear regression models.

An Examination of Selected Organizational Constructs That May Influence a Tri-District Model for Shared Services

ERIC Educational Resources Information Center

Baggs, Bernard T.

2011-01-01

It all began in June 2000. The school districts of Newton Public, Andover Regional, and Green Township, New Jersey contracted Guidelines, Inc., Huntington, Long Island, New York to conduct a Grades K-12 Regional/Shared Services Feasibility Study. The study was funded via a New Jersey state grant from the Regional Efficiency Development Incentive…

Size Scaling in Western North Atlantic Loggerhead Turtles Permits Extrapolation between Regions, but Not Life Stages.

PubMed

Marn, Nina; Klanjscek, Tin; Stokes, Lesley; Jusup, Marko

2015-01-01

Sea turtles face threats globally and are protected by national and international laws. Allometry and scaling models greatly aid sea turtle conservation and research, and help to better understand the biology of sea turtles. Scaling, however, may differ between regions and/or life stages. We analyze differences between (i) two different regional subsets and (ii) three different life stage subsets of the western North Atlantic loggerhead turtles by comparing the relative growth of body width and depth in relation to body length, and discuss the implications. Results suggest that the differences between scaling relationships of different regional subsets are negligible, and models fitted on data from one region of the western North Atlantic can safely be used on data for the same life stage from another North Atlantic region. On the other hand, using models fitted on data for one life stage to describe other life stages is not recommended if accuracy is of paramount importance. In particular, young loggerhead turtles that have not recruited to neritic habitats should be studied and modeled separately whenever practical, while neritic juveniles and adults can be modeled together as one group. Even though morphometric scaling varies among life stages, a common model for all life stages can be used as a general description of scaling, and assuming isometric growth as a simplification is justified. In addition to linear models traditionally used for scaling on log-log axes, we test the performance of a saturating (curvilinear) model. The saturating model is statistically preferred in some cases, but the accuracy gained by the saturating model is marginal.

GFDL's unified regional-global weather-climate modeling system with variable resolution capability for severe weather predictions and regional climate simulations

NASA Astrophysics Data System (ADS)

Lin, S. J.

2015-12-01

The NOAA/Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions (e.g., tornado outbreak events and cat-5 hurricanes) and ultra-high-resolution (1-km) regional climate simulations within a consistent global modeling framework. The fundation of this flexible regional-global modeling system is the non-hydrostatic extension of the vertically Lagrangian dynamical core (Lin 2004, Monthly Weather Review) known in the community as FV3 (finite-volume on the cubed-sphere). Because of its flexability and computational efficiency, the FV3 is one of the final candidates of NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched (single) grid capability, a two-way (regional-global) multiple nested grid capability, and the combination of the stretched and two-way nests, so as to make convection-resolving regional climate simulation within a consistent global modeling system feasible using today's High Performance Computing System. One of our main scientific goals is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornadoes using a global model that was originally designed for century long climate simulations. As a unified weather-climate modeling system, we evaluated the performance of the model with horizontal resolution ranging from 1 km to as low as 200 km. In particular, for downscaling studies, we have developed various tests to ensure that the large-scale circulation within the global varaible resolution system is well simulated while at the same time the small-scale can be accurately captured within the targeted high resolution region.

Microfocal angiography of the pulmonary vasculature

NASA Astrophysics Data System (ADS)

Clough, Anne V.; Haworth, Steven T.; Roerig, David T.; Linehan, John H.; Dawson, Christopher A.

1998-07-01

X-ray microfocal angiography provides a means of assessing regional microvascular perfusion parameters using residue detection of vascular indicators. As an application of this methodology, we studied the effects of alveolar hypoxia, a pulmonary vasoconstrictor, on the pulmonary microcirculation to determine changes in regional blood mean transit time, volume and flow between control and hypoxic conditions. Video x-ray images of a dog lung were acquired as a bolus of radiopaque contrast medium passed through the lobar vasculature. X-ray time-absorbance curves were acquired from arterial and microvascular regions-of-interest during both control and hypoxic alveolar gas conditions. A mathematical model based on indicator-dilution theory applied to image residue curves was applied to the data to determine changes in microvascular perfusion parameters. Sensitivity of the model parameters to the model assumptions was analyzed. Generally, the model parameter describing regional microvascular volume, corresponding to area under the microvascular absorbance curve, was the most robust. The results of the model analysis applied to the experimental data suggest a significant decrease in microvascular volume with hypoxia. However, additional model assumptions concerning the flow kinematics within the capillary bed may be required for assessing changes in regional microvascular flow and mean transit time from image residue data.

Histogram analysis of ADC in brain tumor patients

NASA Astrophysics Data System (ADS)

Banerjee, Debrup; Wang, Jihong; Li, Jiang

2011-03-01

At various stage of progression, most brain tumors are not homogenous. In this presentation, we retrospectively studied the distribution of ADC values inside tumor volume during the course of tumor treatment and progression for a selective group of patients who underwent an anti-VEGF trial. Complete MRI studies were obtained for this selected group of patients including pre- and multiple follow-up, post-treatment imaging studies. In each MRI imaging study, multiple scan series were obtained as a standard protocol which includes T1, T2, T1-post contrast, FLAIR and DTI derived images (ADC, FA etc.) for each visit. All scan series (T1, T2, FLAIR, post-contrast T1) were registered to the corresponding DTI scan at patient's first visit. Conventionally, hyper-intensity regions on T1-post contrast images are believed to represent the core tumor region while regions highlighted by FLAIR may overestimate tumor size. Thus we annotated tumor regions on the T1-post contrast scans and ADC intensity values for pixels were extracted inside tumor regions as defined on T1-post scans. We fit a mixture Gaussian (MG) model for the extracted pixels using the Expectation-Maximization (EM) algorithm, which produced a set of parameters (mean, various and mixture coefficients) for the MG model. This procedure was performed for each visits resulting in a series of GM parameters. We studied the parameters fitted for ADC and see if they can be used as indicators for tumor progression. Additionally, we studied the ADC characteristics in the peri-tumoral region as identified by hyper-intensity on FLAIR scans. The results show that ADC histogram analysis of the tumor region supports the two compartment model that suggests the low ADC value subregion corresponding to densely packed cancer cell while the higher ADC value region corresponding to a mixture of viable and necrotic cells with superimposed edema. Careful studies of the composition and relative volume of the two compartments in tumor region may provide some insights in the early assessment of tumor response to therapy for recurrence brain cancer patients.

Modelling innovation performance of European regions using multi-output neural networks

PubMed Central

Henriques, Roberto

2017-01-01

Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes. PMID:28968449

Modelling innovation performance of European regions using multi-output neural networks.

PubMed

Hajek, Petr; Henriques, Roberto

2017-01-01

Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.

Greening the Grid: Integrating 175 Gigawatts of Renewable Energy into India's Electric Grid - A Detailed Look at the Southern Region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinatedmore » operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: to better anticipate, understand, and mitigate system constraints that could affect RE integration; and to provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission expansion pathways. The model developed for this study provides a rigorous framework for future work and can be updated with the characteristics of new capacity as more information on the future power system is known.« less

Greening the Grid: Integrating 175 Gigawatts of Renewable Energy into India's Electric Grid - A Detailed Look at the Western Region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinatedmore » operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: -To better anticipate, understand, and mitigate system constraints that could affect RE integration; and - To provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission expansion pathways. The model developed for this study provides a rigorous framework for future work and can be updated with the characteristics of new capacity as more information on the future power system is known.« less

GC51D-0831: A Study of the Impact of Dams on Sediment Retention in the Mekong River Basin

NASA Technical Reports Server (NTRS)

Munroe, Thailynn; Griffin, Robert; Anderson, Eric; Markert, Kel

2017-01-01

Dam construction in the Mekong Basin has many cascading effects on the ecology, economy, and hydrology of the surrounding region. The focus of this study is to utilize the Soil Water Assessment Tool (SWAT), developed at Texas A & M, a rainfall-runoff hydrologic model to determine change in sedimentation in the Mekong Basin after the construction of dams. This study uses land cover land use and reservoir datasets created by the NASA SERVIR-Mekong Regional Land Cover Monitoring System and Dam Inundation Mapping Tool as inputs into the model. The study also builds on the capabilities of the SWAT model by using the sediment trapping efficiency (STE) equation from Brune (1953), rewritten by Kummu & Varis (2007), to calculate STE of dams and estimate change in sediment concentration downstream. The outputs from this study can be used to inform dam operation policies, study the correlation between dams and delta subsidence, and study the impact of dams on river fisheries, which are all pressing issues in the Mekong region.

Forward modeling magnetic fields of induced and remanent magnetization in the lithosphere using tesseroids

NASA Astrophysics Data System (ADS)

Baykiev, Eldar; Ebbing, Jörg; Brönner, Marco; Fabian, Karl

2016-11-01

A newly developed software package to calculate the magnetic field in a spherical coordinate system near the Earth's surface and on satellite height is shown to produce reliable modeling results for global and regional applications. The discretization cells of the model are uniformly magnetized spherical prisms, so called tesseroids. The presented algorithm extends an existing code for gravity calculations by applying Poisson's relation to identify the magnetic potential with the sum over pseudogravity fields of tesseroids. By testing different lithosphere discretization grids it is possible to determine the optimal size of tesseroids for field calculations on satellite altitude within realistic measurement error bounds. Also the influence of the Earth's ellipticity upon the modeling result is estimated and global examples are studied. The new software calculates induced and remanent magnetic fields for models at global and regional scale. For regional models far-field effects are evaluated and discussed. This provides bounds for the minimal size of a regional model that is necessary to predict meaningful satellite total field anomalies over the corresponding area.

Habitat prioritization across large landscapes, multiple seasons, and novel areas: an example using greater sage-grouse in Wyoming

USGS Publications Warehouse

Fedy, Bradley C.; Doherty, Kevin E.; Aldridge, Cameron L.; O'Donnell, Michael S.; Beck, Jeffrey L.; Bedrosian, Bryan; Gummer, David; Holloran, Matthew J.; Johnson, Gregory D.; Kaczor, Nicholas W.; Kirol, Christopher P.; Mandich, Cheryl A.; Marshall, David; McKee, Gwyn; Olson, Chad; Pratt, Aaron C.; Swanson, Christopher C.; Walker, Brett L.

2014-01-01

Animal habitat selection is an important and expansive area of research in ecology. In particular, the study of habitat selection is critical in habitat prioritization efforts for species of conservation concern. Landscape planning for species is happening at ever-increasing extents because of the appreciation for the role of landscape-scale patterns in species persistence coupled to improved datasets for species and habitats, and the expanding and intensifying footprint of human land uses on the landscape. We present a large-scale collaborative effort to develop habitat selection models across large landscapes and multiple seasons for prioritizing habitat for a species of conservation concern. Greater sage-grouse (Centrocercus urophasianus, hereafter sage-grouse) occur in western semi-arid landscapes in North America. Range-wide population declines of this species have been documented, and it is currently considered as “warranted but precluded” from listing under the United States Endangered Species Act. Wyoming is predicted to remain a stronghold for sage-grouse populations and contains approximately 37% of remaining birds. We compiled location data from 14 unique radiotelemetry studies (data collected 1994–2010) and habitat data from high-quality, biologically relevant, geographic information system (GIS) layers across Wyoming. We developed habitat selection models for greater sage-grouse across Wyoming for 3 distinct life stages: 1) nesting, 2) summer, and 3) winter. We developed patch and landscape models across 4 extents, producing statewide and regional (southwest, central, northeast) models for Wyoming. Habitat selection varied among regions and seasons, yet preferred habitat attributes generally matched the extensive literature on sage-grouse seasonal habitat requirements. Across seasons and regions, birds preferred areas with greater percentage sagebrush cover and avoided paved roads, agriculture, and forested areas. Birds consistently preferred areas with higher precipitation in the summer and avoided rugged terrain in the winter. Selection for sagebrush cover varied regionally with stronger selection in the Northeast region, likely because of limited availability, whereas avoidance of paved roads was fairly consistent across regions. We chose resource selection function (RSF) thresholds for each model set (seasonal × regional combination) that delineated important seasonal habitats for sage-grouse. Each model set showed good validation and discriminatory capabilities within study-site boundaries. We applied the nesting-season models to a novel area not included in model development. The percentage of independent nest locations that fell directly within identified important habitat was not overly impressive in the novel area (49%); however, including a 500-m buffer around important habitat captured 98% of independent nest locations within the novel area. We also used leks and associated peak male counts as a proxy for nesting habitat outside of the study sites used to develop the models. A 1.5-km buffer around the important nesting habitat boundaries included 77% of males counted at leks in Wyoming outside of the study sites. Data were not available to quantitatively test the performance of the summer and winter models outside our study sites. The collection of models presented here represents large-scale resource-management planning tools that are a significant advancement to previous tools in terms of spatial and temporal resolution.

Quantifying Tropical Glacier Mass Balance Sensitivity to Climate Change Through Regional-Scale Modeling and The Randolph Glacier Inventory

NASA Astrophysics Data System (ADS)

Malone, A.

2017-12-01

Quantifying mass balance sensitivity to climate change is essential for forecasting glacier evolution and deciphering climate signals embedded in archives of past glacier changes. Ideally, these quantifications result from decades of field measurement, remote sensing, and a hierarchy modeling approach, but in data-sparse regions, such as the Himalayas and tropical Andes, regional-scale modeling rooted in first principles provides a first-order picture. Previous regional-scaling modeling studies have applied a surface energy and mass balance approach in order to quantify equilibrium line altitude sensitivity to climate change. In this study, an expanded regional-scale surface energy and mass balance model is implemented to quantify glacier-wide mass balance sensitivity to climate change for tropical Andean glaciers. Data from the Randolph Glacier Inventory are incorporated, and additional physical processes are included, such as a dynamic albedo and cloud-dependent atmospheric emissivity. The model output agrees well with the limited mass balance records for tropical Andean glaciers. The dominant climate variables driving interannual mass balance variability differ depending on the climate setting. For wet tropical glaciers (annual precipitation >0.75 m y-1), temperature is the dominant climate variable. Different hypotheses for the processes linking wet tropical glacier mass balance variability to temperature are evaluated. The results support the hypothesis that glacier-wide mass balance on wet tropical glaciers is largely dominated by processes at the lowest elevation where temperature plays a leading role in energy exchanges. This research also highlights the transient nature of wet tropical glaciers - the vast majority of tropical glaciers and a vital regional water resource - in an anthropogenic warming world.

Does the high–tech industry consistently reduce CO{sub 2} emissions? Results from nonparametric additive regression model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Bin; Research Center of Applied Statistics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013; Lin, Boqiang, E-mail: bqlin@xmu.edu.cn

China is currently the world's largest carbon dioxide (CO{sub 2}) emitter. Moreover, total energy consumption and CO{sub 2} emissions in China will continue to increase due to the rapid growth of industrialization and urbanization. Therefore, vigorously developing the high–tech industry becomes an inevitable choice to reduce CO{sub 2} emissions at the moment or in the future. However, ignoring the existing nonlinear links between economic variables, most scholars use traditional linear models to explore the impact of the high–tech industry on CO{sub 2} emissions from an aggregate perspective. Few studies have focused on nonlinear relationships and regional differences in China. Basedmore » on panel data of 1998–2014, this study uses the nonparametric additive regression model to explore the nonlinear effect of the high–tech industry from a regional perspective. The estimated results show that the residual sum of squares (SSR) of the nonparametric additive regression model in the eastern, central and western regions are 0.693, 0.054 and 0.085 respectively, which are much less those that of the traditional linear regression model (3.158, 4.227 and 7.196). This verifies that the nonparametric additive regression model has a better fitting effect. Specifically, the high–tech industry produces an inverted “U–shaped” nonlinear impact on CO{sub 2} emissions in the eastern region, but a positive “U–shaped” nonlinear effect in the central and western regions. Therefore, the nonlinear impact of the high–tech industry on CO{sub 2} emissions in the three regions should be given adequate attention in developing effective abatement policies. - Highlights: • The nonlinear effect of the high–tech industry on CO{sub 2} emissions was investigated. • The high–tech industry yields an inverted “U–shaped” effect in the eastern region. • The high–tech industry has a positive “U–shaped” nonlinear effect in other regions. • The linear impact of the high–tech industry in the eastern region is the strongest.« less

Validation of WRF forecasts for the Chajnantor region

NASA Astrophysics Data System (ADS)

Pozo, Diana; Marín, J. C.; Illanes, L.; Curé, M.; Rabanus, D.

2016-06-01

This study assesses the performance of the Weather Research and Forecasting (WRF) model to represent the near-surface weather conditions and the precipitable water vapour (PWV) in the Chajnantor plateau, in the north of Chile, from 2007 April to December. The WRF model shows a very good performance forecasting the near-surface temperature and zonal wind component, although it overestimates the 2 m water vapour mixing ratio and underestimates the 10 m meridional wind component. The model represents very well the seasonal, intraseasonal and the diurnal variation of PWV. However, the PWV errors increase after the 12 h of simulation. Errors in the simulations are larger than 1.5 mm only during 10 per cent of the study period, they do not exceed 0.5 mm during 65 per cent of the time and they are below 0.25 mm more than 45 per cent of the time, which emphasizes the good performance of the model to forecast the PWV over the region. The misrepresentation of the near-surface humidity in the region by the WRF model may have a negative impact on the PWV forecasts. Thus, having accurate forecasts of humidity near the surface may result in more accurate PWV forecasts. Overall, results from this, as well as recent studies, supports the use of the WRF model to provide accurate weather forecasts for the region, particularly for the PWV, which can be of great benefit for astronomers in the planning of their scientific operations and observing time.

Regional Climate Models as a Tool for Assessing Changes in the Laurentian Great Lakes Net Basin Supply

NASA Astrophysics Data System (ADS)

Music, B.; Mailhot, E.; Nadeau, D.; Irambona, C.; Frigon, A.

2017-12-01

Over the last decades, there has been growing concern about the effects of climate change on the Great Lakes water supply. Most of the modelling studies focusing on the Laurentian Great Lakes do not allow two-way exchanges of water and energy between the atmosphere and the underlying surface, and therefore do not account for important feedback mechanisms. Moreover, energy budget constraint at the land surface is not usually taken into account. To address this issue, several recent climate change studies used high resolution Regional Climate Models (RCMs) for evaluating changes in the hydrological regime of the Great Lakes. As RCMs operate on the concept of water and energy conservation, an internal consistency of the simulated energy and water budget components is assured. In this study we explore several recently generated Regional Climate Model (RCM) simulations to investigate the Great Lakes' Net Basin Supply (NBS) in a changing climate. These include simulations of the Canadian Regional Climate Model (CRCM5) supplemented by simulations from several others RCMs participating to the North American CORDEX project (CORDEX-NA). The analysis focuses on the NBS extreme values under nonstationary conditions. The results are expected to provide useful information to the industries in the Great Lakes that all need to include accurate climate change information in their long-term strategy plans to better anticipate impacts of low and/or high water levels.

