future model improvements: Topics by Science.gov

Sample records for future model improvements

Agricultural model intercomparison and improvement project: Overview of model intercomparisons

USDA-ARS?s Scientific Manuscript database

Improvement of crop simulation models to better estimate growth and yield is one of the objectives of the Agricultural Model Intercomparison and Improvement Project (AgMIP). The overall goal of AgMIP is to provide an assessment of crop model through rigorous intercomparisons and evaluate future clim...
Shared ownership: what's the future?

PubMed

Roth, Karen L

2013-01-01

The status of library consortia has evolved over time in terms of their composition and alternative negotiating models. New purchasing models may allow improved library involvement in the acquisitions process and improved methods for meeting users' future needs. Ever-increasing costs of library resources and the need to reduce expenses make it necessary to continue the exploration of library consortia for group purchases.
How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability.

PubMed

Fitzpatrick, Matthew C; Blois, Jessica L; Williams, John W; Nieto-Lugilde, Diego; Maguire, Kaitlin C; Lorenz, David J

2018-03-23

Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co-occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage-level information. © 2018 John Wiley & Sons Ltd.
Assimilating the Future for Better Forecasts and Earlier Warnings

NASA Astrophysics Data System (ADS)

Du, H.; Wheatcroft, E.; Smith, L. A.

2016-12-01

Multi-model ensembles have become popular tools to account for some of the uncertainty due to model inadequacy in weather and climate simulation-based predictions. The current multi-model forecasts focus on combining single model ensemble forecasts by means of statistical post-processing. Assuming each model is developed independently or with different primary target variables, each is likely to contain different dynamical strengths and weaknesses. Using statistical post-processing, such information is only carried by the simulations under a single model ensemble: no advantage is taken to influence simulations under the other models. A novel methodology, named Multi-model Cross Pollination in Time, is proposed for multi-model ensemble scheme with the aim of integrating the dynamical information regarding the future from each individual model operationally. The proposed approach generates model states in time via applying data assimilation scheme(s) to yield truly "multi-model trajectories". It is demonstrated to outperform traditional statistical post-processing in the 40-dimensional Lorenz96 flow. Data assimilation approaches are originally designed to improve state estimation from the past to the current time. The aim of this talk is to introduce a framework that uses data assimilation to improve model forecasts at future time (not to argue for any one particular data assimilation scheme). Illustration of applying data assimilation "in the future" to provide early warning of future high-impact events is also presented.
Dengue: recent past and future threats

PubMed Central

Rogers, David J.

2015-01-01

This article explores four key questions about statistical models developed to describe the recent past and future of vector-borne diseases, with special emphasis on dengue: (1) How many variables should be used to make predictions about the future of vector-borne diseases?(2) Is the spatial resolution of a climate dataset an important determinant of model accuracy?(3) Does inclusion of the future distributions of vectors affect predictions of the futures of the diseases they transmit?(4) Which are the key predictor variables involved in determining the distributions of vector-borne diseases in the present and future?Examples are given of dengue models using one, five or 10 meteorological variables and at spatial resolutions of from one-sixth to two degrees. Model accuracy is improved with a greater number of descriptor variables, but is surprisingly unaffected by the spatial resolution of the data. Dengue models with a reduced set of climate variables derived from the HadCM3 global circulation model predictions for the 1980s are improved when risk maps for dengue's two main vectors (Aedes aegypti and Aedes albopictus) are also included as predictor variables; disease and vector models are projected into the future using the global circulation model predictions for the 2020s, 2040s and 2080s. The Garthwaite–Koch corr-max transformation is presented as a novel way of showing the relative contribution of each of the input predictor variables to the map predictions. PMID:25688021
The agricultural model intercomparison and improvement project (AgMIP): Protocols and pilot studies

USDA-ARS?s Scientific Manuscript database

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation research activity for historical period model intercomparison and future climate change conditions with participation of multiple crop and agricultural economic model groups around the...
Model-data integration to improve the LPJmL dynamic global vegetation model

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno

2017-04-01

Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the simulated ecosystem dynamics which consequently changed the development of ecosystem carbon stocks and fluxes under future climate and CO2 change. In summary, our results demonstrate challenges and the potential of using model-data integration approaches to improve a dynamic global vegetation model.
Regional analysis of drought and heat impacts on forests: current and future science directions.

PubMed

Law, Beverly E

2014-12-01

Accurate assessments of forest response to current and future climate and human actions are needed at regional scales. Predicting future impacts on forests will require improved analysis of species-level adaptation, resilience, and vulnerability to mortality. Land system models can be enhanced by creating trait-based groupings of species that better represent climate sensitivity, such as risk of hydraulic failure from drought. This emphasizes the need for more coordinated in situ and remote sensing observations to track changes in ecosystem function, and to improve model inputs, spatio-temporal diagnosis, and predictions of future conditions, including implications of actions to mitigate climate change. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
Economic analysis of tree improvement: A status report

Treesearch

George F. Dutrow

1974-01-01

Review of current literature establishes that most authors believe that tree improvement expands production, although some point out drawbacks and alternatives. Both softwood and hardwood improvement programs have been analyzed. The authors used various models, economic assumptions, and standards of measurement, but available data were limited. Future models shouId...
Integrated Modeling of Optical Systems (IMOS): An Assessment and Future Directions

NASA Technical Reports Server (NTRS)

Moore, Gregory; Broduer, Steve (Technical Monitor)

2001-01-01

Integrated Modeling of Optical Systems (IMOS) is a finite element-based code combining structural, thermal, and optical ray-tracing capabilities in a single environment for analysis of space-based optical systems. We'll present some recent examples of IMOS usage and discuss future development directions. Due to increasing model sizes and a greater emphasis on multidisciplinary analysis and design, much of the anticipated future work will be in the areas of improved architecture, numerics, and overall performance and analysis integration.
76 FR 53137 - Bundled Payments for Care Improvement Initiative: Request for Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-25

... (RFA) will test episode-based payment for acute care and associated post-acute care, using both retrospective and prospective bundled payment methods. The RFA requests applications to test models centered around acute care; these models will inform the design of future models, including care improvement for...
An eco-evolutionary IBM improves predictions of future geneticconnectivity for American Pikas (Ochotona princeps) in Crater Lake National Park, Oregon

EPA Science Inventory

In the face of rapid, contemporary climate change, conservationbiologists are relying heavily on species distribution models (SDMs)to predict shifting occupancy and distribution patterns in responseto future conditions. These models are critical tools for assessingvulnerability t...
Scenarios of land use change for agriculture: the role of Land Evaluation in improving model simulation

NASA Astrophysics Data System (ADS)

Mereu, V.; Santini, M.; Dettori, G.; Muresu, P.; Spano, D.; Duce, P.

2009-12-01

Integrated scenarios of future climate and land use represent a useful input for impact studies about global changes. In particular, improving future land use simulations is essential for the agricultural sector, which is influenced by both biogeophysical constraints and human needs. Often land use change models are mainly based on statistical relationships between known land use distribution and biophysical or socio-economic factors, neglecting the necessary consideration of physical constraints that interact in making lands more or less capable for agriculture and suitable for supporting specific crops. In this study, a well developed land use change model (CLUE@CMCC) was suited for the Mediterranean basin case study, focusing on croplands. Several climate scenarios and future demands for croplands were combined to drive the model, while the same climate scenarios were used to more reliably allocate crops in the most suitable areas on the basis of Land Evaluation techniques. The probability for each map unit to sustain a specific crop, usually related to location characteristics, elasticity to conversion and competition among land use types, now includes specific crop-favoring location characteristics. Results, besides improving the consistency of the land use change model to allocate land for the future, can have the main feedback to suggest feasibility or reasonable thresholds to adjust land use demands during dynamic simulations.
Conjunctive management of surface and groundwater resources under projected future climate change scenarios

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

Mani, Amir; Tsai, Frank T. -C.; Kao, Shih-Chieh

Our study introduces a mixed integer linear fractional programming (MILFP) method to optimize conjunctive use of future surface water and groundwater resources under projected climate change scenarios. The conjunctive management model maximizes the ratio of groundwater usage to reservoir water usage. Future inflows to the reservoirs were estimated from the future runoffs projected through hydroclimate modeling considering the Variable Infiltration Capacity model, and 11 sets of downscaled Coupled Model Intercomparison Project phase 5 global climate model projections. Bayesian model averaging was adopted to quantify uncertainty in future runoff projections and reservoir inflow projections due to uncertain future climate projections. Optimizedmore » conjunctive management solutions were investigated for a water supply network in northern Louisiana which includes the Sparta aquifer. Runoff projections under climate change scenarios indicate that runoff will likely decrease in winter and increase in other seasons. Ultimately, results from the developed conjunctive management model with MILFP indicate that the future reservoir water, even at 2.5% low inflow cumulative probability level, could counterbalance groundwater pumping reduction to satisfy demands while improving the Sparta aquifer through conditional groundwater head constraint.« less
Conjunctive management of surface and groundwater resources under projected future climate change scenarios

DOE PAGES

Mani, Amir; Tsai, Frank T. -C.; Kao, Shih-Chieh; ...

2016-06-16

Our study introduces a mixed integer linear fractional programming (MILFP) method to optimize conjunctive use of future surface water and groundwater resources under projected climate change scenarios. The conjunctive management model maximizes the ratio of groundwater usage to reservoir water usage. Future inflows to the reservoirs were estimated from the future runoffs projected through hydroclimate modeling considering the Variable Infiltration Capacity model, and 11 sets of downscaled Coupled Model Intercomparison Project phase 5 global climate model projections. Bayesian model averaging was adopted to quantify uncertainty in future runoff projections and reservoir inflow projections due to uncertain future climate projections. Optimizedmore » conjunctive management solutions were investigated for a water supply network in northern Louisiana which includes the Sparta aquifer. Runoff projections under climate change scenarios indicate that runoff will likely decrease in winter and increase in other seasons. Ultimately, results from the developed conjunctive management model with MILFP indicate that the future reservoir water, even at 2.5% low inflow cumulative probability level, could counterbalance groundwater pumping reduction to satisfy demands while improving the Sparta aquifer through conditional groundwater head constraint.« less
Investigating the Effect of Advanced Automatic Transmissions of Fuel Consumption Using Vehicle Testing and Modeling (SAE 2016-01-1142)

EPA Science Inventory

EPA used the validated ALPHA model to predict the effectiveness improvement of real-world transmissions over a baseline four-speed transmission and to predict further improvements possible from future eight-speed transmissions.
Improved hydrological model parametrization for climate change impact assessment under data scarcity - The potential of field monitoring techniques and geostatistics.

PubMed

Meyer, Swen; Blaschek, Michael; Duttmann, Rainer; Ludwig, Ralf

2016-02-01

According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. These changes are expected to have severe direct impacts on the management of water resources, agricultural productivity and drinking water supply. Current projections of future hydrological change, based on regional climate model results and subsequent hydrological modeling schemes, are very uncertain and poorly validated. The Rio Mannu di San Sperate Basin, located in Sardinia, Italy, is one test site of the CLIMB project. The Water Simulation Model (WaSiM) was set up to model current and future hydrological conditions. The availability of measured meteorological and hydrological data is poor as it is common for many Mediterranean catchments. In this study we conducted a soil sampling campaign in the Rio Mannu catchment. We tested different deterministic and hybrid geostatistical interpolation methods on soil textures and tested the performance of the applied models. We calculated a new soil texture map based on the best prediction method. The soil model in WaSiM was set up with the improved new soil information. The simulation results were compared to standard soil parametrization. WaSiMs was validated with spatial evapotranspiration rates using the triangle method (Jiang and Islam, 1999). WaSiM was driven with the meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. The climate change impact was assessed based on differences between reference and future time series. The simulated results show a reduction of all hydrological quantities in the future in the spring season. Furthermore simulation results reveal an earlier onset of dry conditions in the catchment. We show that a solid soil model setup based on short-term field measurements can improve long-term modeling results, which is especially important in ungauged catchments. Copyright © 2015 Elsevier B.V. All rights reserved.
Reducing the Uncertainty in Atlantic Meridional Overturning Circulation Projections Using Bayesian Model Averaging

NASA Astrophysics Data System (ADS)

Olson, R.; An, S. I.

2016-12-01

Atlantic Meridional Overturning Circulation (AMOC) in the ocean might slow down in the future, which can lead to a host of climatic effects in North Atlantic and throughout the world. Despite improvements in climate models and availability of new observations, AMOC projections remain uncertain. Here we constrain CMIP5 multi-model ensemble output with observations of a recently developed AMOC index to provide improved Bayesian predictions of future AMOC. Specifically, we first calculate yearly AMOC index loosely based on Rahmstorf et al. (2015) for years 1880—2004 for both observations, and the CMIP5 models for which relevant output is available. We then assign a weight to each model based on a Bayesian Model Averaging method that accounts for differential model skill in terms of both mean state and variability. We include the temporal autocorrelation in climate model errors, and account for the uncertainty in the parameters of our statistical model. We use the weights to provide future weighted projections of AMOC, and compare them to un-weighted ones. Our projections use bootstrapping to account for uncertainty in internal AMOC variability. We also perform spectral and other statistical analyses to show that AMOC index variability, both in models and in observations, is consistent with red noise. Our results improve on and complement previous work by using a new ensemble of climate models, a different observational metric, and an improved Bayesian weighting method that accounts for differential model skill at reproducing internal variability. Reference: Rahmstorf, S., Box, J. E., Feulner, G., Mann, M. E., Robinson, A., Rutherford, S., & Schaffernicht, E. J. (2015). Exceptional twentieth-century slowdown in atlantic ocean overturning circulation. Nature Climate Change, 5(5), 475-480. doi:10.1038/nclimate2554
Systematic Review of Model-Based Economic Evaluations of Treatments for Alzheimer's Disease.

PubMed

Hernandez, Luis; Ozen, Asli; DosSantos, Rodrigo; Getsios, Denis

2016-07-01

Numerous economic evaluations using decision-analytic models have assessed the cost effectiveness of treatments for Alzheimer's disease (AD) in the last two decades. It is important to understand the methods used in the existing models of AD and how they could impact results, as they could inform new model-based economic evaluations of treatments for AD. The aim of this systematic review was to provide a detailed description on the relevant aspects and components of existing decision-analytic models of AD, identifying areas for improvement and future development, and to conduct a quality assessment of the included studies. We performed a systematic and comprehensive review of cost-effectiveness studies of pharmacological treatments for AD published in the last decade (January 2005 to February 2015) that used decision-analytic models, also including studies considering patients with mild cognitive impairment (MCI). The background information of the included studies and specific information on the decision-analytic models, including their approach and components, assumptions, data sources, analyses, and results, were obtained from each study. A description of how the modeling approaches and assumptions differ across studies, identifying areas for improvement and future development, is provided. At the end, we present our own view of the potential future directions of decision-analytic models of AD and the challenges they might face. The included studies present a variety of different approaches, assumptions, and scope of decision-analytic models used in the economic evaluation of pharmacological treatments of AD. The major areas for improvement in future models of AD are to include domains of cognition, function, and behavior, rather than cognition alone; include a detailed description of how data used to model the natural course of disease progression were derived; state and justify the economic model selected and structural assumptions and limitations; provide a detailed (rather than high-level) description of the cost components included in the model; and report on the face-, internal-, and cross-validity of the model to strengthen the credibility and confidence in model results. The quality scores of most studies were rated as fair to good (average 87.5, range 69.5-100, in a scale of 0-100). Despite the advancements in decision-analytic models of AD, there remain several areas of improvement that are necessary to more appropriately and realistically capture the broad nature of AD and the potential benefits of treatments in future models of AD.
Future riverine nitrogen export to US coastal regions: Prospects for improving water quality amid population growth.

EPA Science Inventory

Excess nitrogen (N) in the environment degrades ecosystems and adversely affects human health. Here we examine predictions of contemporary (2000) and future (2030) coastal N loading in the continental US by the Nutrient Export from WaterSheds (NEWS) model. Future scenarios were b...

Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio

NASA Astrophysics Data System (ADS)

Aburas, Maher Milad; Ho, Yuek Ming; Ramli, Mohammad Firuz; Ash'aari, Zulfa Hanan

2017-07-01

The creation of an accurate simulation of future urban growth is considered one of the most important challenges in urban studies that involve spatial modeling. The purpose of this study is to improve the simulation capability of an integrated CA-Markov Chain (CA-MC) model using CA-MC based on the Analytical Hierarchy Process (AHP) and CA-MC based on Frequency Ratio (FR), both applied in Seremban, Malaysia, as well as to compare the performance and accuracy between the traditional and hybrid models. Various physical, socio-economic, utilities, and environmental criteria were used as predictors, including elevation, slope, soil texture, population density, distance to commercial area, distance to educational area, distance to residential area, distance to industrial area, distance to roads, distance to highway, distance to railway, distance to power line, distance to stream, and land cover. For calibration, three models were applied to simulate urban growth trends in 2010; the actual data of 2010 were used for model validation utilizing the Relative Operating Characteristic (ROC) and Kappa coefficient methods Consequently, future urban growth maps of 2020 and 2030 were created. The validation findings confirm that the integration of the CA-MC model with the FR model and employing the significant driving force of urban growth in the simulation process have resulted in the improved simulation capability of the CA-MC model. This study has provided a novel approach for improving the CA-MC model based on FR, which will provide powerful support to planners and decision-makers in the development of future sustainable urban planning.
Blended Learning and Innovative Technologies in Training of Future Specialists in Foreign Higher Education Institutions

ERIC Educational Resources Information Center

Gurevych, Roman; Kademiya, Maya

2017-01-01

The article characterizes one of the most promising models of blended learning in higher education institutions. The article describes the peculiarities of improving the education process, the formation of motivational and professional competency of future specialists as well as the usage of one of the models of blended learning--"flipped…
The International Reference Ionosphere Today and in the Future

NASA Technical Reports Server (NTRS)

Bilitza, Dieter; McKinnell, Lee-Ane; Reinisch, Bodo; Fuller-Rowell,Tim

2010-01-01

The international reference ionosphere (IRI) is the internationally recognized and recommended standard for the specification of plasma parameters in Earth's ionosphere. It describes monthly averages of electron density, electron temperature, ion temperature, ion composition, and several additional parameters in the altitude range from 60 to 1,500 km. A joint working group of the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI) is in charge of developing and improving the IRI model. As requested by COSPAR and URSI, IRI is an empirical model being based on most of the available and reliable data sources for the ionospheric plasma. The paper describes the latest version of the model and reviews efforts towards future improvements, including the development of new global models for the F2 peak density and height, and a new approach to describe the electron density in the topside and plasmasphere. Our emphasis will be on the electron density because it is the IRI parameter most relevant to geodetic techniques and studies. Annual IRI meetings are the main venue for the discussion of IRI activities, future improvements, and additions to the model. A new special IRI task force activity is focusing on the development of a real-time IRI (RT-IRI) by combining data assimilation techniques with the IRI model. A first RT-IRI task force meeting was held in 2009 in Colorado Springs. We will review the outcome of this meeting and the plans for the future. The IRI homepage is at http://www.IRI.gsfc.nasa.gov
Modeling Future Fire danger over North America in a Changing Climate

NASA Astrophysics Data System (ADS)

Jain, P.; Paimazumder, D.; Done, J.; Flannigan, M.

2016-12-01

Fire danger ratings are used to determine wildfire potential due to weather and climate factors. The Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System (CFFDRS), incorporates temperature, relative humidity, windspeed and precipitation to give a daily fire danger rating that is used by wildfire management agencies in an operational context. Studies using GCM output have shown that future wildfire danger will increase in a warming climate. However, these studies are somewhat limited by the coarse spatial resolution (typically 100-400km) and temporal resolution (typically 6-hourly to monthly) of the model output. Future wildfire potential over North America based on FWI is calculated using output from the Weather, Research and Forecasting (WRF) model, which is used to downscale future climate scenarios from the bias-corrected Community Climate System Model (CCSM) under RCP8.5 scenarios at a spatial resolution of 36km. We consider five eleven year time slices: 1990-2000, 2020-2030, 2030-2040, 2050-2060 and 2080-2090. The dynamically downscaled simulation improves determination of future extreme weather by improving both spatial and temporal resolution over most GCM models. To characterize extreme fire weather we calculate annual numbers of spread days (days for which FWI > 19) and annual 99th percentile of FWI. Additionally, an extreme value analysis based on the peaks-over-threshold method allows us to calculate the return values for extreme FWI values.
Future riverine nitrogen export to US coastal regions: Prospects for improving water quality considering population growth

EPA Science Inventory

Excess nitrogen (N) in the environment degrades ecosystems and adversely affects human health. Here we examine predictions of contemporary (2000) and future (2030) coastal N loading in the continental US by the Nutrient Export from WaterSheds (NEWS) model. Future output is from s...
Improving Climate Projections Using "Intelligent" Ensembles

NASA Technical Reports Server (NTRS)

Baker, Noel C.; Taylor, Patrick C.

2015-01-01

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.
An improved Burgers cellular automaton model for bicycle flow

NASA Astrophysics Data System (ADS)

Xue, Shuqi; Jia, Bin; Jiang, Rui; Li, Xingang; Shan, Jingjing

2017-12-01

As an energy-efficient and healthy transport mode, bicycling has recently attracted the attention of governments, transport planners, and researchers. The dynamic characteristics of the bicycle flow must be investigated to improve the facility design and traffic operation of bicycling. We model the bicycle flow by using an improved Burgers cellular automaton model. Through a following move mechanism, the modified model enables bicycles to move smoothly and increase the critical density to a more rational level than the original model. The model is calibrated and validated by using experimental data and field data. The results show that the improved model can effectively simulate the bicycle flow. The performance of the model under different parameters is investigated and discussed. Strengths and limitations of the improved model are suggested for future work.
System dynamics approach for modeling of sugar beet yield considering the effects of climatic variables.

PubMed

Pervin, Lia; Islam, Md Saiful

2015-02-01

The aim of this study was to develop a system dynamics model for computation of yields and to investigate the dependency of yields on some major climatic parameters, i.e. temperature and rainfall, for Beta vulgaris subsp. (sugar beet crops) under future climate change scenarios. A system dynamics model was developed which takes account of the effects of rainfall and temperature on sugar beet yields under limited irrigation conditions. A relationship was also developed between the seasonal evapotranspiration and seasonal growing degree days for sugar beet crops. The proposed model was set to run for the present time period of 1993-2012 and for the future period 2013-2040 for Lethbridge region (Alberta, Canada). The model provides sugar beet yields on a yearly basis which are comparable to the present field data. It was found that the future average yield will be increased at about 14% with respect to the present average yield. The proposed model can help to improve the understanding of soil water conditions and irrigation water requirements of an area under certain climatic conditions and can be used for future prediction of yields for any crops in any region (with the required information to be provided). The developed system dynamics model can be used as a supporting tool for decision making, for improvement of agricultural management practice of any region. © 2014 Society of Chemical Industry.
Development of Future Scenario Emission Inventories for East Asia in Support of Multiple Modeling Studies

NASA Astrophysics Data System (ADS)

Kim, Y.; Woo, J. H.; Choi, K. C.; Lee, J. B.; Song, C. K.; Kim, S. K.; Hong, J.; Hong, S. C.; Zhang, Q.; Hong, C.; Tong, D.

2015-12-01

Future emission scenarios based on up-to-date regional socio-economic and control policy information were developed in support of climate-air quality integrated modeling research over East Asia. Two IPCC-participated Integrated Assessment Models(IAMs) were used to developed those scenario pathways. The two emission processing systems, KU-EPS and SMOKE-Asia, were used to convert these future scenario emissions to comprehensive chemical transport model-ready form. The NIER/KU-CREATE (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment) served as the regional base-year emission inventory. For anthropogenic emissions, it has 54 fuel classes, 201 sub-sectors and 13 pollutants, including CO2, CH4, N2O, SO2, NOx, CO, NMVOC, NH3, OC, BC, PM10, PM2.5, and mercury. Fast energy growth and aggressive penetration of the control measures make emissions projection very active for East Asia. Despite of more stringent air pollution control policies by the governments, however, air quality over the region seems not been improved as much - even worse in many cases. The needs of more scientific understanding of inter-relationship among emissions, transport, chemistry over the region are very high to effectively protect public health and ecosystems against ozone, fine particles, and other toxic pollutants in the air. After developing these long-term future emissions, therefore, we also tried to apply our future scenarios to develop the present emissions inventory for chemical weather forecasting and aircraft field campaign. On site, we will present; 1) the future scenario development framework and process methodologies, 2) initial development results of the future emission pathways, 3) present emission inventories from short-term projection, and 4) air quality modeling performance improvements over the region.
Drivers' communicative interactions: on-road observations and modelling for integration in future automation systems.

PubMed

Portouli, Evangelia; Nathanael, Dimitris; Marmaras, Nicolas

2014-01-01

Social interactions with other road users are an essential component of the driving activity and may prove critical in view of future automation systems; still up to now they have received only limited attention in the scientific literature. In this paper, it is argued that drivers base their anticipations about the traffic scene to a large extent on observations of social behaviour of other 'animate human-vehicles'. It is further argued that in cases of uncertainty, drivers seek to establish a mutual situational awareness through deliberate communicative interactions. A linguistic model is proposed for modelling these communicative interactions. Empirical evidence from on-road observations and analysis of concurrent running commentary by 25 experienced drivers support the proposed model. It is suggested that the integration of a social interactions layer based on illocutionary acts in future driving support and automation systems will improve their performance towards matching human driver's expectations. Practitioner Summary: Interactions between drivers on the road may play a significant role in traffic coordination. On-road observations and running commentaries are presented as empirical evidence to support a model of such interactions; incorporation of drivers' interactions in future driving support and automation systems may improve their performance towards matching driver's expectations.
Spatial Statistical Network Models for Stream and River Temperature in the Chesapeake Bay Watershed, USA

EPA Science Inventory

Regional temperature models are needed for characterizing and mapping stream thermal regimes, establishing reference conditions, predicting future impacts and identifying critical thermal refugia. Spatial statistical models have been developed to improve regression modeling techn...
The maturing of the quality improvement paradigm in the SEL

NASA Technical Reports Server (NTRS)

Basili, Victor R.