Ionospheric E-Region Response to Solar-Geomagnetic Storms Observed by TIMED/SABER and Application to IRI Storm-Model Development

NASA Technical Reports Server (NTRS)

Mertens, Christopher J.; Mast, Jeffrey C.; Winick, Jeremy R.; Russell, James M., III; Mlynczak, Martin G.; Evans, David S.

2007-01-01

The large thermospheric infrared radiance enhancements observed from the TIMED/SABER experiment during recent solar storms provide an exciting opportunity to study the influence of solar-geomagnetic disturbances on the upper atmosphere and ionosphere. In particular, nighttime enhancements of 4.3 um emission, due to vibrational excitation and radiative emission by NO+, provide an excellent proxy to study and analyze the response of the ionospheric E-region to auroral electron dosing and storm-time enhancements to the E-region electron density. In this paper we give a status report of on-going work on model and data analysis methodologies of deriving NO+ 4.3 um volume emission rates, a proxy for the storm-time E-region response, and the approach for deriving an empirical storm-time correction to International Reference Ionosphere (IRI) E-region NO+ and electron densities.

The Be-WetSpa-Pest modeling approach to simulate human and environmental exposure from pesticide application

NASA Astrophysics Data System (ADS)

Binder, Claudia; Garcia-Santos, Glenda; Andreoli, Romano; Diaz, Jaime; Feola, Giuseppe; Wittensoeldner, Moritz; Yang, Jing

2016-04-01

This study presents an integrative and spatially explicit modeling approach for analyzing human and environmental exposure from pesticide application of smallholders in the potato producing Andean region in Colombia. The modeling approach fulfills the following criteria: (i) it includes environmental and human compartments; (ii) it contains a behavioral decision-making model for estimating the effect of policies on pesticide flows to humans and the environment; (iii) it is spatially explicit; and (iv) it is modular and easily expandable to include additional modules, crops or technologies. The model was calibrated and validated for the Vereda La Hoya and was used to explore the effect of different policy measures in the region. The model has moderate data requirements and can be adapted relatively easy to other regions in developing countries with similar conditions.

Regional groundwater characteristics and hydraulic conductivity based on geological units in Korean peninsula

NASA Astrophysics Data System (ADS)

Kim, Y.; Suk, H.

2011-12-01

In this study, about 2,000 deep observation wells, stream and/or river distribution, and river's density were analyzed to identify regional groundwater flow trend, based on the regional groundwater survey of four major river watersheds including Geum river, Han river, Youngsan-Seomjin river, and Nakdong river in Korea. Hydrogeologial data were collected to analyze regional groundwater flow characteristics according to geological units. Additionally, hydrological soil type data were collected to estimate direct runoff through SCS-CN method. Temperature and precipitation data were used to quantify infiltration rate. The temperature and precipitation data were also used to quantify evaporation by Thornthwaite method and to evaluate groundwater recharge, respectively. Understanding the regional groundwater characteristics requires the database of groundwater flow parameters, but most hydrogeological data include limited information such as groundwater level and well configuration. In this study, therefore, groundwater flow parameters such as hydraulic conductivities or transmissivities were estimated using observed groundwater level by inverse model, namely PEST (Non-linear Parameter ESTimation). Since groundwater modeling studies have some uncertainties in data collection, conceptualization, and model results, model calibration should be performed. The calibration may be manually performed by changing parameters step by step, or various parameters are simultaneously changed by automatic procedure using PEST program. In this study, both manual and automatic procedures were employed to calibrate and estimate hydraulic parameter distributions. In summary, regional groundwater survey data obtained from four major river watersheds and various data of hydrology, meteorology, geology, soil, and topography in Korea were used to estimate hydraulic conductivities using PEST program. Especially, in order to estimate hydraulic conductivity effectively, it is important to perform in such a way that areas of same or similar hydrogeological characteristics should be grouped into zones. Keywords: regional groundwater, database, hydraulic conductivity, PEST, Korean peninsular Acknowledgements: This work was supported by the Radioactive Waste Management of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Knowledge Economy (2011T100200152)

Observed Local Impacts of Global Irrigation on Surface Temperature

NASA Astrophysics Data System (ADS)

Chen, L.; Dirmeyer, P.

2017-12-01

Agricultural irrigation has significant potential for altering local climate through reducing soil albedo, increasing evapotranspiration, and enabling greater leaf area. Numerous studies using regional or global climate models have demonstrated the cooling effects of irrigation on mean and extreme temperature, especially over regions where irrigation is extensive. However, these model-based results have not been validated due to the limitations of observational datasets. In this study, multiple satellite-based products, including the Moderate Resolution Imaging Spectroradiometer (MODIS) and Soil Moisture Active Passive (SMAP) data sets, are used to isolate and quantify the local impacts of irrigation on surface climate over the irrigated regions, which are derived from the Global Map of Irrigation Areas (GMIA). The relationships among soil moisture, albedo, evapotranspiration, and surface temperature are explored. Strong evaporative cooling of irrigation on daytime surface temperature is found over the arid and semi-arid regions, such as California's Central Valley, the Great Plains, and central Asia. However, the cooling effects are less evident in most areas of eastern China, India, and the Lower Mississippi River Basin in spite of extensive irrigation over these regions. Results are also compared with irrigation experiments using the Community Earth System Model (CESM) to assess the model's ability to represent land-atmosphere interactions in regards to irrigation.

Modelling urban growth in the Indo-Gangetic plain using nighttime OLS data and cellular automata

NASA Astrophysics Data System (ADS)

Roy Chowdhury, P. K.; Maithani, Sandeep

2014-12-01

The present study demonstrates the applicability of the Operational Linescan System (OLS) sensor in modelling urban growth at regional level. The nighttime OLS data provides an easy, inexpensive way to map urban areas at a regional scale, requiring a very small volume of data. A cellular automata (CA) model was developed for simulating urban growth in the Indo-Gangetic plain; using OLS data derived maps as input. In the proposed CA model, urban growth was expressed in terms of causative factors like economy, topography, accessibility and urban infrastructure. The model was calibrated and validated based on OLS data of year 2003 and 2008 respectively using spatial metrics measures and subsequently the urban growth was predicted for the year 2020. The model predicted high urban growth in North Western part of the study area, in south eastern part growth would be concentrated around two cities, Kolkata and Howrah. While in the middle portion of the study area, i.e., Jharkhand, Bihar and Eastern Uttar Pradesh, urban growth has been predicted in form of clusters, mostly around the present big cities. These results will not only provide an input to urban planning but can also be utilized in hydrological and ecological modelling which require an estimate of future built up areas especially at regional level.

Field-based landslide susceptibility assessment in a data-scarce environment: the populated areas of the Rwenzori Mountains

NASA Astrophysics Data System (ADS)

Jacobs, Liesbet; Dewitte, Olivier; Poesen, Jean; Sekajugo, John; Nobile, Adriano; Rossi, Mauro; Thiery, Wim; Kervyn, Matthieu

2018-01-01

The inhabited zone of the Ugandan Rwenzori Mountains is affected by landslides, frequently causing loss of life, damage to infrastructure and loss of livelihood. This area of ca. 1230 km2 is characterized by contrasting geomorphologic, climatic and lithological patterns, resulting in different landslide types. In this study, the spatial pattern of landslide susceptibility is investigated based on an extensive field inventory constructed for five representative areas within the region (153 km2) and containing over 450 landslides. To achieve a reliable susceptibility assessment, the effects of (1) using different topographic data sources and spatial resolutions and (2) changing the scale of assessment by comparing local and regional susceptibility models on the susceptibility model performances are investigated using a pixel-based logistic regression approach. Topographic data are extracted from different digital elevation models (DEMs) based on radar interferometry (SRTM and TanDEM-X) and optical stereophotogrammetry (ASTER DEM). Susceptibility models using the radar-based DEMs tend to outperform the ones using the ASTER DEM. The model spatial resolution is varied between 10, 20, 30 and 90 m. The optimal resolution depends on the location of the investigated area within the region but the lowest model resolution (90 m) rarely yields the best model performances while the highest model resolution (10 m) never results in significant increases in performance compared to the 20 m resolution. Models built for the local case studies generally have similar or better performances than the regional model and better reflect site-specific controlling factors. At the regional level the effect of distinguishing landslide types between shallow and deep-seated landslides is investigated. The separation of landslide types allows us to improve model performances for the prediction of deep-seated landslides and to better understand factors influencing the occurrence of shallow landslides such as tangent curvature and total rainfall. Finally, the landslide susceptibility assessment is overlaid with a population density map in order to identify potential landslide risk hotspots, which could direct research and policy action towards reduced landslide risk in this under-researched, landslide-prone region.

Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models

NASA Astrophysics Data System (ADS)

Hoffman, A.; Forest, C. E.; Kemanian, A.

2016-12-01

A significant number of food-insecure nations exist in regions of the world where dust plays a large role in the climate system. While the impacts of common climate variables (e.g. temperature, precipitation, ozone, and carbon dioxide) on crop yields are relatively well understood, the impact of mineral aerosols on yields have not yet been thoroughly investigated. This research aims to develop the data and tools to progress our understanding of mineral aerosol impacts on crop yields. Suspended dust affects crop yields by altering the amount and type of radiation reaching the plant, modifying local temperature and precipitation. While dust events (i.e. dust storms) affect crop yields by depleting the soil of nutrients or by defoliation via particle abrasion. The impact of dust on yields is modeled statistically because we are uncertain which impacts will dominate the response on national and regional scales considered in this study. Multiple linear regression is used in a number of large-scale statistical crop modeling studies to estimate yield responses to various climate variables. In alignment with previous work, we develop linear crop models, but build upon this simple method of regression with machine-learning techniques (e.g. random forests) to identify important statistical predictors and isolate how dust affects yields on the scales of interest. To perform this analysis, we develop a crop-climate dataset for maize, soybean, groundnut, sorghum, rice, and wheat for the regions of West Africa, East Africa, South Africa, and the Sahel. Random forest regression models consistently model historic crop yields better than the linear models. In several instances, the random forest models accurately capture the temperature and precipitation threshold behavior in crops. Additionally, improving agricultural technology has caused a well-documented positive trend that dominates time series of global and regional yields. This trend is often removed before regression with traditional crop models, but likely at the cost of removing climate information. Our random forest models consistently discover the positive trend without removing any additional data. The application of random forests as a statistical crop model provides insight into understanding the impact of dust on yields in marginal food producing regions.

WRF-Chem simulated surface ozone over south Asia during the pre-monsoon: effects of emission inventories and chemical mechanisms

NASA Astrophysics Data System (ADS)

Sharma, Amit; Ojha, Narendra; Pozzer, Andrea; Mar, Kathleen A.; Beig, Gufran; Lelieveld, Jos; Gunthe, Sachin S.

2017-12-01

We evaluate numerical simulations of surface ozone mixing ratios over the south Asian region during the pre-monsoon season, employing three different emission inventories in the Weather Research and Forecasting model with Chemistry (WRF-Chem) with the second-generation Regional Acid Deposition Model (RADM2) chemical mechanism: the Emissions Database for Global Atmospheric Research - Hemispheric Transport of Air Pollution (EDGAR-HTAP), the Intercontinental Chemical Transport Experiment phase B (INTEX-B) and the Southeast Asia Composition, Cloud, Climate Coupling Regional Study (SEAC4RS). Evaluation of diurnal variability in modelled ozone compared to observational data from 15 monitoring stations across south Asia shows the model ability to reproduce the clean, rural and polluted urban conditions over this region. In contrast to the diurnal average, the modelled ozone mixing ratios during noontime, i.e. hours of intense photochemistry (11:30-16:30 IST - Indian Standard Time - UTC +5:30), are found to differ among the three inventories. This suggests that evaluations of the modelled ozone limited to 24 h average are insufficient to assess uncertainties associated with ozone buildup. HTAP generally shows 10-30 ppbv higher noontime ozone mixing ratios than SEAC4RS and INTEX-B, especially over the north-west Indo-Gangetic Plain (IGP), central India and southern India. The HTAP simulation repeated with the alternative Model for Ozone and Related Chemical Tracers (MOZART) chemical mechanism showed even more strongly enhanced surface ozone mixing ratios due to vertical mixing of enhanced ozone that has been produced aloft. Our study indicates the need to also evaluate the O3 precursors across a network of stations and the development of high-resolution regional inventories for the anthropogenic emissions over south Asia accounting for year-to-year changes to further reduce uncertainties in modelled ozone over this region.

The Impact of US SO2 Emissions on Clouds and the Hydrological Cycle at Global and Regional Scales in Three Coupled Chemistry-Climate Models

NASA Astrophysics Data System (ADS)

Westervelt, D. M.

2016-12-01

It is widely expected that global and regional emissions of atmospheric aerosols and their precursors will decrease strongly throughout the remainder of the 21st century, due to emission reduction policies enacted to protect human health. Although there is some evidence that these aerosol reductions may lead to significant regional and global climate impacts, we currently lack a full understanding of the magnitude, spatial and temporal pattern, and statistical significance of these influences, especially for clouds and precipitation. Further, we often lack robust understanding of the processes by which regional aerosols influence local and remote climate. Here, we aim to quantify systematically the cloud and hydrological cycle response to regional changes in aerosols through model simulations using three fully coupled chemistry-climate models: NOAA Geophysical Fluid Dynamics Laboratory Coupled Model 3 (GFDL-CM3), NCAR Community Earth System Model (NCAR-CESM1), and NASA Goddard Institute for Space Studies ModelE2 (GISS-E2). The central approach we use is to contrast a long control experiment (400 years) with a collection of long individual perturbation experiments ( 200 years). We perturb emissions of sulfur dioxide (SO2; precursor to sulfate aerosol) in the United States and determine which responses are significant relative to internal variability and robust across the three models. Initial results show robust, statistically significant decreases in cloud droplet number and liquid water path in the source region across the three models due to decreases in sulfate aerosols. Setting SO2 emissions to zero over the U.S. causes both local and remote impacts in precipitation, with notable significant increases in Sahel and Arctic precipitation. In 13 of the 15 regions we analyze, the precipitation response to zero U.S. SO2 emissions agrees in sign, with agreement in magnitude to within one standard deviation in many of those regions. U.S. sulfate also impacts the timing of the arrival of the Sahel rainy season. Our approach enables us to develop a basis for understanding the response of regional emissions of aerosols and their precursors, and will be expanded to other regions and aerosol species in future work.

Failed rib region prediction in a human body model during crash events with precrash braking.

PubMed

Guleyupoglu, B; Koya, B; Barnard, R; Gayzik, F S

2018-02-28

The objective of this study is 2-fold. We used a validated human body finite element model to study the predicted chest injury (focusing on rib fracture as a function of element strain) based on varying levels of simulated precrash braking. Furthermore, we compare deterministic and probabilistic methods of rib injury prediction in the computational model. The Global Human Body Models Consortium (GHBMC) M50-O model was gravity settled in the driver position of a generic interior equipped with an advanced 3-point belt and airbag. Twelve cases were investigated with permutations for failure, precrash braking system, and crash severity. The severities used were median (17 kph), severe (34 kph), and New Car Assessment Program (NCAP; 56.4 kph). Cases with failure enabled removed rib cortical bone elements once 1.8% effective plastic strain was exceeded. Alternatively, a probabilistic framework found in the literature was used to predict rib failure. Both the probabilistic and deterministic methods take into consideration location (anterior, lateral, and posterior). The deterministic method is based on a rubric that defines failed rib regions dependent on a threshold for contiguous failed elements. The probabilistic method depends on age-based strain and failure functions. Kinematics between both methods were similar (peak max deviation: ΔX head = 17 mm; ΔZ head = 4 mm; ΔX thorax = 5 mm; ΔZ thorax = 1 mm). Seat belt forces at the time of probabilistic failed region initiation were lower than those at deterministic failed region initiation. The probabilistic method for rib fracture predicted more failed regions in the rib (an analog for fracture) than the deterministic method in all but 1 case where they were equal. The failed region patterns between models are similar; however, there are differences that arise due to stress reduced from element elimination that cause probabilistic failed regions to continue to rise after no deterministic failed region would be predicted. Both the probabilistic and deterministic methods indicate similar trends with regards to the effect of precrash braking; however, there are tradeoffs. The deterministic failed region method is more spatially sensitive to failure and is more sensitive to belt loads. The probabilistic failed region method allows for increased capability in postprocessing with respect to age. The probabilistic failed region method predicted more failed regions than the deterministic failed region method due to force distribution differences.

Simulation of Multiscale Ground-Water Flow in Part of the Northeastern San Joaquin Valley, California

USGS Publications Warehouse

Phillips, Steven P.; Green, Christopher T.; Burow, Karen R.; Shelton, Jennifer L.; Rewis, Diane L.

2007-01-01

The transport and fate of agricultural chemicals in a variety of environmental settings is being evaluated as part of the U.S. Geological Survey (USGS) National Water-Quality Assessment Program. One of the locations being evaluated is a 2,700-km2 (square kilometer) regional study area in the northeastern San Joaquin Valley surrounding the city of Modesto, an area dominated by irrigated agriculture in a semi-arid climate. Ground water is a key source of water for irrigation and public supply, and exploitation of this resource has altered the natural flow system. The aquifer system is predominantly alluvial, and an unconfined to semiconfined aquifer overlies a confined aquifer in the southwestern part of the study area; these aquifers are separated by the lacustrine Corcoran Clay. A regional-scale 16-layer steady-state model of ground-water flow in the aquifer system in the regional study area was developed to provide boundary conditions for an embedded 110-layer steady-state local-scale model of part of the aquifer system overlying the Corcoran Clay along the Merced River. The purpose of the local-scale model was to develop a better understanding of the aquifer system and to provide a basis for simulation of reactive transport of agricultural chemicals. The heterogeneity of aquifer materials was explicitly incorporated into the regional and local models using information from geologic and drillers? logs of boreholes. Aquifer materials were differentiated in the regional model by the percentage of coarse-grained sediments in a cell, and in the local model by four hydrofacies (sand, silty sand, silt, and clay). The calibrated horizontal hydraulic conductivity values of the coarse-grained materials in the zone above the Corcoran Clay in the regional model and of the sand hydrofacies used in the local model were about equal (30?80 m/d [meter per day]), and the vertical hydraulic conductivity values in the same zone of the regional model (median of 0.012 m/d), which is dominated by the finer-grained materials, were about an order of magnitude less than that for the clay hydrofacies in the local model. Data used for calibrating both models included long-term hourly water-level measurements in 20 short-screened wells installed by the USGS in the Modesto and Merced River areas. Additional calibration data for the regional model included water-level measurements in 11 wells upslope and 17 wells downslope from these areas. The root mean square error was 2.3 m (meter) for all wells in the regional model and 0.8 m for only the USGS wells; the associated average errors were 0.9 m and 0.3 m, respectively. The root mean square error for the 12 USGS wells along a transect in the local model area was 0.08 m; the average error was 0.0 m. Particle tracking was used with the local model to estimate the concentration of an environmental tracer, sulfur hexafluoride, in 10 USGS transect wells near the Merced River that were sampled for this constituent. Measured and estimated concentrations in the mid-depth and deepest wells, which would be most sensitive to errors in hydraulic conductivity estimates, were consistent. The combined results of particle tracking and sulfur hexafluoride analysis suggest that most water sampled from the transect wells was recharged less that 25 years ago.