1993-01-01

The Software Engineering Laboratory uses a paradigm for improving the software process and product, called the quality improvement paradigm. This paradigm has evolved over the past 18 years, along with our software development processes and product. Since 1976, when we first began the SEL, we have learned a great deal about improving the software process and product, making a great many mistakes along the way. Quality improvement paradigm, as it is currently defined, can be broken up into six steps: characterize the current project and its environment with respect to the appropriate models and metrics; set the quantifiable goals for successful project performance and improvement; choose the appropriate process model and supporting methods and tools for this project; execute the processes, construct the products, and collect, validate, and analyze the data to provide real-time feedback for corrective action; analyze the data to evaluate the current practices, determine problems, record findings, and make recommendations for future project improvements; and package the experience gained in the form of updated and refined models and other forms of structured knowledge gained from this and prior projects and save it in an experience base to be reused on future projects.
Analysis of rocket engine injection combustion processes

NASA Technical Reports Server (NTRS)

Salmon, J. W.; Saltzman, D. H.

1977-01-01

Mixing methodology improvement for the JANNAF DER and CICM injection/combustion analysis computer programs was accomplished. ZOM plane prediction model development was improved for installation into the new standardized DER computer program. An intra-element mixing model developing approach was recommended for gas/liquid coaxial injection elements for possible future incorporation into the CICM computer program.
Alternative futures of dissolved inorganic nitrogen export from ...

EPA Pesticide Factsheets

Nitrogen (N) export from the Mississippi River Basin contributes to seasonal hypoxia in the Gulf of Mexico (GOM). We explored monthly dissolved inorganic N (DIN) export to the GOM for a historical year (2002) and two future scenarios (year 2022) by linking macroeonomic energy, agriculture market, air quality, and agriculture land management models to a DIN export model. Future scenarios considered policies aimed at encouraging bioenergy crop production and reducing atmospheric N-emissions, as well as the effect of population growth and the states’ infrastructure plans on sewage fluxes. Model-derived DIN export decreased by about 9% (from 279 to 254 kg N km−2 year−1) between 2002 and 2022 due to a 28% increase in area planted with corn, 24% improvement in crop N-recovery efficiency (NRE, to 0.52), 22% reduction in atmospheric N deposition, and 23% increase in sewage inputs. Changes in atmospheric and sewage inputs had a relatively small effect on DIN export and the effect of bioenergy crop production depended on nutrient management practices. Without improved NRE, increased production of corn would have increased DIN export by about 14% (to 289 kg N km−2 year−1) between 2002 and 2022. Model results suggest that meeting future crop demand while reducing the areal extent of hypoxia could require aggressive actions, such improving basin-level crop NRE to 0.62 or upgrading N-removal capabilities in waste water treatment plants beyond current plans. Tile-dra
Multifactor valuation models of energy futures and options on futures

NASA Astrophysics Data System (ADS)

Bertus, Mark J.

The intent of this dissertation is to investigate continuous time pricing models for commodity derivative contracts that consider mean reversion. The motivation for pricing commodity futures and option on futures contracts leads to improved practical risk management techniques in markets where uncertainty is increasing. In the dissertation closed-form solutions to mean reverting one-factor, two-factor, three-factor Brownian motions are developed for futures contracts. These solutions are obtained through risk neutral pricing methods that yield tractable expressions for futures prices, which are linear in the state variables, hence making them attractive for estimation. These functions, however, are expressed in terms of latent variables (i.e. spot prices, convenience yield) which complicate the estimation of the futures pricing equation. To address this complication a discussion on Dynamic factor analysis is given. This procedure documents latent variables using a Kalman filter and illustrations show how this technique may be used for the analysis. In addition, to the futures contracts closed form solutions for two option models are obtained. Solutions to the one- and two-factor models are tailored solutions of the Black-Scholes pricing model. Furthermore, since these contracts are written on the futures contracts, they too are influenced by the same underlying parameters of the state variables used to price the futures contracts. To conclude, the analysis finishes with an investigation of commodity futures options that incorporate random discrete jumps.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Cort, K. A.; Hostick, D. J.; Belzer, D. B.

The purpose of the project was to identify and characterize the modeling of deployment programs within the EERE Technology Development (TD) programs, address possible improvements to the modeling process, and note gaps in knowledge for future research.
Vegetation projections for Wind Cave National Park with three future climate scenarios: Final report in completion of Task Agreement J8W07100052

USGS Publications Warehouse

King, David A.; Bachelet, Dominique M.; Symstad, Amy J.

2013-01-01

Since the initial application of MC1 to a small portion of WICA (Bachelet et al. 2000), the model has been altered to improve model performance with the inclusion of dynamic fire. Applying this improved version to WICA required substantial recalibration, during which we have made a number of improvements to MC1 that will be incorporated as permanent changes. In this report we document these changes and our calibration procedure following a brief overview of the model. We compare the projections of current vegetation to the current state of the park and present projections of vegetation dynamics under future climates downscaled from three GCMs selected to represent the existing range in available GCM projections. In doing so, we examine the consequences of different management options regarding fire and grazing, major aspects of biotic management at Wind Cave.
Validation of X1 motorcycle model in industrial plant layout by using WITNESSTM simulation software

NASA Astrophysics Data System (ADS)

Hamzas, M. F. M. A.; Bareduan, S. A.; Zakaria, M. Z.; Tan, W. J.; Zairi, S.

2017-09-01

This paper demonstrates a case study on simulation, modelling and analysis for X1 Motorcycles Model. In this research, a motorcycle assembly plant has been selected as a main place of research study. Simulation techniques by using Witness software were applied to evaluate the performance of the existing manufacturing system. The main objective is to validate the data and find out the significant impact on the overall performance of the system for future improvement. The process of validation starts when the layout of the assembly line was identified. All components are evaluated to validate whether the data is significance for future improvement. Machine and labor statistics are among the parameters that were evaluated for process improvement. Average total cycle time for given workstations is used as criterion for comparison of possible variants. From the simulation process, the data used are appropriate and meet the criteria for two-sided assembly line problems.
Ceramic thermal barrier coatings for commercial gas turbine engines

NASA Technical Reports Server (NTRS)

Meier, Susan Manning; Gupta, Dinesh K.; Sheffler, Keith D.

1991-01-01

The paper provides an overview of the short history, current status, and future prospects of ceramic thermal barrier coatings for gas turbine engines. Particular attention is given to plasma-sprayed and electron beam-physical vapor deposited yttria-stabilized (7 wt pct Y2O3) zirconia systems. Recent advances include improvements in the spallation life of thermal barrier coatings, improved bond coat composition and spraying techniques, and improved component design. The discussion also covers field experience, life prediction modeling, and future directions in ceramic coatings in relation to gas turbine engine design.
Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Xu, Xiaofeng; Yuan, Fengming; Hanson, Paul J.; Wullschleger, Stan D.; Thornton, Peter E.; Riley, William J.; Song, Xia; Graham, David E.; Song, Changchun; Tian, Hanqin

2016-06-01

Over the past 4 decades, a number of numerical models have been developed to quantify the magnitude, investigate the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH4) fluxes within terrestrial ecosystems. These CH4 models are also used for integrating multi-scale CH4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls, and (3) significant data-model and model-model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Three areas for future improvements and applications of terrestrial CH4 models are that (1) CH4 models should more explicitly represent the mechanisms underlying land-atmosphere CH4 exchange, with an emphasis on improving and validating individual CH4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. These improvements in CH4 models would be beneficial for the Earth system models and further simulation of climate-carbon cycle feedbacks.

Evaluation of origin-destination matrix estimation techniques to support aspects of traffic modeling.

DOT National Transportation Integrated Search

2014-05-01

Travel demand forecasting models are used to predict future traffic volumes to evaluate : roadway improvement alternatives. Each of the metropolitan planning organizations (MPO) in : Alabama maintains a travel demand model to support planning efforts...
Passive Thermal Control Challenges for Future Exploration Missions

NASA Technical Reports Server (NTRS)

Rickman, Steven L.