Quantifying Impacts of Land-use and Land Cover Change in a Changing Climate at the Regional Scale using an Integrated Earth System Modeling Approach

NASA Astrophysics Data System (ADS)

Huang, M.

2016-12-01

Earth System models (ESMs) are effective tools for investigating the water-energy-food system interactions under climate change. In this presentation, I will introduce research efforts at the Pacific Northwest National Laboratory towards quantifying impacts of LULCC on the water-energy-food nexus in a changing climate using an integrated regional Earth system modeling framework: the Platform for Regional Integrated Modeling and Analysis (PRIMA). Two studies will be discussed to showcase the capability of PRIMA: (1) quantifying changes in terrestrial hydrology over the Conterminous US (CONUS) from 2005 to 2095 using the Community Land Model (CLM) driven by high-resolution downscaled climate and land cover products from PRIMA, which was designed for assessing the impacts of and potential responses to climate and anthropogenic changes at regional scales; (2) applying CLM over the CONUS to provide the first county-scale model validation in simulating crop yields and assessing associated impacts on the water and energy budgets using CLM. The studies demonstrate the benefits of incorporating and coupling human activities into complex ESMs, and critical needs to account for the biogeophysical and biogeochemical effects of LULCC in climate impacts studies, and in designing mitigation and adaptation strategies at a scale meaningful for decision-making. Future directions in quantifying LULCC impacts on the water-energy-food nexus under a changing climate, as well as feedbacks among climate, energy production and consumption, and natural/managed ecosystems using an Integrated Multi-scale, Multi-sector Modeling framework will also be discussed.

Application of a process-based shallow landslide hazard model over a broad area in Central Italy

USGS Publications Warehouse

Gioia, Eleonora; Speranza, Gabriella; Ferretti, Maurizio; Godt, Jonathan W.; Baum, Rex L.; Marincioni, Fausto

2015-01-01

Process-based models are widely used for rainfall-induced shallow landslide forecasting. Previous studies have successfully applied the U.S. Geological Survey’s Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model (Baum et al. 2002) to compute infiltration-driven changes in the hillslopes’ factor of safety on small scales (i.e., tens of square kilometers). Soil data input for such models are difficult to obtain across larger regions. This work describes a novel methodology for the application of TRIGRS over broad areas with relatively uniform hydrogeological properties. The study area is a 550-km2 region in Central Italy covered by post-orogenic Quaternary sediments. Due to the lack of field data, we assigned mechanical and hydrological property values through a statistical analysis based on literature review of soils matching the local lithologies. We calibrated the model using rainfall data from 25 historical rainfall events that triggered landslides. We compared the variation of pressure head and factor of safety with the landslide occurrence to identify the best fitting input conditions. Using calibrated inputs and a soil depth model, we ran TRIGRS for the study area. Receiver operating characteristic (ROC) analysis, comparing the model’s output with a shallow landslide inventory, shows that TRIGRS effectively simulated the instability conditions in the post-orogenic complex during historical rainfall scenarios. The implication of this work is that rainfall-induced landslides over large regions may be predicted by a deterministic model, even where data on geotechnical and hydraulic properties as well as temporal changes in topography or subsurface conditions are not available.

Computational models of Bitemporal, Bifrontal and Right Unilateral ECT predict differential stimulation of brain regions associated with efficacy and cognitive side effects.

PubMed

Bai, S; Gálvez, V; Dokos, S; Martin, D; Bikson, M; Loo, C

2017-03-01

Extensive clinical research has shown that the efficacy and cognitive outcomes of electroconvulsive therapy (ECT) are determined, in part, by the type of electrode placement used. Bitemporal ECT (BT, stimulating electrodes placed bilaterally in the frontotemporal region) is the form of ECT with relatively potent clinical and cognitive side effects. However, the reasons for this are poorly understood. This study used computational modelling to examine regional differences in brain excitation between BT, Bifrontal (BF) and Right Unilateral (RUL) ECT, currently the most clinically-used ECT placements. Specifically, by comparing similarities and differences in current distribution patterns between BT ECT and the other two placements, the study aimed to create an explanatory model of critical brain sites that mediate antidepressant efficacy and sites associated with cognitive, particularly memory, adverse effects. High resolution finite element human head models were generated from MRI scans of three subjects. The models were used to compare differences in activation between the three ECT placements, using subtraction maps. In this exploratory study on three realistic head models, Bitemporal ECT resulted in greater direct stimulation of deep midline structures and also left temporal and inferior frontal regions. Interpreted in light of existing knowledge on depressive pathophysiology and cognitive neuroanatomy, it is suggested that the former sites are related to efficacy and the latter to cognitive deficits. We hereby propose an approach using binarised subtraction models that can be used to optimise, and even individualise, ECT therapies. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Reference evapotranspiration forecasting based on local meteorological and global climate information screened by partial mutual information

NASA Astrophysics Data System (ADS)

Fang, Wei; Huang, Shengzhi; Huang, Qiang; Huang, Guohe; Meng, Erhao; Luan, Jinkai

2018-06-01

In this study, reference evapotranspiration (ET0) forecasting models are developed for the least economically developed regions subject to meteorological data scarcity. Firstly, the partial mutual information (PMI) capable of capturing the linear and nonlinear dependence is investigated regarding its utility to identify relevant predictors and exclude those that are redundant through the comparison with partial linear correlation. An efficient input selection technique is crucial for decreasing model data requirements. Then, the interconnection between global climate indices and regional ET0 is identified. Relevant climatic indices are introduced as additional predictors to comprise information regarding ET0, which ought to be provided by meteorological data unavailable. The case study in the Jing River and Beiluo River basins, China, reveals that PMI outperforms the partial linear correlation in excluding the redundant information, favouring the yield of smaller predictor sets. The teleconnection analysis identifies the correlation between Nino 1 + 2 and regional ET0, indicating influences of ENSO events on the evapotranspiration process in the study area. Furthermore, introducing Nino 1 + 2 as predictors helps to yield more accurate ET0 forecasts. A model performance comparison also shows that non-linear stochastic models (SVR or RF with input selection through PMI) do not always outperform linear models (MLR with inputs screen by linear correlation). However, the former can offer quite comparable performance depending on smaller predictor sets. Therefore, efforts such as screening model inputs through PMI and incorporating global climatic indices interconnected with ET0 can benefit the development of ET0 forecasting models suitable for data-scarce regions.

Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

NASA Technical Reports Server (NTRS)

Zhu, Jiang; Stevens, E.; Zhang, X.; Zavodsky, B. T.; Heinrichs, T.; Broderson, D.

2014-01-01

A case study and monthly statistical analysis using sounder data assimilation to improve the Alaska regional weather forecast model are presented. Weather forecast in Alaska faces challenges as well as opportunities. Alaska has a large land with multiple types of topography and coastal area. Weather forecast models must be finely tuned in order to accurately predict weather in Alaska. Being in the high-latitudes provides Alaska greater coverage of polar orbiting satellites for integration into forecasting models than the lower 48. Forecasting marine low stratus clouds is critical to the Alaska aviation and oil industry and is the current focus of the case study. NASA AIRS/CrIS sounder profiles data are used to do data assimilation for the Alaska regional weather forecast model to improve Arctic marine stratus clouds forecast. Choosing physical options for the WRF model is discussed. Preprocess of AIRS/CrIS sounder data for data assimilation is described. Local observation data, satellite data, and global data assimilation data are used to verify and/or evaluate the forecast results by the MET tools Model Evaluation Tools (MET).

The regional climate model RegCM3 performances over several regions and climate regimes

NASA Astrophysics Data System (ADS)

Coppola, E.; Rauscher, S.; Gao, X.; Giorgi, F.; Im, E. S.; Mariotti, L.; Seth, A.; Sylla, M. B.

2009-04-01

Regional Climate models are more and more needed to provide high resolution regional climate information in climate impact studies. Water availability in a future scenario is the main request of policy makers for adaptation and mitigation purposes. However precipitation changes are unlikely to be as spatially coherent as temperature changes and they are closely related to the regional model itself. In addition model skill varies regionally. An example of several ICTP regional climate model (RegCM3) simulations is reported over China, Korea, Africa, Central and Southern America, Europe and Australia. Over China, Australia, and Korea the regional model improves the simulation compared to the driving GCM when compared with CRU observations. In China, for example, the higher resolution of the regional model inhibits the penetration of the monsoon precipitation front from the southern slope of the Himalaya onto the Tibetan Plateau. In Korea the nested domain simulation (20 km) shows an encouraging performance with regard to capturing extreme precipitation episodes and the finer spatial distribution reflects the detailed geography of the Korean Peninsula. Over South America, RegCM captures the annual cycle of precipitation over Northeast Brazil and the South American Monsoon region, although the monsoon onset occurs too early in the model. Precipitation over the Amazon is not well captured, with too little precipitation associated with weak easterlies and reduced moisture transport into the interior of the continent. RegCM simulates the annual cycle of precipitation over Central America and the Caribbean fairly well; in particular, the complex spatial distribution of the Mid-Summer Drought, a decrease in precipitation that occurs during the middle of the rainy season in July and August, is better captured by RegCM than by the GCM. In addition, RegCM simulates the strength and position of the Caribbean low level jet, a mesoscale feature related to precipitation anomalies in the region. Over Africa our analysis shows that RegCM3 is able to reproduce fairly well the spatial variability of seasonal mean temperature, precipitation and the associated low-level circulation. However, monsoon flow is over predicted while African Easterly Jet (AEJ) core underestimated and shifted a bit northward. Finally, over Europe the regional model shows a cold bias for most part of the year and a wet bias in winter and spring. Rain frequency is too high especially over the mountainous regions. The spatial patter of the precipitation extreme is well represented in the model although a slight overestimation of the 95, 98 99 percentile is evident.

Social Capital and Fear of Crime in Adolescence: A Multilevel Study.

PubMed

Vieno, Alessio; Lenzi, Michela; Roccato, Michele; Russo, Silvia; Monaci, Maria Grazia; Scacchi, Luca

2016-09-01

Hierarchical linear modeling was used to examine the relationships between social capital (at the individual, the neighborhood, and the regional levels) and adolescents' fear of crime, while controlling for the main individual (sociodemographics, television viewing, and bullying victimization), neighborhood (neighborhood size and aggregated victimization), and regional (crime rate and level of urbanization) variables. Data were analyzed using a three-level model based on 22,639 15.7-year-old (SD = 0.67) students nested within 1081 neighborhoods and 19 Italian regions. The findings revealed that individual and contextual measures of social capital, modeled at the individual, neighborhood, and regional levels simultaneously, showed negative associations with adolescents' fear of crime. Males and participants with higher family affluence were less likely to feel fear of crime, whereas victimization, both at the individual and neighborhood levels, had a positive association with fear of crime. Strengths, limitations, and potential applications of the study are discussed. © Society for Community Research and Action 2016.

Conference on the Ionosphere and Radio Wave Propagation, 3rd, University of Sydney, Australia, February 11-15, 1985, Proceedings

NASA Astrophysics Data System (ADS)

Cole, D. G.; McNamara, L. F.

1985-12-01

Various papers on the ionosphere and radio wave propagation are presented. The subjects discussed include: day-to-day variability in foF2 at low latitudes over a solar cycle; semiempirical, low-latitude ionospheric model; remote sensing with the Jindalee skywave radar; photographic approach to irregularities in the 80-100 km region; interference of radio waves in a CW system; study of the F-region characteristics at Waltair; recent developments in the international reference ionosphere; research-oriented ionosonde with directional capabilities; and ionospheric forecasting for specific applications. Also addressed are: experimental and theoretical techniques for the equatorial F region; empirical models of ionospheric electron concentration; the Jindalee ionospheric sounding system; a semiempirical midlatitude ionospheric model; Es structure using an HF radar; short-term variations in f0F2 and IEC; nonreciprocity in Omega propagation observed at middle latitudes; propagation management for no acknowledge HF links; new techniques in ionospheric sounding and studies; and lunar effects in the ionospheric F region.

Stable region for maxillary dental cast superimposition in adults, studied with the aid of stable miniscrews.

PubMed

Chen, G; Chen, S; Zhang, X Y; Jiang, R P; Liu, Y; Shi, F H; Xu, T M

2011-05-01

To identify a stable and reproducible reference region to superimpose serial maxillary dental models in adult extraction cases. Fifteen adult volunteers were enrolled. To reduce protrusion, bilateral maxillary first premolars were extracted in all volunteers. Each volunteer received six miniscrews, including two loaded miniscrews used to retract anterior teeth and four unloaded miniscrews. Impressions for maxillary models were taken at T1 (1 week after miniscrew placement) and T2 (17 months later). Dental models were created and then scanned using a laser scanner. Stability of the miniscrews was evaluated, and dental models were registered using stationary miniscrews. The palatal region, where deviation was within 0.5 mm in all subjects, was determined to be the stable region. Reproducibility of the new palatal region for 3D digital model superimposition was evaluated. Deviation of the medial 2/3 of the palatal region between the third rugae and the line in contact with the distal surface of the bilateral maxillary first molars was within 0.5 mm. Tooth movement of 15 subjects was measured to evaluate the validity of the new 3D superimposition method. Displacements were 8.18 ± 2.94 mm (central incisor) and 2.25 ± 0.73 mm (first molar) measured by miniscrew superimposition, while values of 7.81 ± 2.53 mm (central incisor) and 2.29 ± 1.03 mm (first molar) were measured using the 3D palatal vault regional superimposition method; no significant difference was observed. The medial 2/3 of the third rugae and the regional palatal vault dorsal to it is a stable region to register 3D digital models for evaluation of orthodontic tooth movement in adult patients. © 2011 John Wiley & Sons A/S.

Which complexity of regional climate system models is essential for downscaling anthropogenic climate change in the Northwest European Shelf?

NASA Astrophysics Data System (ADS)

Mathis, Moritz; Elizalde, Alberto; Mikolajewicz, Uwe

2018-04-01

Climate change impact studies for the Northwest European Shelf (NWES) make use of various dynamical downscaling strategies in the experimental setup of regional ocean circulation models. Projected change signals from coupled and uncoupled downscalings with different domain sizes and forcing global and regional models show substantial uncertainty. In this paper, we investigate influences of the downscaling strategy on projected changes in the physical and biogeochemical conditions of the NWES. Our results indicate that uncertainties due to different downscaling strategies are similar to uncertainties due to the choice of the parent global model and the downscaling regional model. Downscaled change signals reveal to depend stronger on the downscaling strategy than on the model skills in simulating present-day conditions. Uncoupled downscalings of sea surface temperature (SST) changes are found to be tightly constrained by the atmospheric forcing. The incorporation of coupled air-sea interaction, by contrast, allows the regional model system to develop independently. Changes in salinity show a higher sensitivity to open lateral boundary conditions and river runoff than to coupled or uncoupled atmospheric forcings. Dependencies on the downscaling strategy for changes in SST, salinity, stratification and circulation collectively affect changes in nutrient import and biological primary production.

Ionization correction factors for H II regions in blue compact dwarf galaxies

NASA Astrophysics Data System (ADS)

Holovatyi, V. V.; Melekh, B. Ya.

2002-08-01

Energy distributions in the spectra of the ionizing nuclei of H II regions beyond λ <= 91.2 nm were calculated. A grid of photoionization models of 270 H II regions was constructed. The free parameters of the model grid are the hydrogen density nH in the nebular gas, filling factor, energy Lc-spectrum of ionizing nuclei, and metallicity. The chemical composition from the studies of Izotov et al. were used for model grid initialization. The integral linear spectra calculated for the photoionization models were used to determine the concentration ne, temperatures Te of electrons, and ionic concentrations n(A+i)/n(H+) by the nebular gas diagnostic method. The averaged relative ionic abundances n(A+i)/n(H+) thus calculated were used to determine new expressions for ionization correction factors which we recommend for the determination of abundances in the H II regions of blue compact dwarf galaxies.

Empirical assessment of debris flow risk on a regional scale in Yunnan province, southwestern China.

PubMed

Liu, Xilin; Yue, Zhong Qi; Tham, Lesliw George; Lee, Chack Fan

2002-08-01

Adopting the definition suggested by the United Nations, a risk model for regional debris flow assessment is presented. Risk is defined as the product of hazard and vulnerability, both of which are necessary for evaluation. A Multiple-Factor Composite Assessment Model is developed for quantifying regional debris flow hazard by taking into account eight variables that contribute to debris flow magnitude and its frequency of occurrence. Vulnerability is a measure of the potential total losses. On a regional scale, it can be measured by the fixed asset, gross domestic product, land resources, population density, as well as the age, education, and wealth of the inhabitants. A nonlinear power-function assessment model that accounts for these indexes is developed. As a case study, the model is applied to compute the hazard, vulnerability and risk for each prefecture of the Yunnan province in southwestern China.

Modeling the effect of land use on carbon storage in the forests of the Pacific Northwest

NASA Technical Reports Server (NTRS)

Cohen, Warren B.; Wallin, David O.; Harmon, Mark E.; Sollins, Philip; Daly, Christopher; Ferrell, William K.

1992-01-01

There is concern as to how the balance of carbon in the terrestrial ecosystem will change in response to a variety of land use practices. A study is described in which a methodology is being developed to help narrow this uncertainty for the temperate forets of the Pacific Northwest region of the US. A carbon storage model is being developed to respond to forest harvesting, the dominant use of land in the region. By linking the carbon model to satellite imagery and a climate simulation model, the current amount of carbon stored in the forests of the Pacific northwest is estimated. The archive of Landsat multispectral scanner (MSS) images permits a 20-year historical perspective of land use changes in the region. With these data, the recent impact of regional land use in forest carbon stores is assessed.

Can Regional Climate Modeling Capture the Observed Changes in Spatial Organization of Extreme Storms at Higher Temperatures?

NASA Astrophysics Data System (ADS)

Li, J.; Wasko, C.; Johnson, F.; Evans, J. P.; Sharma, A.

2018-05-01

The spatial extent and organization of extreme storm events has important practical implications for flood forecasting. Recently, conflicting evidence has been found on the observed changes of storm spatial extent with increasing temperatures. To further investigate this question, a regional climate model assessment is presented for the Greater Sydney region, in Australia. Two regional climate models were considered: the first a convection-resolving simulation at 2-km resolution, the second a resolution of 10 km with three different convection parameterizations. Both the 2- and the 10-km resolutions that used the Betts-Miller-Janjic convective scheme simulate decreasing storm spatial extent with increasing temperatures for 1-hr duration precipitation events, consistent with the observation-based study in Australia. However, other observed relationships of extreme rainfall with increasing temperature were not well represented by the models. Improved methods for considering storm organization are required to better understand potential future changes.

Geophysical Model Research and Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pasyanos, M; Walter, W; Tkalcic, H

2004-07-07

Geophysical models constitute an important component of calibration for nuclear explosion monitoring. We will focus on four major topics: (1) a priori geophysical models, (2) surface wave models, (3) receiver function derived profiles, and (4) stochastic geophysical models. The first, a priori models, can be used to predict a host of geophysical measurements, such as body wave travel times, and can be derived from direct regional studies or even by geophysical analogy. Use of these models is particularly important in aseismic regions or regions without seismic stations, where data of direct measurements might not exist. Lawrence Livermore National Laboratory (LLNL)more » has developed the Western Eurasia and North Africa (WENA) model which has been evaluated using a number of data sets, including travel times, surface waves, receiver functions, and waveform analysis (Pasyanos et al., 2004). We have joined this model with our Yellow Sea - Korean Peninsula (YSKP) model and the Los Alamos National Laboratory (LANL) East Asia model to construct a model for all of Eurasia and North Africa. Secondly, we continue to improve upon our surface wave model by adding more paths. This has allowed us to expand the region to all of Eurasia and into Africa, increase the resolution of our model, and extend results to even shorter periods (7 sec). High-resolution models exist for the Middle East and the YSKP region. The surface wave results can be inverted either alone, or in conjunction with other data, to derive models of the crust and upper mantle structure. We are also using receiver functions, in joint inversions with the surface waves, to produce profiles directly under seismic stations throughout the region. In a collaborative project with Ammon, et al., they have been focusing on stations throughout western Eurasia and North Africa, while we have been focusing on LLNL deployments in the Middle East, including Kuwait, Jordan, and the United Arab Emirates. Finally, we have been exploring methodologies such as Markov Chain Monte Carlo (MCMC) to generate data-driven stochastic models. We have applied this technique to the YSKP region using surface wave dispersion data, body wave travel time data, and receiver functions.« less

The role of country-to-region assignments in global integrated modeling of energy, agriculture, land use, and climate

NASA Astrophysics Data System (ADS)

Kyle, P.; Patel, P.; Calvin, K. V.

2014-12-01

Global integrated assessment models used for understanding the linkages between the future energy, agriculture, and climate systems typically represent between 8 and 30 geopolitical macro-regions, balancing the benefits of geographic resolution with the costs of additional data collection, processing, analysis, and computing resources. As these models are continually being improved and updated in order to address new questions for the research and policy communities, it is worth examining the consequences of the country-to-region mapping schemes used for model results. This study presents an application of a data processing system built for the GCAM integrated assessment model that allows any country-to-region assignments, with a minimum of four geopolitical regions and a maximum of 185. We test ten different mapping schemes, including the specific mappings used in existing major integrated assessment models. We also explore the impacts of clustering nations into regions according to the similarity of the structure of each nation's energy and agricultural sectors, as indicated by multivariate analysis. Scenarios examined include a reference scenario, a low-emissions scenario, and scenarios with agricultural and buildings sector climate change impacts. We find that at the global level, the major output variables (primary energy, agricultural land use) are surprisingly similar regardless of regional assignments, but at finer geographic scales, differences are pronounced. We suggest that enhancing geographic resolution is advantageous for analysis of climate impacts on the buildings and agricultural sectors, due to the spatial heterogeneity of these drivers.

Neurons derived from different brain regions are inherently different in vitro: a novel multiregional brain-on-a-chip.

PubMed

Dauth, Stephanie; Maoz, Ben M; Sheehy, Sean P; Hemphill, Matthew A; Murty, Tara; Macedonia, Mary Kate; Greer, Angie M; Budnik, Bogdan; Parker, Kevin Kit

2017-03-01

Brain in vitro models are critically important to developing our understanding of basic nervous system cellular physiology, potential neurotoxic effects of chemicals, and specific cellular mechanisms of many disease states. In this study, we sought to address key shortcomings of current brain in vitro models: the scarcity of comparative data for cells originating from distinct brain regions and the lack of multiregional brain in vitro models. We demonstrated that rat neurons from different brain regions exhibit unique profiles regarding their cell composition, protein expression, metabolism, and electrical activity in vitro. In vivo, the brain is unique in its structural and functional organization, and the interactions and communication between different brain areas are essential components of proper brain function. This fact and the observation that neurons from different areas of the brain exhibit unique behaviors in vitro underline the importance of establishing multiregional brain in vitro models. Therefore, we here developed a multiregional brain-on-a-chip and observed a reduction of overall firing activity, as well as altered amounts of astrocytes and specific neuronal cell types compared with separately cultured neurons. Furthermore, this multiregional model was used to study the effects of phencyclidine, a drug known to induce schizophrenia-like symptoms in vivo, on individual brain areas separately while monitoring downstream effects on interconnected regions. Overall, this work provides a comparison of cells from different brain regions in vitro and introduces a multiregional brain-on-a-chip that enables the development of unique disease models incorporating essential in vivo features. NEW & NOTEWORTHY Due to the scarcity of comparative data for cells from different brain regions in vitro, we demonstrated that neurons isolated from distinct brain areas exhibit unique behaviors in vitro. Moreover, in vivo proper brain function is dependent on the connection and communication of several brain regions, underlining the importance of developing multiregional brain in vitro models. We introduced a novel brain-on-a-chip model, implementing essential in vivo features, such as different brain areas and their functional connections. Copyright © 2017 the American Physiological Society.

Neurons derived from different brain regions are inherently different in vitro: a novel multiregional brain-on-a-chip

PubMed Central

Dauth, Stephanie; Maoz, Ben M.; Sheehy, Sean P.; Hemphill, Matthew A.; Murty, Tara; Macedonia, Mary Kate; Greer, Angie M.; Budnik, Bogdan

2017-01-01

Brain in vitro models are critically important to developing our understanding of basic nervous system cellular physiology, potential neurotoxic effects of chemicals, and specific cellular mechanisms of many disease states. In this study, we sought to address key shortcomings of current brain in vitro models: the scarcity of comparative data for cells originating from distinct brain regions and the lack of multiregional brain in vitro models. We demonstrated that rat neurons from different brain regions exhibit unique profiles regarding their cell composition, protein expression, metabolism, and electrical activity in vitro. In vivo, the brain is unique in its structural and functional organization, and the interactions and communication between different brain areas are essential components of proper brain function. This fact and the observation that neurons from different areas of the brain exhibit unique behaviors in vitro underline the importance of establishing multiregional brain in vitro models. Therefore, we here developed a multiregional brain-on-a-chip and observed a reduction of overall firing activity, as well as altered amounts of astrocytes and specific neuronal cell types compared with separately cultured neurons. Furthermore, this multiregional model was used to study the effects of phencyclidine, a drug known to induce schizophrenia-like symptoms in vivo, on individual brain areas separately while monitoring downstream effects on interconnected regions. Overall, this work provides a comparison of cells from different brain regions in vitro and introduces a multiregional brain-on-a-chip that enables the development of unique disease models incorporating essential in vivo features. NEW & NOTEWORTHY Due to the scarcity of comparative data for cells from different brain regions in vitro, we demonstrated that neurons isolated from distinct brain areas exhibit unique behaviors in vitro. Moreover, in vivo proper brain function is dependent on the connection and communication of several brain regions, underlining the importance of developing multiregional brain in vitro models. We introduced a novel brain-on-a-chip model, implementing essential in vivo features, such as different brain areas and their functional connections. PMID:28031399

Spatiotemporal Distribution of β-Amyloid in Alzheimer Disease Is the Result of Heterogeneous Regional Carrying Capacities.

PubMed

Whittington, Alex; Sharp, David J; Gunn, Roger N

2018-05-01

β-amyloid (Aβ) accumulation in the brain is 1 of 2 pathologic hallmarks of Alzheimer disease (AD), and the spatial distribution of Aβ has been studied extensively ex vivo. Methods: We applied mathematical modeling to Aβ in vivo PET imaging data to investigate competing theories of Aβ spread in AD. Results: Our results provided evidence that Aβ accumulation starts in all brain regions simultaneously and that its spatiotemporal distribution is due to heterogeneous regional carrying capacities (regional maximum possible concentration of Aβ) for the aggregated protein rather than to longer-term spreading from seed regions. Conclusion: The in vivo spatiotemporal distribution of Aβ in AD can be mathematically modeled using a logistic growth model in which the Aβ carrying capacity is heterogeneous across the brain but the exponential growth rate and time of half maximal Aβ concentration are constant. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Case studies of seasonal rainfall forecasts for Hong Kong and its vicinity using a regional climate model

Treesearch

David Hui; Karen Shum; Ji Chen; Shyh-Chin Chen; Jack Ritchie; John Roads

2007-01-01

Seasonal climate forecasts are one of the most promising tools for providing early warnings for natural hazards such as floods and droughts. Using two case studies, this paper documents the skill of a regional climate model in the seasonal forecasting of below normal rainfall in southern China during the rainy seasons of July–August–September 2003 and April–...

The regionalization of national-scale SPARROW models for stream nutrients

USGS Publications Warehouse

Schwarz, Gregory E.; Alexander, Richard B.; Smith, Richard A.; Preston, Stephen D.

2011-01-01

This analysis modifies the parsimonious specification of recently published total nitrogen (TN) and total phosphorus (TP) national-scale SPAtially Referenced Regressions On Watershed attributes models to allow each model coefficient to vary geographically among three major river basins of the conterminous United States. Regionalization of the national models reduces the standard errors in the prediction of TN and TP loads, expressed as a percentage of the predicted load, by about 6 and 7%. We develop and apply a method for combining national-scale and regional-scale information to estimate a hybrid model that imposes cross-region constraints that limit regional variation in model coefficients, effectively reducing the number of free model parameters as compared to a collection of independent regional models. The hybrid TN and TP regional models have improved model fit relative to the respective national models, reducing the standard error in the prediction of loads, expressed as a percentage of load, by about 5 and 4%. Only 19% of the TN hybrid model coefficients and just 2% of the TP hybrid model coefficients show evidence of substantial regional specificity (more than ±100% deviation from the national model estimate). The hybrid models have much greater precision in the estimated coefficients than do the unconstrained regional models, demonstrating the efficacy of pooling information across regions to improve regional models.

Mixed precipitation occurrences over southern Québec, Canada, under warmer climate conditions using a regional climate model

NASA Astrophysics Data System (ADS)

Matte, Dominic; Thériault, Julie M.; Laprise, René

2018-05-01

Winter weather events with temperatures near 0°C are often associated with freezing rain. They can have major impacts on the society by causing power outages and disruptions to the transportation networks. Despite the catastrophic consequences of freezing rain, very few studies have investigated how their occurrences could evolve under climate change. This study aims to investigate the change of freezing rain and ice pellets over southern Québec using regional climate modeling at high resolution. The fifth-generation Canadian Regional Climate Model with climate scenario RCP 8.5 at 0.11° grid mesh was used. The precipitation types such as freezing rain, ice pellets or their combination are diagnosed using five methods (Cantin and Bachand, Bourgouin, Ramer, Czys and, Baldwin). The occurrences of the diagnosed precipitation types for the recent past (1980-2009) are found to be comparable to observations. The projections for the future scenario (2070-2099) suggested a general decrease in the occurrences of mixed precipitation over southern Québec from October to April. This is mainly due to a decrease in long-duration events (≥6 h ). Overall, this study contributes to better understand how the distribution of freezing rain and ice pellets might change in the future using high-resolution regional climate model.

Does temperature nudging overwhelm aerosol radiative effects in regional integrated climate models?

NASA Astrophysics Data System (ADS)

He, Jian; Glotfelty, Timothy; Yahya, Khairunnisa; Alapaty, Kiran; Yu, Shaocai

2017-04-01

Nudging (data assimilation) is used in many regional integrated meteorology-air quality models to reduce biases in simulated climatology. However, in such modeling systems, temperature changes due to nudging could compete with temperature changes induced by radiatively active and hygroscopic short-lived tracers leading to two interesting dilemmas: when nudging is continuously applied, what are the relative sizes of these two radiative forces at regional and local scales? How do these two forces present in the free atmosphere differ from those present at the surface? This work studies these two issues by converting temperature changes due to nudging into pseudo radiative effects (PRE) at the surface (PRE_sfc), in troposphere (PRE_atm), and at the top of atmosphere (PRE_toa), and comparing PRE with the reported aerosol radiative effects (ARE). Results show that the domain-averaged PRE_sfc is smaller than ARE_sfc estimated in previous studies and this work, but could be significantly larger than ARE_sfc at local scales. PRE_atm is also much smaller than ARE_atm. These results indicate that appropriate nudging methodology could be applied to the integrated models to study aerosol radiative effects at continental/regional scales, but it should be treated with caution for local scale applications.

Northeastern Brazilian margin: Regional tectonic evolution based on integrated analysis of seismic reflection and potential field data and modelling

NASA Astrophysics Data System (ADS)

Blaich, Olav A.; Tsikalas, Filippos; Faleide, Jan Inge

2008-10-01

Integration of regional seismic reflection and potential field data along the northeastern Brazilian margin, complemented by crustal-scale gravity modelling, is used to reveal and illustrate onshore-offshore crustal structure correlation, the character of the continent-ocean boundary, and the relationship of crustal structure to regional variation of potential field anomalies. The study reveals distinct along-margin structural and magmatic changes that are spatially related to a number of conjugate Brazil-West Africa transfer systems, governing the margin segmentation and evolution. Several conceptual tectonic models are invoked to explain the structural evolution of the different margin segments in a conjugate margin context. Furthermore, the constructed transects, the observed and modelled Moho relief, and the potential field anomalies indicate that the Recôncavo, Tucano and Jatobá rift system may reflect a polyphase deformation rifting-mode associated with a complex time-dependent thermal structure of the lithosphere. The constructed transects and available seismic reflection profiles, indicate that the northern part of the study area lacks major breakup-related magmatic activity, suggesting a rifted non-volcanic margin affinity. In contrast, the southern part of the study area is characterized by abrupt crustal thinning and evidence for breakup magmatic activity, suggesting that this region evolved, partially, with a rifted volcanic margin affinity and character.

An integrated model for assessing both crop productivity and agricultural water resources at a large scale

NASA Astrophysics Data System (ADS)

Okada, M.; Sakurai, G.; Iizumi, T.; Yokozawa, M.

2012-12-01

Agricultural production utilizes regional resources (e.g. river water and ground water) as well as local resources (e.g. temperature, rainfall, solar energy). Future climate changes and increasing demand due to population increases and economic developments would intensively affect the availability of water resources for agricultural production. While many studies assessed the impacts of climate change on agriculture, there are few studies that dynamically account for changes in water resources and crop production. This study proposes an integrated model for assessing both crop productivity and agricultural water resources at a large scale. Also, the irrigation management to subseasonal variability in weather and crop response varies for each region and each crop. To deal with such variations, we used the Markov Chain Monte Carlo technique to quantify regional-specific parameters associated with crop growth and irrigation water estimations. We coupled a large-scale crop model (Sakurai et al. 2012), with a global water resources model, H08 (Hanasaki et al. 2008). The integrated model was consisting of five sub-models for the following processes: land surface, crop growth, river routing, reservoir operation, and anthropogenic water withdrawal. The land surface sub-model was based on a watershed hydrology model, SWAT (Neitsch et al. 2009). Surface and subsurface runoffs simulated by the land surface sub-model were input to the river routing sub-model of the H08 model. A part of regional water resources available for agriculture, simulated by the H08 model, was input as irrigation water to the land surface sub-model. The timing and amount of irrigation water was simulated at a daily step. The integrated model reproduced the observed streamflow in an individual watershed. Additionally, the model accurately reproduced the trends and interannual variations of crop yields. To demonstrate the usefulness of the integrated model, we compared two types of impact assessment of climate change on crop productivity in a watershed. The first was carried out by the large-scale crop model alone. The second was carried out by the integrated model of the large-scale crop model and the H08 model. The former projected that changes in temperature and precipitation due to future climate change would give rise to increasing the water stress in crops. Nevertheless, the latter projected that the increasing amount of agricultural water resources in the watershed would supply sufficient amount of water for irrigation, consequently reduce the water stress. The integrated model demonstrated the importance of taking into account the water circulation in watershed when predicting the regional crop production.

Evaluating wind extremes in CMIP5 climate models

NASA Astrophysics Data System (ADS)

Kumar, Devashish; Mishra, Vimal; Ganguly, Auroop R.

2015-07-01

Wind extremes have consequences for renewable energy sectors, critical infrastructures, coastal ecosystems, and insurance industry. Considerable debates remain regarding the impacts of climate change on wind extremes. While climate models have occasionally shown increases in regional wind extremes, a decline in the magnitude of mean and extreme near-surface wind speeds has been recently reported over most regions of the Northern Hemisphere using observed data. Previous studies of wind extremes under climate change have focused on selected regions and employed outputs from the regional climate models (RCMs). However, RCMs ultimately rely on the outputs of global circulation models (GCMs), and the value-addition from the former over the latter has been questioned. Regional model runs rarely employ the full suite of GCM ensembles, and hence may not be able to encapsulate the most likely projections or their variability. Here we evaluate the performance of the latest generation of GCMs, the Coupled Model Intercomparison Project phase 5 (CMIP5), in simulating extreme winds. We find that the multimodel ensemble (MME) mean captures the spatial variability of annual maximum wind speeds over most regions except over the mountainous terrains. However, the historical temporal trends in annual maximum wind speeds for the reanalysis data, ERA-Interim, are not well represented in the GCMs. The historical trends in extreme winds from GCMs are statistically not significant over most regions. The MME model simulates the spatial patterns of extreme winds for 25-100 year return periods. The projected extreme winds from GCMs exhibit statistically less significant trends compared to the historical reference period.

Analysis of variables affecting unemployment rate and detecting for cluster in West Java, Central Java, and East Java in 2012

NASA Astrophysics Data System (ADS)

Samuel, Putra A.; Widyaningsih, Yekti; Lestari, Dian

2016-02-01

The objective of this study is modeling the Unemployment Rate (UR) in West Java, Central Java, and East Java, with rate of disease, infant mortality rate, educational level, population size, proportion of married people, and GDRP as the explanatory variables. Spatial factors are also considered in the modeling since the closer the distance, the higher the correlation. This study uses the secondary data from BPS (Badan Pusat Statistik). The data will be analyzed using Moran I test, to obtain the information about spatial dependence, and using Spatial Autoregressive modeling to obtain the information, which variables are significant affecting UR and how great the influence of the spatial factors. The result is, variables proportion of married people, rate of disease, and population size are related significantly to UR. In all three regions, the Hotspot of unemployed will also be detected districts/cities using Spatial Scan Statistics Method. The results are 22 districts/cities as a regional group with the highest unemployed (Most likely cluster) in the study area; 2 districts/cities as a regional group with the highest unemployed in West Java; 1 district/city as a regional groups with the highest unemployed in Central Java; 15 districts/cities as a regional group with the highest unemployed in East Java.