2004-01-01

This slide presentation reviews the importance of developing passive thermal control for the future exploration missions envisioned in President Bush's call for human exploration of the Moon and Mars. Included in the presentation is a review of the conditions that make the thermal control very challenging on the Moon and Mars. With the future miniaturization of electronics components, power density and the associated challenges of electronics heat dissipation will provide new challenges. There is a challenge for improvement in modeling and analysis of thermal control systems, and for improved facilities to support testing of thermal-vacuum systems.
Past and future weather-induced risk in crop production

NASA Astrophysics Data System (ADS)

Elliott, J. W.; Glotter, M.; Russo, T. A.; Sahoo, S.; Foster, I.; Benton, T.; Mueller, C.

2016-12-01

Drought-induced agricultural loss is one of the most costly impacts of extreme weather and may harm more people than any other consequence of climate change. Improvements in farming practices have dramatically increased crop productivity, but yields today are still tightly linked to climate variation. We report here on a number of recent studies evaluating extreme event risk and impacts under historical and near future conditions, including studies conducted as part of the Agricultural Modeling Intercomparison and Improvement Project (AgMIP), the Inter-Sectoral Impacts Model Intercomparison Project (ISI-MIP) and the UK-US Taskforce on Extreme Weather and Global Food System Resilience.
The value of improved (ERS) information based on domestic distribution effects of U.S. agriculture crops

NASA Technical Reports Server (NTRS)

Bradford, D. F.; Kelejian, H. H.; Brusch, R.; Gross, J.; Fishman, H.; Feenberg, D.

1974-01-01

The value of improving information for forecasting future crop harvests was investigated. Emphasis was placed upon establishing practical evaluation procedures firmly based in economic theory. The analysis was applied to the case of U.S. domestic wheat consumption. Estimates for a cost of storage function and a demand function for wheat were calculated. A model of market determinations of wheat inventories was developed for inventory adjustment. The carry-over horizon is computed by the solution of a nonlinear programming problem, and related variables such as spot and future price at each stage are determined. The model is adaptable to other markets. Results are shown to depend critically on the accuracy of current and proposed measurement techniques. The quantitative results are presented parametrically, in terms of various possible values of current and future accuracies.
Improving Global Modeling and Data Analysis Using Remotely-Sensed Rainfall Data: Lessons From TRMM and Plans for GPM

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Einaudi, Franco (Technical Monitor)

2001-01-01

I will discuss the need for accurate rainfall observations to improve our ability to model the earth's climate and improve short-range weather forecasts. I will give an overview of the recent progress in using of rainfall data provided by TRMM and other microwave instruments in data assimilation to improve global analyses and diagnose state-dependent systematic errors in physical parameterizations. I will outline the current and future research strategies in preparation for the Global Precipitation Mission.
Modeling of Photoionized Plasmas

NASA Technical Reports Server (NTRS)

Kallman, Timothy R.

2010-01-01

In this paper I review the motivation and current status of modeling of plasmas exposed to strong radiation fields, as it applies to the study of cosmic X-ray sources. This includes some of the astrophysical issues which can be addressed, the ingredients for the models, the current computational tools, the limitations imposed by currently available atomic data, and the validity of some of the standard assumptions. I will also discuss ideas for the future: challenges associated with future missions, opportunities presented by improved computers, and goals for atomic data collection.
The Agricultural Model Intercomparison and Improvement Project (AgMIP): Progress and Preliminary Results

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2011-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation exercise for historical model intercomparison and future climate change conditions with participation of multiple crop and agricultural trade modeling groups around the world. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Recent progress and the current status of AgMIP will be presented, highlighting three areas of activity: preliminary results from crop pilot studies, outcomes from regional workshops, and emerging scientific challenges. AgMIP crop modeling efforts are being led by pilot studies, which have been established for wheat, maize, rice, and sugarcane. These crop-specific initiatives have proven instrumental in testing and contributing to AgMIP protocols, as well as creating preliminary results for aggregation and input to agricultural trade models. Regional workshops are being held to encourage collaborations and set research activities in motion for key agricultural areas. The first of these workshops was hosted by Embrapa and UNICAMP and held in Campinas, Brazil. Outcomes from this meeting have informed crop modeling research activities within South America, AgMIP protocols, and future regional workshops. Several scientific challenges have emerged and are currently being addressed by AgMIP researchers. Areas of particular interest include geospatial weather generation, ensemble methods for climate scenarios and crop models, spatial aggregation of field-scale yields to regional and global production, and characterization of future changes in climate variability.
Improving sea level simulation in Mediterranean regional climate models

NASA Astrophysics Data System (ADS)

Adloff, Fanny; Jordà, Gabriel; Somot, Samuel; Sevault, Florence; Arsouze, Thomas; Meyssignac, Benoit; Li, Laurent; Planton, Serge

2017-08-01

For now, the question about future sea level change in the Mediterranean remains a challenge. Previous climate modelling attempts to estimate future sea level change in the Mediterranean did not meet a consensus. The low resolution of CMIP-type models prevents an accurate representation of important small scales processes acting over the Mediterranean region. For this reason among others, the use of high resolution regional ocean modelling has been recommended in literature to address the question of ongoing and future Mediterranean sea level change in response to climate change or greenhouse gases emissions. Also, it has been shown that east Atlantic sea level variability is the dominant driver of the Mediterranean variability at interannual and interdecadal scales. However, up to now, long-term regional simulations of the Mediterranean Sea do not integrate the full sea level information from the Atlantic, which is a substantial shortcoming when analysing Mediterranean sea level response. In the present study we analyse different approaches followed by state-of-the-art regional climate models to simulate Mediterranean sea level variability. Additionally we present a new simulation which incorporates improved information of Atlantic sea level forcing at the lateral boundary. We evaluate the skills of the different simulations in the frame of long-term hindcast simulations spanning from 1980 to 2012 analysing sea level variability from seasonal to multidecadal scales. Results from the new simulation show a substantial improvement in the modelled Mediterranean sea level signal. This confirms that Mediterranean mean sea level is strongly influenced by the Atlantic conditions, and thus suggests that the quality of the information in the lateral boundary conditions (LBCs) is crucial for the good modelling of Mediterranean sea level. We also found that the regional differences inside the basin, that are induced by circulation changes, are model-dependent and thus not affected by the LBCs. Finally, we argue that a correct configuration of LBCs in the Atlantic should be used for future Mediterranean simulations, which cover hindcast period, but also for scenarios.
A residency clinic chronic condition management quality improvement project.

PubMed

Halverson, Larry W; Sontheimer, Dan; Duvall, Sharon

2007-02-01

Quality improvement in chronic disease management is a major agenda for improving health and reducing health care costs. A six-component chronic disease management model can help guide this effort. Several characteristics of the "new model" of family medicine described by the Future of Family Medicine (FFM) Project Leadership Committee are promulgated to foster practice changes that improve quality. Our objective was to implement and assess a quality improvement project guided by the components of a chronic disease management model and FFM new model characteristics. Diabetes was selected as a model chronic disease focus. Multiple practice changes were implemented. A mature electronic medical record facilitated data collection and measurement of quality improvement progress. Data from the diabetes registry demonstrates that our efforts have been effective. Significant improvement occurred in five out of six quality indicators. Multidisciplinary teamwork in a model residency practice guided by chronic disease management principles and the FFM new model characteristics can produce significant management improvements in one important chronic disease.
Ice2sea - the future glacial contribution to sea-level rise

NASA Astrophysics Data System (ADS)

Vaughan, D. G.; Ice2sea Consortium

2009-04-01

The melting of continental ice (glaciers, ice caps and ice sheets) is a substantial source of current sea-level rise, and one that is accelerating more rapidly than was predicted even a few years ago. Indeed, the most recent report from Intergovernmental Panel on Climate Change highlighted that the uncertainty in projections of future sea-level rise is dominated by uncertainty concerning continental ice, and that understanding of the key processes that will lead to loss of continental ice must be improved before reliable projections of sea-level rise can be produced. Such projections are urgently required for effective sea-defence management and coastal adaptation planning. Ice2sea is a consortium of European institutes and international partners seeking European funding to support an integrated scientific programme to improve understanding concerning the future glacial contribution to sea-level rise. This includes improving understanding of the processes that control, past, current and future sea-level rise, and generation of improved estimates of the contribution of glacial components to sea-level rise over the next 200 years. The programme will include targeted studies of key processes in mountain glacier systems and ice caps (e.g. Svalbard), and in ice sheets in both polar regions (Greenland and Antarctica) to improve understanding of how these systems will respond to future climate change. It will include fieldwork and remote sensing studies, and develop a suite of new, cross-validated glacier and ice-sheet model. Ice2sea will deliver these results in forms accessible to scientists, policy-makers and the general public, which will include clear presentations of the sources of uncertainty. Our aim is both, to provide improved projections of the glacial contribution to sea-level rise, and to leave a legacy of improved tools and techniques that will form the basis of ongoing refinements in sea-level projection. Ice2sea will provide exciting opportunities for many early-career glaciologists and ice-modellers in a variety of host institutes.
Future directions for LDEF ionizing radiation modeling and assessments

NASA Technical Reports Server (NTRS)

Armstrong, T. W.; Colborn, B. L.