A comparative study on the stress distribution around dental implants in three arch form models for replacing six implants using finite element analysis.

PubMed

Zarei, Maryam; Jahangirnezhad, Mahmoud; Yousefimanesh, Hojatollah; Robati, Maryam; Robati, Hossein

2018-01-01

Dental implant is a method to replacement of missing teeth. It is important for replacing the missed anterior teeth. In vitro method is a safe method for evaluation of stress distribution. Finite element analysis as an in vitro method evaluated stress distribution around replacement of six maxillary anterior teeth implants in three models of maxillary arch. In this in vitro study, using ABAQUS software (Simulia Corporation, Vélizy-Villacoublay, France), implant simulation was performed for reconstruction of six maxillary anterior teeth in three models. Two implants were placed on both sides of the canine tooth region (A model); two implants on both sides of the canine tooth region and another on one side of the central incisor region (B model); and two implants on both sides of the canine tooth region and two implants in the central incisor area (C model). All implants evaluated in three arch forms (tapered, ovoid, and square). Data were analyzed by finite analysis software. Von Mises stress by increasing of implant number was reduced. In a comparison of A model in each maxillary arch, the stress created in the cortical and cancellous bones in the square arch was less than ovoid and tapered arches. The stress created in implants and cortical and cancellous bones in C model was less than A and B models. The C model (four-implant) reduced the stress distribution in cortical and cancellous bones, but this pattern must be evaluated according to arch form and cost benefit of patients.

Creation of an in vitro biomechanical model of the trachea using rapid prototyping.

PubMed

Walenga, Ross L; Longest, P Worth; Sundaresan, Gobalakrishnan

2014-06-03

Previous in vitro models of the airways are either rigid or, if flexible, have not matched in vivo compliance characteristics. Rapid prototyping provides a quickly evolving approach that can be used to directly produce in vitro airway models using either rigid or flexible polymers. The objective of this study was to use rapid prototyping to directly produce a flexible hollow model that matches the biomechanical compliance of the trachea. The airway model consisted of a previously developed characteristic mouth-throat region, the trachea, and a portion of the main bronchi. Compliance of the tracheal region was known from a previous in vivo imaging study that reported cross-sectional areas over a range of internal pressures. The compliance of the tracheal region was matched to the in vivo data for a specific flexible resin by iteratively selecting the thicknesses and other dimensions of tracheal wall components. Seven iterative models were produced and illustrated highly non-linear expansion consisting of initial rapid size increase, a transition region, and continued slower size increase as pressure was increased. Thickness of the esophageal interface membrane and initial trachea indention were identified as key parameters with the final model correctly predicting all phases of expansion within a value of 5% of the in vivo data. Applications of the current biomechanical model are related to endotracheal intubation and include determination of effective mucus suctioning and evaluation of cuff sealing with respect to gases and secretions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Application of physical scaling towards downscaling climate model precipitation data

NASA Astrophysics Data System (ADS)

Gaur, Abhishek; Simonovic, Slobodan P.

2018-04-01

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

Constructing an everywhere and locally relevant predictive model of the West-African critical zone

NASA Astrophysics Data System (ADS)

Hector, B.; Cohard, J. M.; Pellarin, T.; Maxwell, R. M.; Cappelaere, B.; Demarty, J.; Grippa, M.; Kergoat, L.; Lebel, T.; Mamadou, O.; Mougin, E.; Panthou, G.; Peugeot, C.; Vandervaere, J. P.; Vischel, T.; Vouillamoz, J. M.

2017-12-01

Considering water resources and hydrologic hazards, West Africa is among the most vulnerable regions to face both climatic (e.g. with the observed intensification of precipitation) and anthropogenic changes. With +3% of demographic rate, the region experiences rapid land use changes and increased pressure on surface and groundwater resources with observed consequences on the hydrological cycle (water table rise result of the sahelian paradox, increase in flood occurrence, etc.) Managing large hydrosystems (such as transboundary aquifers or rivers basins as the Niger river) requires anticipation of such changes. However, the region significantly lacks observations, for constructing and validating critical zone (CZ) models able to predict future hydrologic regime, but also comprises hydrosystems which encompass strong environmental gradients (e.g. geological, climatic, ecological) with highly different dominating hydrological processes. We address these issues by constructing a high resolution (1 km²) regional scale physically-based model using ParFlow-CLM which allows modeling a wide range of processes without prior knowledge on their relative dominance. Our approach combines multiple scale modeling from local to meso and regional scales within the same theoretical framework. Local and meso-scale models are evaluated thanks to the rich AMMA-CATCH CZ observation database which covers 3 supersites with contrasted environments in Benin (Lat.: 9.8°N), Niger (Lat.: 13.3°N) and Mali (Lat.: 15.3°N). At the regional scale the lack of relevant map of soil hydrodynamic parameters is addressed using remote sensing data assimilation. Our first results show the model's ability to reproduce the known dominant hydrological processes (runoff generation, ET, groundwater recharge…) across the major West-African regions and allow us to conduct virtual experiments to explore the impact of global changes on the hydrosystems. This approach is a first step toward the construction of a reference model to study regional CZ sensitivity to global changes and will help to identify prior parameters required and to construct meta-models for deeper investigations of interactions within the CZ.

Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and generalized additive modeling.

PubMed

Thelen, Brian; French, Nancy H F; Koziol, Benjamin W; Billmire, Michael; Owen, Robert Chris; Johnson, Jeffrey; Ginsberg, Michele; Loboda, Tatiana; Wu, Shiliang

2013-11-05

A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. The model developed in this study allows a quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data.

REDRAW-Based Evapotranspiration Estimation in Chongli, North China

NASA Astrophysics Data System (ADS)

Zhang, Z.; Wang, Z.

2017-12-01

Evapotranspiration (ET) is the key component of hydrological cycle and spatial estimates of ET are important elements of atmospheric circulation and hydrologic models. Quantifying the ET over large region is significant for water resources planning, hydrologic water balances, water rights management, and water division. In this study, Evapotranspiration (ET) was estimated using REDRAW model in the Chongli on 2014. REDRAW is a satellite-based balance algorithm with reference dry and wet limits model developed to estimate ET. Remote sensing data obtained from MODIS and meteorological data from China Meteorological Data Sharing Service System were used in ET model. In order to analyze the distribution and time variation of ET over the study region, daily, monthly and yearly ET were calculated for the study area, and ET of different land cover types were calculated. In terms of the monthly ET, the figure was low in winter and high in other seasons, and reaches the maximum value in August, showing a high monthly difference. The ET value of water body was the highest and that of barren or sparse vegetation were the lowest, which accorded with local actual condition. Evaluating spatial temporal distribution of actual ET could assist to understand the water consumption regularity in region and figure out the effect from different land cover, which helped to establish links between land use, water allocation, and water use planning in study region. Due to the groundwater recession in north China, the evaluation of regional total water resources become increasingly essential, and the result of this study can be used to plan the water use. As the Chongli will prepare the ski slopes for Winter Olympics on 2022, accuracy estimation of actual ET can efficiently resolve water conflict and relieve water scarcity.

Projected changes in rainfall and temperature over homogeneous regions of India

NASA Astrophysics Data System (ADS)

Patwardhan, Savita; Kulkarni, Ashwini; Rao, K. Koteswara

2018-01-01

The impact of climate change on the characteristics of seasonal maximum and minimum temperature and seasonal summer monsoon rainfall is assessed over five homogeneous regions of India using a high-resolution regional climate model. Providing REgional Climate for Climate Studies (PRECIS) is developed at Hadley Centre for Climate Prediction and Research, UK. The model simulations are carried out over South Asian domain for the continuous period of 1961-2098 at 50-km horizontal resolution. Here, three simulations from a 17-member perturbed physics ensemble (PPE) produced using HadCM3 under the Quantifying Model Uncertainties in Model Predictions (QUMP) project of Hadley Centre, Met. Office, UK, have been used as lateral boundary conditions (LBCs) for the 138-year simulations of the regional climate model under Intergovernmental Panel on Climate Change (IPCC) A1B scenario. The projections indicate the increase in the summer monsoon (June through September) rainfall over all the homogeneous regions (15 to 19%) except peninsular India (around 5%). There may be marginal change in the frequency of medium and heavy rainfall events (>20 mm) towards the end of the present century. The analysis over five homogeneous regions indicates that the mean maximum surface air temperatures for the pre-monsoon season (March-April-May) as well as the mean minimum surface air temperature for winter season (January-February) may be warmer by around 4 °C towards the end of the twenty-first century.

Time-series Oxygen-18 Precipitation Isoscapes for Canada and the Northern United States

NASA Astrophysics Data System (ADS)

Delavau, Carly J.; Chun, Kwok P.; Stadnyk, Tricia A.; Birks, S. Jean; Welker, Jeffrey M.

2014-05-01

The present and past hydrological cycle from the watershed to regional scale can be greatly enhanced using water isotopes (δ18O and δ2H), displayed today as isoscapes. The development of water isoscapes has both hydrological and ecological applications, such as ground water recharge and food web ecology, and can provide critical information when observations are not available due to spatial and temporal gaps in sampling and data networks. This study focuses on the creation of δ18O precipitation (δ18Oppt) isoscapes at a monthly temporal frequency across Canada and the northern United States (US) utilizing CNIP (Canadian Network for Isotopes in Precipitation) and USNIP (United States Network for Isotopes in Precipitation) measurements. Multiple linear stepwise regressions of CNIP and USNIP observations alongside NARR (North American Regional Reanalysis) climatological variables, teleconnection indices, and geographic indicators are utilized to create empirical models that predict the δ18O of monthly precipitation across Canada and the northern US. Pooling information from nearby locations within a region can be useful due to the similarity of processes and mechanisms controlling the variability of δ18O. We expect similarity in the controls on isotopic composition to strengthen the correlation between δ18Oppt and predictor variables, resulting in model simulation improvements. For this reason, three different regionalization approaches are used to separate the study domain into 'isotope zones' to explore the effect of regionalization on model performance. This methodology results in 15 empirical models, five within each regionalization. A split sample calibration and validation approach is employed for model development, and parameter selection is based on demonstrated improvement of the Akaike Information Criteria (AIC). Simulation results indicate the empirical models are generally able to capture the overall monthly variability in δ18Oppt. For the three regionalizations, average adjusted-R2 and RMSE (weighted to number of observations within each isotope zone) range from 0.70 - 0.72 and 2.76 - 2.91, respectively, indicating that on average the different spatial groupings perform comparably. Validation weighted R2and RMSE show a larger spread between models and poorer performance, ranging from 0.45 - 0.59 and 3.28 - 3.39, respectively. Additional evaluation of simulated δ18Oppt at each station and inter/intra-annually is conducted to evaluate model performance over various space and time scales. Stepwise regression derived parameterizations indicate the significance of precipitable water content and latitude as predictor variables for all regionalizations. Long-term (1981-2010) annual average δ18Oppt isoscapes are produced for Canada and the northern US, highlighting the differences between regionalization approaches. 95% confidence interval maps are generated to provide an estimate of the uncertainty associated with long-term δ18Oppt simulations. This is the first ever time-series empirical modelling of δ18Oppt for Canada utilizing CNIP data, as well as the first modelling collaboration between the CNIP and USNIP networks. This study is the initial step towards empirically derived time-series δ18Oppt for use in iso-hydrological modelling studies. Methods and results from this research are equally applicable to ecology and forensics as the simulated δ18Oppt isoscapes provide the primary oxygen source for many plants and foodwebs at refined temporal and spatial scales across Canada and the northern US.

Improving operating room productivity via parallel anesthesia processing.

PubMed

Brown, Michael J; Subramanian, Arun; Curry, Timothy B; Kor, Daryl J; Moran, Steven L; Rohleder, Thomas R

2014-01-01

Parallel processing of regional anesthesia may improve operating room (OR) efficiency in patients undergoes upper extremity surgical procedures. The purpose of this paper is to evaluate whether performing regional anesthesia outside the OR in parallel increases total cases per day, improve efficiency and productivity. Data from all adult patients who underwent regional anesthesia as their primary anesthetic for upper extremity surgery over a one-year period were used to develop a simulation model. The model evaluated pure operating modes of regional anesthesia performed within and outside the OR in a parallel manner. The scenarios were used to evaluate how many surgeries could be completed in a standard work day (555 minutes) and assuming a standard three cases per day, what was the predicted end-of-day time overtime. Modeling results show that parallel processing of regional anesthesia increases the average cases per day for all surgeons included in the study. The average increase was 0.42 surgeries per day. Where it was assumed that three cases per day would be performed by all surgeons, the days going to overtime was reduced by 43 percent with parallel block. The overtime with parallel anesthesia was also projected to be 40 minutes less per day per surgeon. Key limitations include the assumption that all cases used regional anesthesia in the comparisons. Many days may have both regional and general anesthesia. Also, as a case study, single-center research may limit generalizability. Perioperative care providers should consider parallel administration of regional anesthesia where there is a desire to increase daily upper extremity surgical case capacity. Where there are sufficient resources to do parallel anesthesia processing, efficiency and productivity can be significantly improved. Simulation modeling can be an effective tool to show practice change effects at a system-wide level.

Imaging-based biomarkers of cognitive performance in older adults constructed via high-dimensional pattern regression applied to MRI and PET.

PubMed

Wang, Ying; Goh, Joshua O; Resnick, Susan M; Davatzikos, Christos

2013-01-01

In this study, we used high-dimensional pattern regression methods based on structural (gray and white matter; GM and WM) and functional (positron emission tomography of regional cerebral blood flow; PET) brain data to identify cross-sectional imaging biomarkers of cognitive performance in cognitively normal older adults from the Baltimore Longitudinal Study of Aging (BLSA). We focused on specific components of executive and memory domains known to decline with aging, including manipulation, semantic retrieval, long-term memory (LTM), and short-term memory (STM). For each imaging modality, brain regions associated with each cognitive domain were generated by adaptive regional clustering. A relevance vector machine was adopted to model the nonlinear continuous relationship between brain regions and cognitive performance, with cross-validation to select the most informative brain regions (using recursive feature elimination) as imaging biomarkers and optimize model parameters. Predicted cognitive scores using our regression algorithm based on the resulting brain regions correlated well with actual performance. Also, regression models obtained using combined GM, WM, and PET imaging modalities outperformed models based on single modalities. Imaging biomarkers related to memory performance included the orbito-frontal and medial temporal cortical regions with LTM showing stronger correlation with the temporal lobe than STM. Brain regions predicting executive performance included orbito-frontal, and occipito-temporal areas. The PET modality had higher contribution to most cognitive domains except manipulation, which had higher WM contribution from the superior longitudinal fasciculus and the genu of the corpus callosum. These findings based on machine-learning methods demonstrate the importance of combining structural and functional imaging data in understanding complex cognitive mechanisms and also their potential usage as biomarkers that predict cognitive status.

Prediction of monthly regional groundwater levels through hybrid soft-computing techniques

NASA Astrophysics Data System (ADS)

Chang, Fi-John; Chang, Li-Chiu; Huang, Chien-Wei; Kao, I.-Feng

2016-10-01

Groundwater systems are intrinsically heterogeneous with dynamic temporal-spatial patterns, which cause great difficulty in quantifying their complex processes, while reliable predictions of regional groundwater levels are commonly needed for managing water resources to ensure proper service of water demands within a region. In this study, we proposed a novel and flexible soft-computing technique that could effectively extract the complex high-dimensional input-output patterns of basin-wide groundwater-aquifer systems in an adaptive manner. The soft-computing models combined the Self Organized Map (SOM) and the Nonlinear Autoregressive with Exogenous Inputs (NARX) network for predicting monthly regional groundwater levels based on hydrologic forcing data. The SOM could effectively classify the temporal-spatial patterns of regional groundwater levels, the NARX could accurately predict the mean of regional groundwater levels for adjusting the selected SOM, the Kriging was used to interpolate the predictions of the adjusted SOM into finer grids of locations, and consequently the prediction of a monthly regional groundwater level map could be obtained. The Zhuoshui River basin in Taiwan was the study case, and its monthly data sets collected from 203 groundwater stations, 32 rainfall stations and 6 flow stations during 2000 and 2013 were used for modelling purpose. The results demonstrated that the hybrid SOM-NARX model could reliably and suitably predict monthly basin-wide groundwater levels with high correlations (R2 > 0.9 in both training and testing cases). The proposed methodology presents a milestone in modelling regional environmental issues and offers an insightful and promising way to predict monthly basin-wide groundwater levels, which is beneficial to authorities for sustainable water resources management.

Effects of forest cover changes in European Russia on regional weather conditions: results of numerical experiments with the COSMO-CLM model

NASA Astrophysics Data System (ADS)

Olchev, Alexander; Kuzmina, Ekaterina; Rozinkina, Inna; Nikitin, Mikhail; Rivin, Gdaly S.

2017-04-01

The forests have a significant effect on the climatic system. They capture CO2 from the atmosphere, regulate the surface evaporation and runoff, and influence the radiation and thermal conditions of the land surface. It is obvious, that their influence depends on many different factors including regional climate conditions, land use and vegetation structure, surface topography, etc. The main goal of the study is to assess the possible influence of forest cover changes (under deforestation and/or afforestation) on regional weather conditions in the central part of European Russia using the results of modeling experiments provided by the meso-scale COSMO-CLM model. The need of the study lies in a lack of the experimental and modeling data characterizing the influence of the forest and land-use changes on regional weather conditions in European part of Russia. The forest ecosystems in the study region play a very important biosphere role that is significantly increased in the last decades due to considerable strengthening of anthropogenic activity in the area of European Russia. The area selected for the study is located in the central part of European Russia between 55 and 59N and 28 and 37E. It comprises several geographical zones including dark-coniferous forests of the South-European taiga in the north, the mixed forests in the central part and the broad-leaved forests in the south. The forests within the study area are very heterogeneous. The total area covered by forests according to recent remote sensing data is about 50%. The numerical experiments were provided using the COSMO-CLM model with the spatial resolution 13.2 km. As initial and boundary conditions for the numerical experiments the global reanalysis ERA Interim (with the 6-hour resolution in time and 0.75° × 0.75° in space) were used. The weather conditions were simulated in a continuous cycle for several months for the entire area of European Russia using the results of global reanalysis on external boundaries of the modeling domain. For the modeling experiments the warm period (from May to September) of 2010 was selected. The first modeling experiment assumed total deforestation of the study area. The second experiment suggested complete interruption of economic activity in the region, forest regeneration and total area afforestation. It was assumed that the forest cover increase in the considered scenario was only due to increase of the fraction of pioneer small-leaved tree species (e.g. birch, aspen). Any possible changes in proportion of coniferous species were ignored. The results of the modeling experiments showed considerable influence of forest cover changes on regional weather conditions. The influence of forest cover was manifested in changes of spatial patterns of the air temperature at different levels in the atmosphere, in changes of amount and intensity of precipitation, dew point, cloud cover, relative humidity, wind speed, and in changes of a number of other meteorological parameters. It was shown that the total deforestation of the study region can result in increase of the mean air temperature in summer on 0.3°C and in reduction of precipitation by about 6%. The afforestation processes can lead to opposite effects: in case of modeling scenario imitating the total afforestation of the study area the model predicts the decrease of the mean summer temperatures on 0.1°C and increase of precipitation by 4%. The diurnal changes of meteorological parameters can be significantly higher and more heterogeneous. Whereas the changes of the surface air temperature and humidity, wind speed and some other parameters are mainly appeared within the area with changed forest cover only, the changes of precipitation and cloud cover patterns are manifested within the entire European part of Russia including the areas situated outside the study region. The study is involved in the NEESPI program and it was supported by grant of the Russian Science Foundation (14-14- 00956).

Alpine bird distributions along elevation gradients: the consistency of climate and habitat effects across geographic regions.

PubMed

Chamberlain, Dan; Brambilla, Mattia; Caprio, Enrico; Pedrini, Paolo; Rolando, Antonio

2016-08-01

Many species have shown recent shifts in their distributions in response to climate change. Patterns in species occurrence or abundance along altitudinal gradients often serve as the basis for detecting such changes and assessing future sensitivity. Quantifying the distribution of species along altitudinal gradients acts as a fundamental basis for future studies on environmental change impacts, but in order for models of altitudinal distribution to have wide applicability, it is necessary to know the extent to which altitudinal trends in occurrence are consistent across geographically separated areas. This was assessed by fitting models of bird species occurrence across altitudinal gradients in relation to habitat and climate variables in two geographically separated alpine regions, Piedmont and Trentino. The ten species studied showed non-random altitudinal distributions which in most cases were consistent across regions in terms of pattern. Trends in relation to altitude and differences between regions could be explained mostly by habitat or a combination of habitat and climate variables. Variation partitioning showed that most variation explained by the models was attributable to habitat, or habitat and climate together, rather than climate alone or geographic region. The shape and position of the altitudinal distribution curve is important as it can be related to vulnerability where the available space is limited, i.e. where mountains are not of sufficient altitude for expansion. This study therefore suggests that incorporating habitat and climate variables should be sufficient to construct models with high transferability for many alpine species.

Regional Scale Meteorological Analysis and Prediction Using GPS Occultation and EOS Data

NASA Technical Reports Server (NTRS)

Bromwich, David H.; Shum, C. K.; Zhao, Changyin; Kuo, Bill; Rocken, Chris

2004-01-01

The main objective of the research under this award is to improve regional meteorological analysis and prediction for traditionally data limited regions, particularly over the Southern Ocean and Antarctica, using the remote sensing observations from current and upcoming GPS radio occultation missions and the EOS instrument suite. The major components of this project are: 1.Develop and improve the methods for retrieving temperature, moisture, and pressure profiles from GPS radio occultation data and EOS radiometer data. 2. Develop and improve a regional scale data assimilation system (MM5 4DVAR). 3. Perform case studies involving data analysis and numerical modeling to investigate the impact of different data for regional meteorological analysis and the importance of data assimilation for regional meteorological simulation over the Antarctic region. 4. Apply the findings and improvements from the above studies to weather forecasting experiments. 5. In the third year of the award we made significant progress toward the remaining goals of the project. The work included carefully evaluating the performance of an atmospheric mesoscale model, the Polar MM5 in Antarctic applications and improving the upper boundary condition.

Economic development, flow of funds, and the equilibrium interaction of financial frictions.

PubMed

Moll, Benjamin; Townsend, Robert M; Zhorin, Victor

2017-06-13

We use a variety of different datasets from Thailand to study not only the extremes of micro and macro variables but also within-country flow of funds and labor migration. We develop a general equilibrium model that encompasses regional variation in the type of financial friction and calibrate it to measured variation in regional aggregates. The model predicts substantial capital and labor flows from rural to urban areas even though these differ only in the underlying financial regime. Predictions for micro variables not used directly provide a model validation. Finally, we estimate the impact of a policy of counterfactual, regional isolationism.

Economic development, flow of funds, and the equilibrium interaction of financial frictions

PubMed Central

Moll, Benjamin; Townsend, Robert M.; Zhorin, Victor

2017-01-01

We use a variety of different datasets from Thailand to study not only the extremes of micro and macro variables but also within-country flow of funds and labor migration. We develop a general equilibrium model that encompasses regional variation in the type of financial friction and calibrate it to measured variation in regional aggregates. The model predicts substantial capital and labor flows from rural to urban areas even though these differ only in the underlying financial regime. Predictions for micro variables not used directly provide a model validation. Finally, we estimate the impact of a policy of counterfactual, regional isolationism. PMID:28592655

The DIVA model: A neural theory of speech acquisition and production

PubMed Central

Tourville, Jason A.; Guenther, Frank H.

2013-01-01

The DIVA model of speech production provides a computationally and neuroanatomically explicit account of the network of brain regions involved in speech acquisition and production. An overview of the model is provided along with descriptions of the computations performed in the different brain regions represented in the model. The latest version of the model, which contains a new right-lateralized feedback control map in ventral premotor cortex, will be described, and experimental results that motivated this new model component will be discussed. Application of the model to the study and treatment of communication disorders will also be briefly described. PMID:23667281

Modeling lakes and reservoirs in the climate system

USGS Publications Warehouse

MacKay, M.D.; Neale, P.J.; Arp, C.D.; De Senerpont Domis, L. N.; Fang, X.; Gal, G.; Jo, K.D.; Kirillin, G.; Lenters, J.D.; Litchman, E.; MacIntyre, S.; Marsh, P.; Melack, J.; Mooij, W.M.; Peeters, F.; Quesada, A.; Schladow, S.G.; Schmid, M.; Spence, C.; Stokes, S.L.

2009-01-01

Modeling studies examining the effect of lakes on regional and global climate, as well as studies on the influence of climate variability and change on aquatic ecosystems, are surveyed. Fully coupled atmosphere-land surface-lake climate models that could be used for both of these types of study simultaneously do not presently exist, though there are many applications that would benefit from such models. It is argued here that current understanding of physical and biogeochemical processes in freshwater systems is sufficient to begin to construct such models, and a path forward is proposed. The largest impediment to fully representing lakes in the climate system lies in the handling of lakes that are too small to be explicitly resolved by the climate model, and that make up the majority of the lake-covered area at the resolutions currently used by global and regional climate models. Ongoing development within the hydrological sciences community and continual improvements in model resolution should help ameliorate this issue.

Regional frequency analysis of extreme rainfall for the Baltimore Metropolitan region based on stochastic storm transposition

NASA Astrophysics Data System (ADS)

Zhou, Z.; Smith, J. A.; Yang, L.; Baeck, M. L.; Wright, D.; Liu, S.

2017-12-01

Regional frequency analyses of extreme rainfall are critical for development of engineering hydrometeorology procedures. In conventional approaches, the assumptions that `design storms' have specified time profiles and are uniform in space are commonly applied but often not appropriate, especially over regions with heterogeneous environments (due to topography, water-land boundaries and land surface properties). In this study, we present regional frequency analyses of extreme rainfall for Baltimore study region combining storm catalogs of rainfall fields derived from weather radar and stochastic storm transposition (SST, developed by Wright et al., 2013). The study region is Dead Run, a small (14.3 km2) urban watershed, in the Baltimore Metropolitan region. Our analyses build on previous empirical and modeling studies showing pronounced spatial heterogeneities in rainfall due to the complex terrain, including the Chesapeake Bay to the east, mountainous terrain to the west and urbanization in this region. We expand the original SST approach by applying a multiplier field that accounts for spatial heterogeneities in extreme rainfall. We also characterize the spatial heterogeneities of extreme rainfall distribution through analyses of rainfall fields in the storm catalogs. We examine the characteristics of regional extreme rainfall and derive intensity-duration-frequency (IDF) curves using the SST approach for heterogeneous regions. Our results highlight the significant heterogeneity of extreme rainfall in this region. Estimates of IDF show the advantages of SST in capturing the space-time structure of extreme rainfall. We also illustrate application of SST analyses for flood frequency analyses using a distributed hydrological model. Reference: Wright, D. B., J. A. Smith, G. Villarini, and M. L. Baeck (2013), Estimating the frequency of extreme rainfall using weather radar and stochastic storm transposition, J. Hydrol., 488, 150-165.

Assessing the contribution of different factors in RegCM4.3 regional climate model projections using the Factor Separation method over the Med-CORDEX domain

NASA Astrophysics Data System (ADS)

Zsolt Torma, Csaba; Giorgi, Filippo

2014-05-01

A set of regional climate model (RCM) simulations applying dynamical downscaling of global climate model (GCM) simulations over the Mediterranean domain specified by the international initiative Coordinated Regional Downscaling Experiment (CORDEX) were completed with the Regional Climate Model RegCM, version RegCM4.3. Two GCMs were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields for the RegCM: HadGEM2-ES (HadGEM) and MPI-ESM-MR (MPI). The simulations consist of an ensemble including multiple physics configurations and different "Reference Concentration Pathways" (RCP4.5 and RCP8.5). In total 15 simulations were carried out with 7 model physics configurations with varying convection and land surface schemes. The horizontal grid spacing of the RCM simulations is 50 km and the simulated period in all cases is 1970-2100 (1970-2099 in case of HadGEM driven simulations). This ensemble includes a combination of experiments in which different model components are changed individually and in combination, and thus lends itself optimally to the application of the Factor Separation (FS) method. This study applies the FS method to investigate the contributions of different factors, along with their synergy, on a set of regional climate model (RCM) projections for the Mediterranean region. The FS method is applied to 6 projections for the period 1970-2100 performed with the regional model RegCM4.3 over the Med-CORDEX domain. Two different sets of factors are intercompared, namely the driving global climate model (HadGEM and MPI) boundary conditions against two model physics settings (convection scheme and irrigation). We find that both the GCM driving conditions and the model physics provide important contributions, depending on the variable analyzed (surface air temperature and precipitation), season (winter vs. summer) and time horizon into the future, while the synergy term mostly tends to counterbalance the contributions of the individual factors. We demonstrate the usefulness of the FS method to assess different sources of uncertainty in RCM-based regional climate projections.

The assumption of equilibrium in models of migration.

PubMed

Schachter, J; Althaus, P G

1993-02-01

In recent articles Evans (1990) and Harrigan and McGregor (1993) (hereafter HM) scrutinized the equilibrium model of migration presented in a 1989 paper by Schachter and Althaus. This model used standard microeconomics to analyze gross interregional migration flows based on the assumption that gross flows are in approximate equilibrium. HM criticized the model as theoretically untenable, while Evans summoned empirical as well as theoretical objections. HM claimed that equilibrium of gross migration flows could be ruled out on theoretical grounds. They argued that the absence of net migration requires that either all regions have equal populations or that unsustainable regional migration propensities must obtain. In fact some moves are inter- and other are intraregional. It does not follow, however, that the number of interregional migrants will be larger for the more populous region. Alternatively, a country could be divided into a large number of small regions that have equal populations. With uniform propensities to move, each of these analytical regions would experience in equilibrium zero net migration. Hence, the condition that net migration equal zero is entirely consistent with unequal distributions of population across regions. The criticisms of Evans were based both on flawed reasoning and on misinterpretation of the results of a number of econometric studies. His reasoning assumed that the existence of demand shifts as found by Goldfarb and Yezer (1987) and Topel (1986) invalidated the equilibrium model. The equilibrium never really obtains exactly, but economic modeling of migration properly begins with a simple equilibrium model of the system. A careful reading of the papers Evans cited in support of his position showed that in fact they affirmed rather than denied the appropriateness of equilibrium modeling. Zero net migration together with nonzero gross migration are not theoretically incompatible with regional heterogeneity of population, wages, or amenities.

Sources of Sahelian-Sudan moisture: Insights from a moisture-tracing atmospheric model

NASA Astrophysics Data System (ADS)

Salih, Abubakr A. M.; Zhang, Qiong; Pausata, Francesco S. R.; Tjernström, Michael

2016-07-01

The summer rainfall across Sahelian-Sudan is one of the main sources of water for agriculture, human, and animal needs. However, the rainfall is characterized by large interannual variability, which has attracted extensive scientific efforts to understand it. This study attempts to identify the source regions that contribute to the Sahelian-Sudan moisture budget during July through September. We have used an atmospheric general circulation model with an embedded moisture-tracing module (Community Atmosphere Model version 3), forced by observed (1979-2013) sea-surface temperatures. The result suggests that about 40% of the moisture comes with the moisture flow associated with the seasonal migration of the Intertropical Convergence Zone (ITCZ) and originates from Guinea Coast, central Africa, and the Western Sahel. The Mediterranean Sea, Arabian Peninsula, and South Indian Ocean regions account for 10.2%, 8.1%, and 6.4%, respectively. Local evaporation and the rest of the globe supply the region with 20.3% and 13.2%, respectively. We also compared the result from this study to a previous analysis that used the Lagrangian model FLEXPART forced by ERA-Interim. The two approaches differ when comparing individual regions, but are in better agreement when neighboring regions of similar atmospheric flow features are grouped together. Interannual variability with the rainfall over the region is highly correlated with contributions from regions that are associated with the ITCZ movement, which is in turn linked to the Atlantic Multidecadal Oscillation. Our result is expected to provide insights for the effort on seasonal forecasting of the rainy season over Sahelian Sudan.

Impacts of regional land-grab on regional hydroclimate in southeastern Africa via modeling and remote sensing

NASA Astrophysics Data System (ADS)

Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

2017-12-01

Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are significant enough to induce changes in the evolution of the planetary boundary layer and its interaction with the atmosphere above. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models or Earth System Models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from timber harvesting due to a land grab boom in Mozambique. We also focus more narrowly at quantifying regional impacts on Gorongosa National Park, a nationally important economic and biodiversity resource in southeastern Africa. After nationalizing all land in 1975 after Mozambique gained independence, complex social processes, including an extended low intensity conflict civil war and economic hardships, led to an escalation of land use rights grants to foreign governments. Between 2004 and 2009, large tracts of land were requested for timber. Here we use existing tree cover loss datasets to more accurately represent land cover within a regional weather model. LULC in a region encompassing Gorongosa is updated at three instances between 2001 and 2014 using a tree cover loss dataset. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the land grab. Results suggest that the land grab has impacted microclimate parameters in a significant way via direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional social dynamics are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

Some comments on the World Energy Conference (WEC) energy demand model

NASA Astrophysics Data System (ADS)

Brandell, L.

1982-04-01

The WEC model, relating the energy demand for a region in a year to gross national product (GNP), aggregated energy prices and elasticity constants, is generalized. The changes that result from the assumption that the elasticity factors are not constant are examined. The resulting differential equation contains the variables energy demand per capita and GNP per capita for the region considered. The effect of time lag in energy demand and the influence of the population growth rate are also included in the model. No projections of the future energy demand were made, but model sensitiveness to the modifications were studied. Time lag effects and population growth effects can raise the projected energy demand for a region by 10% or more.

Noah-MP-Crop: Enhancing cropland representation in the community land surface modeling system

NASA Astrophysics Data System (ADS)

Liu, X.; Chen, F.; Barlage, M. J.; Zhou, G.; Niyogi, D.

2015-12-01

Croplands are important in land-atmosphere interactions and in modifying local and regional weather and climate. Despite their importance, croplands are poorly represented in the current version of the coupled Weather Research and Forecasting (WRF)/ Noah land-surface modeling system, resulting in significant surface temperature and humidity biases across agriculture- dominated regions of the United States. This study aims to improve the WRF weather forecasting and regional climate simulations during the crop growing season by enhancing the representation of cropland in the Noah-MP land model. We introduced dynamic crop growth parameterization into Noah-MP and evaluated the enhanced model (Noah-MP-Crop) at both the field and regional scales with multiple crop biomass datasets, surface fluxes and soil moisture/temperature observations. We also integrated a detailed cropland cover map into WRF, enabling the model to simulate corn and soybean field across the U.S. Great Plains. Results show marked improvement in the Noah-MP-Crop performance in simulating leaf area index (LAI), crop biomass, soil temperature, and surface fluxes. Enhanced cropland representation is not only crucial for improving weather forecasting but can also help assess potential impacts of weather variability on regional hydrometeorology and crop yields. In addition to its applications to WRF, Noah-MP-Crop can be applied in high-spatial-resolution regional crop yield modeling and drought assessments

Interactive coupling of regional climate and sulfate aerosol models over eastern Asia

NASA Astrophysics Data System (ADS)

Qian, Yun; Giorgi, Filippo

1999-03-01

The NCAR regional climate model (RegCM) is interactively coupled to a simple radiatively active sulfate aerosol model over eastern Asia. Both direct and indirect aerosol effects are represented. The coupled model system is tested for two simulation periods, November 1994 and July 1995, with aerosol sources representative of present-day anthropogenic sulfur emissions. The model sensitivity to the intensity of the aerosol source is also studied. The main conclusions from our work are as follows: (1) The aerosol distribution and cycling processes show substantial regional spatial variability, and temporal variability varying on a range of scales, from the diurnal scale of boundary layer and cumulus cloud evolution to the 3-10 day scale of synoptic scale events and the interseasonal scale of general circulation features; (2) both direct and indirect aerosol forcings have regional effects on surface climate; (3) the regional climate response to the aerosol forcing is highly nonlinear, especially during the summer, due to the interactions with cloud and precipitation processes; (4) in our simulations the role of the aerosol indirect effects is dominant over that of direct effects; (5) aerosol-induced feedback processes can affect the aerosol burdens at the subregional scale. This work constitutes the first step in a long term research project aimed at coupling a hierarchy of chemistry/aerosol models to the RegCM over the eastern Asia region.

Evidence for an anterior-posterior differentiation in the human hippocampal formation revealed by meta-analytic parcellation of fMRI coordinate maps: focus on the subiculum.