1992-01-01

Data from the ionizing radiation dosimetry aboard LDEF provide a unique opportunity for assessing the accuracy of current space radiation models and in identifying needed improvements for future mission applications. Details are given of the LDEF data available for radiation model evaluations. The status is given of model comparisons with LDEF data, along with future directions of planned modeling efforts and data comparison assessments. The methodology is outlined which is related to modeling being used to help insure that the LDEF ionizing radiation results can be used to address ionizing radiation issues for future missions. In general, the LDEF radiation modeling has emphasized quick-look predictions using simplified methods to make comparisons with absorbed dose measurements and induced radioactivity measurements of emissions. Modeling and LDEF data comparisons related to linear energy transfer spectra are of importance for several reasons which are outlined. The planned modeling and LDEF data comparisons for LET spectra is discussed, including components of the LET spectra due to different environment sources, contribution from different production mechanisms, and spectra in plastic detectors vs silicon.
Sentinel site data for model improvement – Definition and characterization

USDA-ARS?s Scientific Manuscript database

Crop models are increasingly being used to assess the impacts of future climate change on production and food security. High quality site-specific data on weather, soils, management, and cultivar are needed for those model applications. Also important, is that model development, evaluation, improvem...
Are implicit policy assumptions about climate adaptation trying to push drinking water utilities down an impossible path?

NASA Astrophysics Data System (ADS)

Klasic, M. R.; Ekstrom, J.; Bedsworth, L. W.; Baker, Z.

2017-12-01

Extreme events such as wildfires, droughts, and flooding are projected to be more frequent and intense under a changing climate, increasing challenges to water quality management. To protect and improve public health, drinking water utility managers need to understand and plan for climate change and extreme events. This three year study began with the assumption that improved climate projections were key to advancing climate adaptation at the local level. Through a survey (N = 259) and interviews (N = 61) with California drinking water utility managers during the peak of the state's recent drought, we found that scientific information was not a key barrier hindering adaptation. Instead, we found that managers fell into three distinct mental models based on their interaction with, perceptions, and attitudes, towards scientific information and the future of water in their system. One of the mental models, "modeled futures", is a concept most in line with how climate change scientists talk about the use of information. Drinking water utilities falling into the "modeled future" category tend to be larger systems that have adequate capacity to both receive and use scientific information. Medium and smaller utilities in California, that more often serve rural low income communities, tend to fall into the other two mental models, "whose future" and "no future". We show evidence that there is an implicit presumption that all drinking water utility managers should strive to align with "modeled future" mental models. This presentation questions this assumption as it leaves behind many utilities that need to adapt to climate change (several thousand in California alone), but may not have the technical, financial, managerial, or other capacity to do so. It is clear that no single solution or pathway to drought resilience exists for water utilities, but we argue that a more explicit understanding and definition of what it means to be a resilient drinking water utility is necessary. By highlighting, then questioning, the assumption that all utility managers should strive to have "modeled future" mentalities, this presentation seeks to foster an open dialogue around which pathway or pathways are most feasible for supporting drinking water utility managers planning for climate change.
Why System Safety Professionals Should Read Accident Reports

NASA Technical Reports Server (NTRS)

Holloway, C. M.; Johnson, C. W.

2006-01-01

System safety professionals, both researchers and practitioners, who regularly read accident reports reap important benefits. These benefits include an improved ability to separate myths from reality, including both myths about specific accidents and ones concerning accidents in general; an increased understanding of the consequences of unlikely events, which can help inform future designs; a greater recognition of the limits of mathematical models; and guidance on potentially relevant research directions that may contribute to safety improvements in future systems.
Global Health Impacts of Future Aviation Emissions Under Alternative Control Scenarios

PubMed Central

2015-01-01

There is strong evidence of an association between fine particulate matter less than 2.5 μm (PM2.5) in aerodynamic diameter and adverse health outcomes. This study analyzes the global excess mortality attributable to the aviation sector in the present (2006) and in the future (three 2050 scenarios) using the integrated exposure response model that was also used in the 2010 Global Burden of Disease assessment. The PM2.5 concentrations for the present and future scenarios were calculated using aviation emission inventories developed by the Volpe National Transportation Systems Center and a global chemistry-climate model. We found that while excess mortality due to the aviation sector emissions is greater in 2050 compared to 2006, improved fuel policies (technology and operations improvements yielding smaller increases in fuel burn compared to 2006, and conversion to fully sustainable fuels) in 2050 could lead to 72% fewer deaths for adults 25 years and older than a 2050 scenario with no fuel improvements. Among the four health outcomes examined, ischemic heart disease was the greatest cause of death. Our results suggest that implementation of improved fuel policies can have substantial human health benefits. PMID:25412200
Global health impacts of future aviation emissions under alternative control scenarios.

PubMed

Morita, Haruka; Yang, Suijia; Unger, Nadine; Kinney, Patrick L

2014-12-16

There is strong evidence of an association between fine particulate matter less than 2.5 μm (PM2.5) in aerodynamic diameter and adverse health outcomes. This study analyzes the global excess mortality attributable to the aviation sector in the present (2006) and in the future (three 2050 scenarios) using the integrated exposure response model that was also used in the 2010 Global Burden of Disease assessment. The PM2.5 concentrations for the present and future scenarios were calculated using aviation emission inventories developed by the Volpe National Transportation Systems Center and a global chemistry-climate model. We found that while excess mortality due to the aviation sector emissions is greater in 2050 compared to 2006, improved fuel policies (technology and operations improvements yielding smaller increases in fuel burn compared to 2006, and conversion to fully sustainable fuels) in 2050 could lead to 72% fewer deaths for adults 25 years and older than a 2050 scenario with no fuel improvements. Among the four health outcomes examined, ischemic heart disease was the greatest cause of death. Our results suggest that implementation of improved fuel policies can have substantial human health benefits.
Emissions from international shipping: 2. Impact of future technologies on scenarios until 2050

NASA Astrophysics Data System (ADS)

Eyring, V.; KöHler, H. W.; Lauer, A.; Lemper, B.

2005-09-01

In this study the today's fleet-average emission factors of the most important ship exhausts are used to calculate emission scenarios for the future. To develop plausible future technology scenarios, first upcoming regulations and compliance with future regulations through technological improvements are discussed. We present geographically resolved emission inventory scenarios until 2050, based on a mid-term prognosis for 2020 and a long-term prognosis for 2050. The scenarios are based on some very strict assumptions on future ship traffic demands and technological improvements. The four future ship traffic demand scenarios are mainly determined by the economic growth, which follows the IPCC SRES storylines. The resulting fuel consumption is projected through extrapolations of historical trends in economic growth, total seaborne trade and number of ships, as well as the average installed power per ship. For the future technology scenarios we assume a diesel-only fleet in 2020 resulting in fuel consumption between 382 and 409 million metric tons (Mt). For 2050 one technology scenario assumes that 25% of the fuel consumed by a diesel-only fleet can be saved by applying future alternative propulsion plants, resulting in a fuel consumption that varies between 402 and 543 Mt. The other scenario is a business-as-usual scenario for a diesel-only fleet even in 2050 and gives an estimate between 536 and 725 Mt. Dependent on how rapid technology improvements for diesel engines are introduced, possible technology reduction factors are applied to the today's fleet-average emission factors of all important species to estimate future ship emissions. Combining the four traffic demand scenarios with the four technology scenarios, our results suggest emissions between 8.8 and 25.0 Tg (NO2) in 2020, and between 3.1 to 38.8 Tg (NO2) in 2050. The development of forecast scenarios for CO2, NOx, SOx, CO, hydrocarbons, and particulate matter is driven by the requirements for global model studies of the effects of these emissions on the chemical composition of the atmosphere and on climate. The developed scenarios are suitable for use as input for chemical transport models (CTMs) and coupled chemistry-climate models (CCMs).
Optimizing future imaging survey of galaxies to confront dark energy and modified gravity models

NASA Astrophysics Data System (ADS)

Yamamoto, Kazuhiro; Parkinson, David; Hamana, Takashi; Nichol, Robert C.; Suto, Yasushi

2007-07-01

We consider the extent to which future imaging surveys of galaxies can distinguish between dark energy and modified gravity models for the origin of the cosmic acceleration. Dynamical dark energy models may have similar expansion rates as models of modified gravity, yet predict different growth of structure histories. We parametrize the cosmic expansion by the two parameters, w0 and wa, and the linear growth rate of density fluctuations by Linder’s γ, independently. Dark energy models generically predict γ≈0.55, while the Dvali-Gabadadze-Porrati (DGP) model γ≈0.68. To determine if future imaging surveys can constrain γ within 20% (or Δγ<0.1), we perform the Fisher matrix analysis for a weak-lensing survey such as the ongoing Hyper Suprime-Cam (HSC) project. Under the condition that the total observation time is fixed, we compute the figure of merit (FoM) as a function of the exposure time texp. We find that the tomography technique effectively improves the FoM, which has a broad peak around texp≃several˜10min; a shallow and wide survey is preferred to constrain the γ parameter. While Δγ<0.1 cannot be achieved by the HSC weak-lensing survey alone, one can improve the constraints by combining with a follow-up spectroscopic survey like Wide-field Fiber-fed Multi-Object Spectrograph (WFMOS) and/or future cosmic microwave background (CMB) observations.
Drought, Fire and Insects in Western US Forests: Observations to Improve Regional Land System Modeling

NASA Astrophysics Data System (ADS)

Law, B. E.; Yang, Z.; Berner, L. T.; Hicke, J. A.; Buotte, P.; Hudiburg, T. W.

2015-12-01

Drought, fire and insects are major disturbances in the western US, and conditions are expected to get warmer and drier in the future. We combine multi-scale observations and modeling with CLM4.5 to examine the effects of these disturbances on forests in the western US. We modified the Community Land Model, CLM4.5, to improve simulated drought-related mortality in forests, and prediction of insect outbreaks under future climate conditions. We examined differences in plant traits that represent species variation in sensitivity to drought, and redefined plant groupings in PFTs. Plant traits, including sapwood area: leaf area ratio and stemwood density were strongly correlated with water availability during the ecohydrologic year. Our database of co-located observations of traits for 30 tree species was used to produce parameterization of the model by species groupings according to similar traits. Burn area predicted by the new fire model in CLM4.5 compares well with recent years of GFED data, but has a positive bias compared with Landsat-based MTBS. Biomass mortality over recent decades increased, and was captured well by the model in general, but missed mortality trends of some species. Comparisons with AmeriFlux data showed that the model with dynamic tree mortality only (no species trait improvements) overestimated GPP in dry years compared with flux data at semi-arid sites, and underestimated GPP at more mesic sites that experience dry summers. Simulations with both dynamic tree mortality and species trait parameters improved estimates of GPP by 17-22%; differences between predicted and observed NEE were larger. Future projections show higher productivity from increased atmospheric CO2 and warming that somewhat offsets drought and fire effects over the next few decades. Challenges include representation of hydraulic failure in models, and availability of species trait and carbon/water process data in disturbance- and drought-impacted regions.
Past, Present, and Future Capabilities of the Transonic Dynamics Tunnel from an Aeroelasticity Perspective

NASA Technical Reports Server (NTRS)

Cole, Stanley R.; Garcia, Jerry L.

2000-01-01

The NASA Langley Transonic Dynamics Tunnel (TDT) has provided a unique capability for aeroelastic testing for forty years. The facility has a rich history of significant contributions to the design of many United States commercial transports, military aircraft, launch vehicles, and spacecraft. The facility has many features that contribute to its uniqueness for aeroelasticity testing, perhaps the most important feature being the use of a heavy gas test medium to achieve higher test densities. Higher test medium densities substantially improve model-building requirements and therefore simplify the fabrication process for building aeroelastically scaled wind tunnel models. Aeroelastic scaling for the heavy gas results in lower model structural frequencies. Lower model frequencies tend to a make aeroelastic testing safer. This paper will describe major developments in the testing capabilities at the TDT throughout its history, the current status of the facility, and planned additions and improvements to its capabilities in the near future.

NASA Workshop on future directions in surface modeling and grid generation

NASA Technical Reports Server (NTRS)

Vandalsem, W. R.; Smith, R. E.; Choo, Y. K.; Birckelbaw, L. D.; Vogel, A. A.

1992-01-01

Given here is a summary of the paper sessions and panel discussions of the NASA Workshop on Future Directions in Surface Modeling and Grid Generation held a NASA Ames Research Center, Moffett Field, California, December 5-7, 1989. The purpose was to assess U.S. capabilities in surface modeling and grid generation and take steps to improve the focus and pace of these disciplines within NASA. The organization of the workshop centered around overviews from NASA centers and expert presentations from U.S. corporations and universities. Small discussion groups were held and summarized by group leaders. Brief overviews and a panel discussion by representatives from the DoD were held, and a NASA-only session concluded the meeting. In the NASA Program Planning Session summary there are five recommended steps for NASA to take to improve the development and application of surface modeling and grid generation.
Robust predictive cruise control for commercial vehicles

NASA Astrophysics Data System (ADS)

Junell, Jaime; Tumer, Kagan

2013-10-01

In this paper we explore learning-based predictive cruise control and the impact of this technology on increasing fuel efficiency for commercial trucks. Traditional cruise control is wasteful when maintaining a constant velocity over rolling hills. Predictive cruise control (PCC) is able to look ahead at future road conditions and solve for a cost-effective course of action. Model- based controllers have been implemented in this field but cannot accommodate many complexities of a dynamic environment which includes changing road and vehicle conditions. In this work, we focus on incorporating a learner into an already successful model- based predictive cruise controller in order to improve its performance. We explore back propagating neural networks to predict future errors then take actions to prevent said errors from occurring. The results show that this approach improves the model based PCC by up to 60% under certain conditions. In addition, we explore the benefits of classifier ensembles to further improve the gains due to intelligent cruise control.
SMRT: A new, modular snow microwave radiative transfer model

NASA Astrophysics Data System (ADS)

Picard, Ghislain; Sandells, Melody; Löwe, Henning; Dumont, Marie; Essery, Richard; Floury, Nicolas; Kontu, Anna; Lemmetyinen, Juha; Maslanka, William; Mätzler, Christian; Morin, Samuel; Wiesmann, Andreas

2017-04-01

Forward models of radiative transfer processes are needed to interpret remote sensing data and derive measurements of snow properties such as snow mass. A key requirement and challenge for microwave emission and scattering models is an accurate description of the snow microstructure. The snow microwave radiative transfer model (SMRT) was designed to cater for potential future active and/or passive satellite missions and developed to improve understanding of how to parameterize snow microstructure. SMRT is implemented in Python and is modular to allow easy intercomparison of different theoretical approaches. Separate modules are included for the snow microstructure model, electromagnetic module, radiative transfer solver, substrate, interface reflectivities, atmosphere and permittivities. An object-oriented approach is used with carefully specified exchanges between modules to allow future extensibility i.e. without constraining the parameter list requirements. This presentation illustrates the capabilities of SMRT. At present, five different snow microstructure models have been implemented, and direct insertion of the autocorrelation function from microtomography data is also foreseen with SMRT. Three electromagnetic modules are currently available. While DMRT-QCA and Rayleigh models need specific microstructure models, the Improved Born Approximation may be used with any microstructure representation. A discrete ordinates approach with stream connection is used to solve the radiative transfer equations, although future inclusion of 6-flux and 2-flux solvers are envisioned. Wrappers have been included to allow existing microwave emission models (MEMLS, HUT, DMRT-QMS) to be run with the same inputs and minimal extra code (2 lines). Comparisons between theoretical approaches will be shown, and evaluation against field experiments in the frequency range 5-150 GHz. SMRT is simple and elegant to use whilst providing a framework for future development within the community.
A unified probabilistic approach to improve spelling in an event-related potential-based brain-computer interface.