PubMed

Chase, Henry W; Clos, Mareike; Dibble, Sofia; Fox, Peter; Grace, Anthony A; Phillips, Mary L; Eickhoff, Simon B

2015-06-01

Previous studies, predominantly in experimental animals, have suggested the presence of a differentiation of function across the hippocampal formation. In rodents, ventral regions are thought to be involved in emotional behavior while dorsal regions mediate cognitive or spatial processes. Using a combination of modeling the co-occurrence of significant activations across thousands of neuroimaging experiments and subsequent data-driven clustering of these data we were able to provide evidence of distinct subregions within a region corresponding to the human subiculum, a critical hub within the hippocampal formation. This connectivity-based model consists of a bilateral anterior region, as well as separate posterior and intermediate regions on each hemisphere. Functional connectivity assessed both by meta-analytic and resting fMRI approaches revealed that more anterior regions were more strongly connected to the default mode network, and more posterior regions were more strongly connected to 'task positive' regions. In addition, our analysis revealed that the anterior subregion was functionally connected to the ventral striatum, midbrain and amygdala, a circuit that is central to models of stress and motivated behavior. Analysis of a behavioral taxonomy provided evidence for a role for each subregion in mnemonic processing, as well as implication of the anterior subregion in emotional and visual processing and the right posterior subregion in reward processing. These findings lend support to models which posit anterior-posterior differentiation of function within the human hippocampal formation and complement other early steps toward a comparative (cross-species) model of the region. Copyright © 2015 Elsevier Inc. All rights reserved.

Effects of Inventory Bias on Landslide Susceptibility Calculations

NASA Technical Reports Server (NTRS)

Stanley, T. A.; Kirschbaum, D. B.

2017-01-01

Many landslide inventories are known to be biased, especially inventories for large regions such as Oregon's SLIDO or NASA's Global Landslide Catalog. These biases must affect the results of empirically derived susceptibility models to some degree. We evaluated the strength of the susceptibility model distortion from postulated biases by truncating an unbiased inventory. We generated a synthetic inventory from an existing landslide susceptibility map of Oregon, then removed landslides from this inventory to simulate the effects of reporting biases likely to affect inventories in this region, namely population and infrastructure effects. Logistic regression models were fitted to the modified inventories. Then the process of biasing a susceptibility model was repeated with SLIDO data. We evaluated each susceptibility model with qualitative and quantitative methods. Results suggest that the effects of landslide inventory bias on empirical models should not be ignored, even if those models are, in some cases, useful. We suggest fitting models in well-documented areas and extrapolating across the study region as a possible approach to modeling landslide susceptibility with heavily biased inventories.

Effects of Inventory Bias on Landslide Susceptibility Calculations

NASA Technical Reports Server (NTRS)

Stanley, Thomas; Kirschbaum, Dalia B.

2017-01-01

Many landslide inventories are known to be biased, especially inventories for large regions such as Oregons SLIDO or NASAs Global Landslide Catalog. These biases must affect the results of empirically derived susceptibility models to some degree. We evaluated the strength of the susceptibility model distortion from postulated biases by truncating an unbiased inventory. We generated a synthetic inventory from an existing landslide susceptibility map of Oregon, then removed landslides from this inventory to simulate the effects of reporting biases likely to affect inventories in this region, namely population and infrastructure effects. Logistic regression models were fitted to the modified inventories. Then the process of biasing a susceptibility model was repeated with SLIDO data. We evaluated each susceptibility model with qualitative and quantitative methods. Results suggest that the effects of landslide inventory bias on empirical models should not be ignored, even if those models are, in some cases, useful. We suggest fitting models in well-documented areas and extrapolating across the study region as a possible approach to modelling landslide susceptibility with heavily biased inventories.

Development of Groundwater Management Model for Sustainable Groundwater Use in the Agricultural Region

NASA Astrophysics Data System (ADS)

Park, D.; Bae, G.; Lee, K.

2010-12-01

In many agricultural regions, high dependence of irrigation on groundwater has brought about serious concerns about unplanned groundwater developments and over-pumping. Various agricultural activities including fertilization and livestock husbandry usually result in groundwater contamination in those regions. Field works in Icheon, Korea showed that in this region the rice farming still requires a significant amount of water and continuous construction of greenhouse can make the contamination from the fertilization more serious. In this study, a groundwater management model based on the simulation-optimization methodology is developed to achieve sufficient groundwater supply and groundwater quality conservation together on regional-scale. This model can obtain the on-ground contaminant loading mass by integrating an analytical model for 1-D solute transport in unsaturated zone with 3-D groundwater flow and solute transport model, HydroGeosphere. The outputs of the 1-D unsaturated transport model, concentrations of the contaminant leaching on water table, work as contaminant sources in the 3-D solute transport model in saturated zone. This integrated simulation model is linked to genetic algorithm that searches the global optimum for the sustainable groundwater use. And, in order for the design on the contaminant sources to be more effective, it also links the backward transport model useful for evaluating the contamination from contaminant sources to each pumping well. The first objective of the management in this study is to obtain the optimal pumping rates that not only can supply sufficient amount of the groundwater but protect the groundwater from the excessive drawdown and contamination. The second objective is to control the periodic loading of the contaminant by suggesting the allowable contaminant loading mass. For this multi-objective groundwater management, the objective function to maximize both pumping rates and allowable contaminant loading mass and at the same time to satisfy the constraints for contaminant concentration and drawdown are assigned in the optimization model. The proposed methodology can be useful to provide the groundwater management options for sustainable groundwater use in the agricultural regions.

Dynamical Downscaling of Seasonal Climate Prediction over Nordeste Brazil with ECHAM3 and NCEP's Regional Spectral Models at IRI.

NASA Astrophysics Data System (ADS)

Nobre, Paulo; Moura, Antonio D.; Sun, Liqiang

2001-12-01

This study presents an evaluation of a seasonal climate forecast done with the International Research Institute for Climate Prediction (IRI) dynamical forecast system (regional model nested into a general circulation model) over northern South America for January-April 1999, encompassing the rainy season over Brazil's Nordeste. The one-way nesting is one in two tiers: first the NCEP's Regional Spectral Model (RSM) runs with an 80-km grid mesh forced by the ECHAM3 atmospheric general circulation model (AGCM) outputs; then the RSM runs with a finer grid mesh (20 km) forced by the forecasts generated by the RSM-80. An ensemble of three realizations is done. Lower boundary conditions over the oceans for both ECHAM and RSM model runs are sea surface temperature forecasts over the tropical oceans. Soil moisture is initialized by ECHAM's inputs. The rainfall forecasts generated by the regional model are compared with those of the AGCM and observations. It is shown that the regional model at 80-km resolution improves upon the AGCM rainfall forecast, reducing both seasonal bias and root-mean-square error. On the other hand, the RSM-20 forecasts presented larger errors, with spatial patterns that resemble those of local topography. The better forecast of the position and width of the intertropical convergence zone (ITCZ) over the tropical Atlantic by the RSM-80 model is one of the principal reasons for better-forecast scores of the RSM-80 relative to the AGCM. The regional model improved the spatial as well as the temporal details of rainfall distribution, and also presenting the minimum spread among the ensemble members. The statistics of synoptic-scale weather variability on seasonal timescales were best forecast with the regional 80-km model over the Nordeste. The possibility of forecasting the frequency distribution of dry and wet spells within the rainy season is encouraging.

A computer simulation model to compute the radiation transfer of mountainous regions

NASA Astrophysics Data System (ADS)

Li, Yuguang; Zhao, Feng; Song, Rui

2011-11-01

In mountainous regions, the radiometric signal recorded at the sensor depends on a number of factors such as sun angle, atmospheric conditions, surface cover type, and topography. In this paper, a computer simulation model of radiation transfer is designed and evaluated. This model implements the Monte Carlo ray-tracing techniques and is specifically dedicated to the study of light propagation in mountainous regions. The radiative processes between sun light and the objects within the mountainous region are realized by using forward Monte Carlo ray-tracing methods. The performance of the model is evaluated through detailed comparisons with the well-established 3D computer simulation model: RGM (Radiosity-Graphics combined Model) based on the same scenes and identical spectral parameters, which shows good agreements between these two models' results. By using the newly developed computer model, series of typical mountainous scenes are generated to analyze the physical mechanism of mountainous radiation transfer. The results show that the effects of the adjacent slopes are important for deep valleys and they particularly affect shadowed pixels, and the topographic effect needs to be considered in mountainous terrain before accurate inferences from remotely sensed data can be made.

A method for physically based model analysis of conjunctive use in response to potential climate changes

USGS Publications Warehouse

Hanson, R.T.; Flint, L.E.; Flint, A.L.; Dettinger, M.D.; Faunt, C.C.; Cayan, D.; Schmid, W.

2012-01-01

Potential climate change effects on aspects of conjunctive management of water resources can be evaluated by linking climate models with fully integrated groundwater-surface water models. The objective of this study is to develop a modeling system that links global climate models with regional hydrologic models, using the California Central Valley as a case study. The new method is a supply and demand modeling framework that can be used to simulate and analyze potential climate change and conjunctive use. Supply-constrained and demand-driven linkages in the water system in the Central Valley are represented with the linked climate models, precipitation-runoff models, agricultural and native vegetation water use, and hydrologic flow models to demonstrate the feasibility of this method. Simulated precipitation and temperature were used from the GFDL-A2 climate change scenario through the 21st century to drive a regional water balance mountain hydrologic watershed model (MHWM) for the surrounding watersheds in combination with a regional integrated hydrologic model of the Central Valley (CVHM). Application of this method demonstrates the potential transition from predominantly surface water to groundwater supply for agriculture with secondary effects that may limit this transition of conjunctive use. The particular scenario considered includes intermittent climatic droughts in the first half of the 21st century followed by severe persistent droughts in the second half of the 21st century. These climatic droughts do not yield a valley-wide operational drought but do cause reduced surface water deliveries and increased groundwater abstractions that may cause additional land subsidence, reduced water for riparian habitat, or changes in flows at the Sacramento-San Joaquin River Delta. The method developed here can be used to explore conjunctive use adaptation options and hydrologic risk assessments in regional hydrologic systems throughout the world.

Can We Use Tree Rings of Black Alder to Reconstruct Lake Levels? A Case Study for the Mecklenburg Lake District, Northeastern Germany

PubMed Central

van der Maaten, Ernst; van der Maaten-Theunissen, Marieke; Buras, Allan; Scharnweber, Tobias; Simard, Sonia; Kaiser, Knut; Lorenz, Sebastian; Wilmking, Martin

2015-01-01

In this study, we explore the potential to reconstruct lake-level (and groundwater) fluctuations from tree-ring chronologies of black alder (Alnus glutinosa L.) for three study lakes in the Mecklenburg Lake District, northeastern Germany. As gauging records for lakes in this region are generally short, long-term reconstructions of lake-level fluctuations could provide valuable information on past hydrological conditions, which, in turn, are useful to assess dynamics of climate and landscape evolution. We selected black alder as our study species as alder typically thrives as riparian vegetation along lakeshores. For the study lakes, we tested whether a regional signal in lake-level fluctuations and in the growth of alder exists that could be used for long-term regional hydrological reconstructions, but found that local (i.e. site-specific) signals in lake level and tree-ring chronologies prevailed. Hence, we built lake/groundwater-level reconstruction models for the three study lakes individually. Two sets of models were considered based on (1) local tree-ring series of black alder, and (2) site-specific Standardized Precipitation Evapotranspiration Indices (SPEI). Although the SPEI-based models performed statistically well, we critically reflect on the reliability of these reconstructions, as SPEI cannot account for human influence. Tree-ring based reconstruction models, on the other hand, performed poor. Combined, our results suggest that, for our study area, long-term regional reconstructions of lake-level fluctuations that consider both recent and ancient (e.g., archaeological) wood of black alder seem extremely challenging, if not impossible. PMID:26317768

Air Quality Modeling for the Urban Jackson, Mississippi Region Using a High Resolution WRF/Chem Model

PubMed Central

Yerramilli, Anjaneyulu; Dodla, Venkata B.; Desamsetti, Srinivas; Challa, Srinivas V.; Young, John H.; Patrick, Chuck; Baham, Julius M.; Hughes, Robert L.; Yerramilli, Sudha; Tuluri, Francis; Hardy, Mark G.; Swanier, Shelton J.

2011-01-01

In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi) region using an online WRF/Chem (Weather Research and Forecasting–Chemistry) model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators. PMID:21776240

Source tagging modeling study of regional contributions to acid rain in summer over Liaoning Province, Northeastern China.

PubMed

Gbaguidi, Alex E; Wang, Zifa; Wang, Wei; Yang, Ting; Chen, Huan-Sheng

2018-04-01

Strong acid rain was recently observed over Northeastern China, particularly in summer in Liaoning Province where alkaline dust largely neutralized acids in the past. This seems to be related to the regional transboundary pollution and poses new challenges in acid rain control scheme in China. In order to delve into the regional transport impact, and quantify its potential contributions to such an "eruption" of acid rain over Liaoning, this paper employs an online source tagging model in coupling with the Nested Air Quality Prediction Modeling System (NAQPMS). Validation of predictions shows the model capability in reproducing key meteorological and chemical features. Acid concentration over Liaoning is more pronounced in August (average of 0.087 mg/m 3 ) with strong pollutant import from regional sources against significant depletion of basic species. Seasonal mean contributions from regional sources are assessed at both lower and upper boundary layers to elucidate the main pathways of the impact of regional sources on acid concentration over Liaoning. At the upper layer (1.2 km), regional sources contribute to acid concentration over Liaoning by 67%, mainly from Shandong (16%), Hebei (13%), Tianjin (11%) and Korean Peninsula (9%). Identified main city-receptors in Liaoning are Dandong, Dalian, Chaohu, Yingkou, Liaoyang, Jinfu, Shengyang, Panjin, Tieling, Benxi, Anshan and Fushun. At lower layer (120 m) where Liaoning local contribution is dominant (58%), regional sources account for 39% in acid concentration. However, inter-municipal acid exchanges are prominent at this layer and many cities in Liaoning are revealed as important sources of local acid production. Seasonal acid contribution average within 1.2 km-120 m attains 55%, suggesting dominance of vertical pollutant transport from regional sources towards lower boundary layer in Liaoning. As direct environmental implication, this study provides policy makers with a perspective of regulating the regional transboundary environmental impact assessment in China with application to acid rain control. Copyright © 2018 Elsevier Ltd. All rights reserved.

Thermal and albedo mapping of the north and south polar regions of Mars

NASA Technical Reports Server (NTRS)

Paige, D. A.; Keegan, K. D.

1991-01-01

The first maps are presented of the north and south polar regions of Mars. The thermal properties of the midlatitude regions from -60 deg to +60 deg latitude were mapped in previous studies. The presented maps complete the mapping of entire planet. The maps for the north and south polar regions were derived from Viking Infrared Thermal Mapper (IRTM) observations. Best fit thermal inertias were determined by comparing the available IRTM 20 micron channel brightness within a given region to surface temperatures computed by a diurnal and seasonal thermal model. The model assumes no atmospheric contributions to the surface heat balance. The resulting maps of apparent thermal inertia and average IRTM measured solar channel lambert albedo for the north and south polar regions from the poles to +/- 60 deg latitude.

Study on the total amount control of atmospheric pollutant based on GIS.

PubMed

Wang, Jian-Ping; Guo, Xi-Kun

2005-08-01

To provide effective environmental management for total amount control of atmospheric pollutants. An atmospheric diffusion model of sulfur dioxide on the surface of the earth was established and tested in Shantou of Guangdong Province on the basis of an overall assessment of regional natural environment, social economic state of development, pollution sources and atmospheric environmental quality. Compared with actual monitoring results in a studied region, simulation values fell within the range of two times of error and were evenly distributed in the two sides of the monitored values. Predicted with the largest emission model method, the largest emission of sulfur dioxide would be 54,279.792 tons per year in 2010. The mathematical model established and revised on the basis of GIS is more rational and suitable for the regional characteristics of total amount control of air pollutants.

A 3-D Model Study of Aerosol Composition and Radiative Forcing in the Asian-Pacific Region

NASA Technical Reports Server (NTRS)

Chin, Mian; Ginoux, Paul; Torres, Omar; Zhao, Xuepeng; Einaudi, Franco (Technical Monitor)

2000-01-01

The Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model will be used in analyzing the aerosol data in the ACE-Asia program. Our objectives are (1) to understand the physical, chemical, and optical properties of aerosol and the processes that control these properties over the Asian-Pacific region, (2) to determine the aerosol radiative forcing over the Asian-Pacific region, and (3) to investigate the interaction between aerosol and tropospheric chemistry. We will present the GOCART aerosol simulations of sulfate, dust, carbonaceous, and sea salt concentrations, their optical thicknesses, and their radiative effects. We will also show the comparisons of model results with data taken from previous field campaigns, ground-based sun photometer measurements, and satellite observations. Finally, we will present our plan for the ACE-Asia study.

Modeling preferential water flow and solute transport in unsaturated soil using the active region model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheng, F.; Wang, K.; Zhang, R.

2009-03-15

Preferential flow and solute transport are common processes in the unsaturated soil, in which distributions of soil water content and solute concentrations are often characterized as fractal patterns. An active region model (ARM) was recently proposed to describe the preferential flow and transport patterns. In this study, ARM governing equations were derived to model the preferential soil water flow and solute transport processes. To evaluate the ARM equations, dye infiltration experiments were conducted, in which distributions of soil water content and Cl{sup -} concentration were measured. Predicted results using the ARM and the mobile-immobile region model (MIM) were compared withmore » the measured distributions of soil water content and Cl{sup -} concentration. Although both the ARM and the MIM are two-region models, they are fundamental different in terms of treatments of the flow region. The models were evaluated based on the modeling efficiency (ME). The MIM provided relatively poor prediction results of the preferential flow and transport with negative ME values or positive ME values less than 0.4. On the contrary, predicted distributions of soil water content and Cl- concentration using the ARM agreed reasonably well with the experimental data with ME values higher than 0.8. The results indicated that the ARM successfully captured the macroscopic behavior of preferential flow and solute transport in the unsaturated soil.« less

Influence of boundary conditions to multi-model simulations of ozone and PM2.5 levels over Europe and North America in frame of AQMEII3

NASA Astrophysics Data System (ADS)

Im, Ulas; Hansen, Kaj M.; Geels, Camilla; Christensen, Jesper H.; Brandt, Jørgen; Hogrefe, Christian; Galmarini, Stefano

2016-04-01

AQMEII (Air Quality Model Evaluation International Initiative) promotes research on regional air quality model evaluation across the European and North American atmospheric modelling communities, providing the ideal platform for advancing the evaluation of air quality models at the regional scale. In frame of the AQMEII3 model evaluation exercise, thirteen regional chemistry and transport models have simulated the air pollutant levels over Europe and/or North America for the year 2010, along with various sensitivity simulations of reductions in anthropogenic emissions and boundary conditions. All participating groups have performed sensitivity simulation with 20% reductions in global (GLO) anthropogenic emissions. In addition, various groups simulated sensitivity scenarios of 20% reductions in anthropogenic emissions in different HTAP-defined regions such as North America (NAM), Europe (EUR) and East Asia (EAS). The boundary conditions for the base case and the perturbation scenarios were derived from the MOZART-IFS global chemical model. The present study will evaluate the impact of these emission perturbations on regional surface ozone and PM2.5 levels as well as over individual surface measurement stations over both continents and vertical profiles over the radiosonde stations from the World Ozone and Ultraviolet Radiation Data Centre (WOUDC) and the Aerosol Robotic Network (AERONET) stations for ozone and for PM2.5, respectively.

Peri-implant bone density in senile osteoporosis-changes from implant placement to osseointegration.

PubMed

Beppu, Kensuke; Kido, Hirofumi; Watazu, Akira; Teraoka, Kay; Matsuura, Masaro

2013-04-01

The aim of this study was to examine healing over time after implant body placement in a senile osteoporosis model and a control group. In this study, 16-week-old male mice were used. The senile osteoporosis model consisted of senescence-accelerated prone 6 mice and the control group consisted of senescence-accelerated resistant 1 mice. Titanium-coated plastic implants were used as experimental implants whose dimensions were 3.0 mm in length, 1.1 mm in apical diameter, and 1.2 mm in coronal diameter. Bone samples were collected at 5, 7, 14, 21, and 28 days after implant placement. A micro-quantitative computed tomography (QCT) system was used to scan these samples and a phantom in order to quantitate bone mineral measurements. Bone mineral density (BMD) of each sample was measured. Each sample was also examined by light microscopy after QCT imaging. At 14 and 28 days after implant placement, the bone-implant contact (BIC) ratios were calculated from light microscopy images and were divided into cortical bone and bone marrow regions. When BMD was compared between the osteoporosis and control groups using micro-QCT, the osteoporosis group had a significantly lower BMD in the region 0-20 µm from the implant surface in the bone marrow region at 14 days onward after implant placement. Compared with the control group, the osteoporosis model also had significantly lower BMD in all regions 0-100 µm from the implant surface in the bone marrow region at 14 days after placement. However, in the cortical bone region, no statistically significant difference was observed in the regions at the bone-implant interface. Light microscopy revealed osseointegration for all implants 28 days after implant placement. The osteoporosis model tended to have lower BICs compared with that of the control group, although this did not reach statistical significance. Our results showed that osseointegration was achieved in the osteoporosis model. However, the BMD was 30-40% lower than that of the control group in the region closest to the implant surface in bone marrow region. Peri-implant BMD was lower in a relatively large area in the osteoporosis model during an important time for osseointegration. Therefore, this result suggests that osteoporosis might be considered as a risk factor in implant therapy. The osteoporosis model had a lower BMD than the control group in the region closest to the implant during an important time for osseointegration. This result suggests that senile osteoporosis might be a risk factor in implant therapy. However, the osteoporosis model and the control group had no difference in peri-implant BMD in the cortical bone region. This suggests that risk might be avoided by implant placement that effectively uses the cortical bone. © 2011 Wiley Periodicals, Inc.

Validation of newly designed regional earth system model (RegESM) for Mediterranean Basin

NASA Astrophysics Data System (ADS)

Turuncoglu, Ufuk Utku; Sannino, Gianmaria

2017-05-01

We present a validation analysis of a regional earth system model system (RegESM) for the Mediterranean Basin. The used configuration of the modeling system includes two active components: a regional climate model (RegCM4) and an ocean modeling system (ROMS). To assess the performance of the coupled modeling system in representing the climate of the basin, the results of the coupled simulation (C50E) are compared to the results obtained by a standalone atmospheric simulation (R50E) as well as several observation datasets. Although there is persistent cold bias in fall and winter, which is also seen in previous studies, the model reproduces the inter-annual variability and the seasonal cycles of sea surface temperature (SST) in a general good agreement with the available observations. The analysis of the near-surface wind distribution and the main circulation of the sea indicates that the coupled model can reproduce the main characteristics of the Mediterranean Sea surface and intermediate layer circulation as well as the seasonal variability of wind speed and direction when it is compared with the available observational datasets. The results also reveal that the simulated near-surface wind speed and direction have poor performance in the Gulf of Lion and surrounding regions that also affects the large positive SST bias in the region due to the insufficient horizontal resolution of the atmospheric component of the coupled modeling system. The simulated seasonal climatologies of the surface heat flux components are also consistent with the CORE.2 and NOCS datasets along with the overestimation in net long-wave radiation and latent heat flux (or evaporation, E), although a large observational uncertainty is found in these variables. Also, the coupled model tends to improve the latent heat flux by providing a better representation of the air-sea interaction as well as total heat flux budget over the sea. Both models are also able to reproduce the temporal evolution of the inter-annual anomaly of surface air temperature and precipitation (P) over defined sub-regions. The Mediterranean water budget (E, P and E-P) estimates also show that the coupled model has high skill in the representation of water budget of the Mediterranean Sea. To conclude, the coupled model reproduces climatological land surface fields and the sea surface variables in the range of observation uncertainty and allow studying air-sea interaction and main regional climate characteristics of the basin.

Influence of land use and climate on wetland breeding birds in the Prairie Pothole region of Canada

USGS Publications Warehouse

Forcey, G.M.; Linz, G.M.; Thogmartin, W.E.; Bleier, W.J.

2007-01-01

Bird populations are influenced by a variety of factors at both small and large scales that range from the presence of suitable nesting habitat, predators, and food supplies to climate conditions and land-use patterns. We evaluated the influences of regional climate and land-use variables on wetland breeding birds in the Canada section of Bird Conservation Region 11 (CA-BCR11), the Prairie Potholes. We used bird abundance data from the North American Breeding Bird Survey, land-use data from the Prairie Farm Rehabilitation Administration, and weather data from the National Climatic Data and Information Archive to model effects of regional environmental variables on bird abundance. Models were constructed a priori using information from published habitat associations in the literature, and fitting was performed with WinBUGS using Markov chain Monte Carlo techniques. Both land-use and climate variables contributed to predicting bird abundance in CA-BCR11, although climate predictors contributed the most to improving model fit. Examination of regional effects of climate and land use on wetland birds in CA-BCR11 revealed relationships with environmental covariates that are often overlooked by small-scale habitat studies. Results from these studies can be used to improve conservation and management planning for regional populations of avifauna. ?? 2007 NRC.

A Probabilistic Tsunami Hazard Study of the Auckland Region, Part I: Propagation Modelling and Tsunami Hazard Assessment at the Shoreline

NASA Astrophysics Data System (ADS)

Power, William; Wang, Xiaoming; Lane, Emily; Gillibrand, Philip

2013-09-01

Regional source tsunamis represent a potentially devastating threat to coastal communities in New Zealand, yet are infrequent events for which little historical information is available. It is therefore essential to develop robust methods for quantitatively estimating the hazards posed, so that effective mitigation measures can be implemented. We develop a probabilistic model for the tsunami hazard posed to the Auckland region of New Zealand from the Kermadec Trench and the southern New Hebrides Trench subduction zones. An innovative feature of our model is the systematic analysis of uncertainty regarding the magnitude-frequency distribution of earthquakes in the source regions. The methodology is first used to estimate the tsunami hazard at the coastline, and then used to produce a set of scenarios that can be applied to produce probabilistic maps of tsunami inundation for the study region; the production of these maps is described in part II. We find that the 2,500 year return period regional source tsunami hazard for the densely populated east coast of Auckland is dominated by events originating in the Kermadec Trench, while the equivalent hazard to the sparsely populated west coast is approximately equally due to events on the Kermadec Trench and the southern New Hebrides Trench.

Coupled Regional Ocean-Atmosphere Modeling of the Mount Pinatubo Impact on the Red Sea

NASA Astrophysics Data System (ADS)

Stenchikov, G. L.; Osipov, S.

2017-12-01

The 1991 eruption of Mount Pinatubo had dramatic effects on the regional climate in the Middle East. Though acknowledged, these effects have not been thoroughly studied. To fill this gap and to advance understanding of the mechanisms that control variability in the Middle East's regional climate, we simulated the impact of the 1991 Pinatubo eruption using a regional coupled ocean-atmosphere modeling system set for the Middle East and North Africa (MENA) domain. We used the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) framework, which couples the Weather Research and Forecasting Model (WRF) model with the Regional Oceanic Modeling System (ROMS). We modified the WRF model to account for the radiative effect of volcanic aerosols. Our coupled ocean-atmosphere simulations verified by available observations revealed strong perturbations in the energy balance of the Red Sea, which drove thermal and circulation responses. Our modeling approach allowed us to separate changes in the atmospheric circulation caused by the impact of the volcano from direct regional radiative cooling from volcanic aerosols. The atmospheric circulation effect was significantly stronger than the direct volcanic aerosols effect. We found that the Red Sea response to the Pinatubo eruption was stronger and qualitatively different from that of the global ocean system. Our results suggest that major volcanic eruptions significantly affect the climate in the Middle East and the Red Sea and should be carefully taken into account in assessments of long-term climate variability and warming trends in MENA and the Red Sea.

Three-dimensional hydrogeologic framework model of the Rio Grande transboundary region of New Mexico and Texas, USA, and northern Chihuahua, Mexico

USGS Publications Warehouse

Sweetkind, Donald S.

2017-09-08

As part of a U.S. Geological Survey study in cooperation with the Bureau of Reclamation, a digital three-dimensional hydrogeologic framework model was constructed for the Rio Grande transboundary region of New Mexico and Texas, USA, and northern Chihuahua, Mexico. This model was constructed to define the aquifer system geometry and subsurface lithologic characteristics and distribution for use in a regional numerical hydrologic model. The model includes five hydrostratigraphic units: river channel alluvium, three informal subdivisions of Santa Fe Group basin fill, and an undivided pre-Santa Fe Group bedrock unit. Model input data were compiled from published cross sections, well data, structure contour maps, selected geophysical data, and contiguous compilations of surficial geology and structural features in the study area. These data were used to construct faulted surfaces that represent the upper and lower subsurface hydrostratigraphic unit boundaries. The digital three-dimensional hydrogeologic framework model is constructed through combining faults, the elevation of the tops of each hydrostratigraphic unit, and boundary lines depicting the subsurface extent of each hydrostratigraphic unit. The framework also compiles a digital representation of the distribution of sedimentary facies within each hydrostratigraphic unit. The digital three-dimensional hydrogeologic model reproduces with reasonable accuracy the previously published subsurface hydrogeologic conceptualization of the aquifer system and represents the large-scale geometry of the subsurface aquifers. The model is at a scale and resolution appropriate for use as the foundation for a numerical hydrologic model of the study area.

RESULTS OF PHOTOCHEMICAL SIMULATIONS OF SUBGRID SCALE POINT SOURCE EMISSIONS WITH THE MODELS-3 CMAQ MODELING SYSTEM

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) / Plume-in-Grid (PinG) model was applied on a domain encompassing the greater Nashville, Tennessee region. Model simulations were performed for selected days in July 1995 during the Southern Oxidant Study (SOS) field study program wh...

Applying the age-shift approach to model responses to midrotation fertilization

Treesearch

Colleen A. Carlson; Thomas R. Fox; H. Lee Allen; Timothy J. Albaugh

2010-01-01

Growth and yield models used to evaluate midrotation fertilization economics require adjustments to account for the typically observed responses. This study investigated the use of age-shift models to predict midrotation fertilizer responses. Age-shift prediction models were constructed from a regional study consisting of 43 installations of a nitrogen (N) by...

Comparing potential recharge estimates from three Land Surface Models across the Western US

PubMed Central

NIRAULA, REWATI; MEIXNER, THOMAS; AJAMI, HOORI; RODELL, MATTHEW; GOCHIS, DAVID; CASTRO, CHRISTOPHER L.

2018-01-01

Groundwater is a major source of water in the western US. However, there are limited recharge estimates available in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US. Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01–15% for Mosaic, 3.2–42% for Noah, and 6.7–31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge rates in data limited regions. PMID:29618845

Global and regional modeling of clouds and aerosols in the marine boundary layer during VOCALS: the VOCA intercomparison

DOE PAGES

Wyant, M. C.; Bretherton, Christopher S.; Wood, Robert; ...

2015-01-09

A diverse collection of models are used to simulate the marine boundary layer in the southeast Pacific region during the period of the October–November 2008 VOCALS REx (VAMOS Ocean Cloud Atmosphere Land Study Regional Experiment) field campaign. Regional models simulate the period continuously in boundary-forced free-running mode, while global forecast models and GCMs (general circulation models) are run in forecast mode. The models are compared to extensive observations along a line at 20° S extending westward from the South American coast. Most of the models simulate cloud and aerosol characteristics and gradients across the region that are recognizably similar tomore » observations, despite the complex interaction of processes involved in the problem, many of which are parameterized or poorly resolved. Some models simulate the regional low cloud cover well, though many models underestimate MBL (marine boundary layer) depth near the coast. Most models qualitatively simulate the observed offshore gradients of SO 2, sulfate aerosol, CCN (cloud condensation nuclei) concentration in the MBL as well as differences in concentration between the MBL and the free troposphere. Most models also qualitatively capture the decrease in cloud droplet number away from the coast. However, there are large quantitative intermodel differences in both means and gradients of these quantities. Many models are able to represent episodic offshore increases in cloud droplet number and aerosol concentrations associated with periods of offshore flow. Most models underestimate CCN (at 0.1% supersaturation) in the MBL and free troposphere. The GCMs also have difficulty simulating coastal gradients in CCN and cloud droplet number concentration near the coast. The overall performance of the models demonstrates their potential utility in simulating aerosol–cloud interactions in the MBL, though quantitative estimation of aerosol–cloud interactions and aerosol indirect effects of MBL clouds with these models remains uncertain.« less

Problems with the North American Monsoon in CMIP/IPCC GCM Precipitation

NASA Astrophysics Data System (ADS)

Schiffer, N. J.; Nesbitt, S. W.

2011-12-01

Successful water management in the Desert Southwest and surrounding areas hinges on anticipating the timing and distribution of precipitation. IPCC AR4 models predict a more arid climate, more extreme precipitation events, and an earlier peak in springtime streamflow in the North American Monsoon region as the area warms. This study aims to assess the summertime skill with which general circulation models (GCMs) simulate precipitation and related dynamics over this region, a necessary precursor to reliable hydroclimate projections. Thirty-year climatologies of several GCMs in the third and fifth Climate Model Intercomparison Projects (CMIP) are statistically evaluated against each other and observed climatology for their skill in representing the location, timing, variability, character, and large-scale forcing of precipitation over the southwestern United States and northwestern Mexico. The results of this study will lend greater credence to more detailed, higher resolution studies, based on the CMIP and IPCC models, of the region's future hydrology. Our ultimate goal is to provide guidance such that decision-makers can plan future water management with more confidence.

Approach to Assessing the Effects of Aerial Deposition on Water Quality in the Alberta Oil Sands Region.

PubMed

Dayyani, Shadi; Daly, Gillian; Vandenberg, Jerry

2016-02-01

Snow cover forms a porous medium that acts as a receptor for aerially deposited polycyclic aromatic hydrocarbons (PAHs) and metals. The snowpack, acting as a temporary storage reservoir, releases contaminants accumulating over the winter during a relatively short melt period. This process could result in elevated concentrations of contaminants in melt water. Recent studies in the Alberta oil sands region have documented increases in snowpack and lake sediment concentrations; however, no studies have addressed the fate and transport of contaminants during the snowmelt period. This study describes modelling approaches that were developed to assess potential effects of aerially deposited PAHs and metals to snowpack and snowmelt water concentrations. The contribution of snowmelt to freshwater PAH concentrations is assessed using a dynamic, multi-compartmental fate model, and the contribution to metal concentrations is estimated using a mass-balance approach. The modelling approaches described herein were applied to two watersheds in the Alberta oil sands region for two planned oil sands developments. Accumulation of PAHs in a lake within the deposition zone was also modelled for comparison to observed concentrations.

Untangling the Effect of Head Acceleration on Brain Responses to Blast Waves

PubMed Central

Mao, Haojie; Unnikrishnan, Ginu; Rakesh, Vineet; Reifman, Jaques

2015-01-01

Multiple injury-causing mechanisms, such as wave propagation, skull flexure, cavitation, and head acceleration, have been proposed to explain blast-induced traumatic brain injury (bTBI). An accurate, quantitative description of the individual contribution of each of these mechanisms may be necessary to develop preventive strategies against bTBI. However, to date, despite numerous experimental and computational studies of bTBI, this question remains elusive. In this study, using a two-dimensional (2D) rat head model, we quantified the contribution of head acceleration to the biomechanical response of brain tissues when exposed to blast waves in a shock tube. We compared brain pressure at the coup, middle, and contre-coup regions between a 2D rat head model capable of simulating all mechanisms (i.e., the all-effects model) and an acceleration-only model. From our simulations, we determined that head acceleration contributed 36–45% of the maximum brain pressure at the coup region, had a negligible effect on the pressure at the middle region, and was responsible for the low pressure at the contre-coup region. Our findings also demonstrate that the current practice of measuring rat brain pressures close to the center of the brain would record only two-thirds of the maximum pressure observed at the coup region. Therefore, to accurately capture the effects of acceleration in experiments, we recommend placing a pressure sensor near the coup region, especially when investigating the acceleration mechanism using different experimental setups. PMID:26458125

A biomechanical modeling-guided simultaneous motion estimation and image reconstruction technique (SMEIR-Bio) for 4D-CBCT reconstruction

NASA Astrophysics Data System (ADS)

Huang, Xiaokun; Zhang, You; Wang, Jing

2018-02-01

Reconstructing four-dimensional cone-beam computed tomography (4D-CBCT) images directly from respiratory phase-sorted traditional 3D-CBCT projections can capture target motion trajectory, reduce motion artifacts, and reduce imaging dose and time. However, the limited numbers of projections in each phase after phase-sorting decreases CBCT image quality under traditional reconstruction techniques. To address this problem, we developed a simultaneous motion estimation and image reconstruction (SMEIR) algorithm, an iterative method that can reconstruct higher quality 4D-CBCT images from limited projections using an inter-phase intensity-driven motion model. However, the accuracy of the intensity-driven motion model is limited in regions with fine details whose quality is degraded due to insufficient projection number, which consequently degrades the reconstructed image quality in corresponding regions. In this study, we developed a new 4D-CBCT reconstruction algorithm by introducing biomechanical modeling into SMEIR (SMEIR-Bio) to boost the accuracy of the motion model in regions with small fine structures. The biomechanical modeling uses tetrahedral meshes to model organs of interest and solves internal organ motion using tissue elasticity parameters and mesh boundary conditions. This physics-driven approach enhances the accuracy of solved motion in the organ’s fine structures regions. This study used 11 lung patient cases to evaluate the performance of SMEIR-Bio, making both qualitative and quantitative comparisons between SMEIR-Bio, SMEIR, and the algebraic reconstruction technique with total variation regularization (ART-TV). The reconstruction results suggest that SMEIR-Bio improves the motion model’s accuracy in regions containing small fine details, which consequently enhances the accuracy and quality of the reconstructed 4D-CBCT images.