PubMed

Kindermans, Pieter-Jan; Verschore, Hannes; Schrauwen, Benjamin

2013-10-01

In recent years, in an attempt to maximize performance, machine learning approaches for event-related potential (ERP) spelling have become more and more complex. In this paper, we have taken a step back as we wanted to improve the performance without building an overly complex model, that cannot be used by the community. Our research resulted in a unified probabilistic model for ERP spelling, which is based on only three assumptions and incorporates language information. On top of that, the probabilistic nature of our classifier yields a natural dynamic stopping strategy. Furthermore, our method uses the same parameters across 25 subjects from three different datasets. We show that our classifier, when enhanced with language models and dynamic stopping, improves the spelling speed and accuracy drastically. Additionally, we would like to point out that as our model is entirely probabilistic, it can easily be used as the foundation for complex systems in future work. All our experiments are executed on publicly available datasets to allow for future comparison with similar techniques.
Multiscale Modeling, Simulation and Visualization and Their Potential for Future Aerospace Systems

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Compiler)

2002-01-01

This document contains the proceedings of the Training Workshop on Multiscale Modeling, Simulation and Visualization and Their Potential for Future Aerospace Systems held at NASA Langley Research Center, Hampton, Virginia, March 5 - 6, 2002. The workshop was jointly sponsored by Old Dominion University's Center for Advanced Engineering Environments and NASA. Workshop attendees were from NASA, other government agencies, industry, and universities. The objectives of the workshop were to give overviews of the diverse activities in hierarchical approach to material modeling from continuum to atomistics; applications of multiscale modeling to advanced and improved material synthesis; defects, dislocations, and material deformation; fracture and friction; thin-film growth; characterization at nano and micro scales; and, verification and validation of numerical simulations, and to identify their potential for future aerospace systems.
TOWARDS AN IMPROVED UNDERSTANDING OF SIMULATED AND OBSERVED CHANGES IN EXTREME PRECIPITATION

EPA Science Inventory

The evaluation of climate model precipitation is expected to reveal biases in simulated mean and extreme precipitation which may be a result of coarse model resolution or inefficiencies in the precipitation generating mechanisms in models. The analysis of future extreme precip...
Improved LTVMPC design for steering control of autonomous vehicle

NASA Astrophysics Data System (ADS)

Velhal, Shridhar; Thomas, Susy

2017-01-01

An improved linear time varying model predictive control for steering control of autonomous vehicle running on slippery road is presented. Control strategy is designed such that the vehicle will follow the predefined trajectory with highest possible entry speed. In linear time varying model predictive control, nonlinear vehicle model is successively linearized at each sampling instant. This linear time varying model is used to design MPC which will predict the future horizon. By incorporating predicted input horizon in each successive linearization the effectiveness of controller has been improved. The tracking performance using steering with front wheel and braking at four wheels are presented to illustrate the effectiveness of the proposed method.
Preparing systems engineering and computing science students in disciplined methods, quantitative, and advanced statistical techniques to improve process performance

NASA Astrophysics Data System (ADS)

McCray, Wilmon Wil L., Jr.

The research was prompted by a need to conduct a study that assesses process improvement, quality management and analytical techniques taught to students in U.S. colleges and universities undergraduate and graduate systems engineering and the computing science discipline (e.g., software engineering, computer science, and information technology) degree programs during their academic training that can be applied to quantitatively manage processes for performance. Everyone involved in executing repeatable processes in the software and systems development lifecycle processes needs to become familiar with the concepts of quantitative management, statistical thinking, process improvement methods and how they relate to process-performance. Organizations are starting to embrace the de facto Software Engineering Institute (SEI) Capability Maturity Model Integration (CMMI RTM) Models as process improvement frameworks to improve business processes performance. High maturity process areas in the CMMI model imply the use of analytical, statistical, quantitative management techniques, and process performance modeling to identify and eliminate sources of variation, continually improve process-performance; reduce cost and predict future outcomes. The research study identifies and provides a detail discussion of the gap analysis findings of process improvement and quantitative analysis techniques taught in U.S. universities systems engineering and computing science degree programs, gaps that exist in the literature, and a comparison analysis which identifies the gaps that exist between the SEI's "healthy ingredients " of a process performance model and courses taught in U.S. universities degree program. The research also heightens awareness that academicians have conducted little research on applicable statistics and quantitative techniques that can be used to demonstrate high maturity as implied in the CMMI models. The research also includes a Monte Carlo simulation optimization model and dashboard that demonstrates the use of statistical methods, statistical process control, sensitivity analysis, quantitative and optimization techniques to establish a baseline and predict future customer satisfaction index scores (outcomes). The American Customer Satisfaction Index (ACSI) model and industry benchmarks were used as a framework for the simulation model.
Performance improvement and implementation science: infection prevention competencies for current and future role development.

PubMed

Hanchett, Marilyn

2012-05-01

The Association for Professionals in Infection Control and Epidemiology, Inc, developed its first model of infection preventionist (IP) competency in 2011. The model is based on the principles of patient safety, professional and practice standards, and core competencies identified through research conducted by the Certification Board of Infection Control and Epidemiology, Inc. In addition, the model highlights 4 domains that are predicted to be key areas for future competency development. Performance improvement (PI) and implementation represent 1 of the 4 forward-focused domains. Concurrently, the inclusion of implementation science (IS) in the competency model is consistent with the research goals established by the Association for Professionals in Infection Control and Epidemiology, Inc, in its 2020 strategic plan. This article explains the importance of PI and IS and describes their relevance to the current and future IP role development. Significant challenges such as role delineation and compression are discussed. The need for the IP to acquire new competencies at integrating, as well as differentiating, PI and IS are explored in terms of emerging issues and trends. Copyright © 2012 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Mosby, Inc. All rights reserved.
Four decades of modeling methane cycling in terrestrial ecosystems: Where we are heading?

NASA Astrophysics Data System (ADS)

Xu, X.; Yuan, F.; Hanson, P. J.; Wullschleger, S. D.; Thornton, P. E.; Tian, H.; Riley, W. J.; Song, X.; Graham, D. E.; Song, C.

2015-12-01

A modeling approach to methane (CH4) is widely used to quantify the budget, investigate spatial and temporal variabilities, and understand the mechanistic processes and environmental controls on CH4 fluxes across spatial and temporal scales. Moreover, CH4 models are an important tool for integrating CH4 data from multiple sources, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. We reviewed 39 terrestrial CH4 models to characterize their strengths and weaknesses and to design a roadmap for future model improvement and application. We found that: (1) the focus of CH4 models have been shifted from theoretical to site- to regional-level application over the past four decades, expressed as dramatic increases in CH4 model development on regional budget quantification; (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls; (3) significant data-model and model-model mismatches are partially attributed to different representations of wetland characterization and inundation dynamics. Three efforts should be paid special attention for future improvements and applications of fully mechanistic CH4 models: (1) CH4 models should be improved to represent the mechanisms underlying land-atmosphere CH4 exchange, with emphasis on improving and validating individual CH4 processes over depth and horizontal space; (2) models should be developed that are capable of simulating CH4 fluxes across space and time (particularly hot moments and hot spots); (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. A newly developed microbial functional group-based CH4 model (CLM-Microbe) was further used to demonstrate the features of mechanistic representation and integration with multiple source of observational datasets.
The mutual causality analysis between the stock and futures markets

NASA Astrophysics Data System (ADS)

Yao, Can-Zhong; Lin, Qing-Wen

2017-07-01

In this paper we employ the conditional Granger causality model to estimate the information flow, and find that the improved model outperforms the Granger causality model in revealing the asymmetric correlation between stocks and futures in the Chinese market. First, we find that information flows estimated by Granger causality tests from futures to stocks are greater than those from stocks to futures. Additionally, average correlation coefficients capture some important characteristics between stock prices and information flows over time. Further, we find that direct information flows estimated by conditional Granger causality tests from stocks to futures are greater than those from futures to stocks. Besides, the substantial increases of information flows and direct information flows exhibit a certain degree of synchronism with the occurrences of important events. Finally, the comparative analysis with the asymmetric ratio and the bootstrap technique demonstrates the slight asymmetry of information flows and the significant asymmetry of direct information flows. It reveals that the information flows from futures to stocks are slightly greater than those in the reverse direction, while the direct information flows from stocks to futures are significantly greater than those in the reverse direction.
Impact of geophysical model error for recovering temporal gravity field model

NASA Astrophysics Data System (ADS)

Zhou, Hao; Luo, Zhicai; Wu, Yihao; Li, Qiong; Xu, Chuang

2016-07-01

The impact of geophysical model error on recovered temporal gravity field models with both real and simulated GRACE observations is assessed in this paper. With real GRACE observations, we build four temporal gravity field models, i.e., HUST08a, HUST11a, HUST04 and HUST05. HUST08a and HUST11a are derived from different ocean tide models (EOT08a and EOT11a), while HUST04 and HUST05 are derived from different non-tidal models (AOD RL04 and AOD RL05). The statistical result shows that the discrepancies of the annual mass variability amplitudes in six river basins between HUST08a and HUST11a models, HUST04 and HUST05 models are all smaller than 1 cm, which demonstrates that geophysical model error slightly affects the current GRACE solutions. The impact of geophysical model error for future missions with more accurate satellite ranging is also assessed by simulation. The simulation results indicate that for current mission with range rate accuracy of 2.5 × 10- 7 m/s, observation error is the main reason for stripe error. However, when the range rate accuracy improves to 5.0 × 10- 8 m/s in the future mission, geophysical model error will be the main source for stripe error, which will limit the accuracy and spatial resolution of temporal gravity model. Therefore, observation error should be the primary error source taken into account at current range rate accuracy level, while more attention should be paid to improving the accuracy of background geophysical models for the future mission.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Cort, K. A.; Hostick, D. J.; Belzer, D. B.

This report compiles information and conclusions gathered as part of the “Modeling EERE Deployment Programs” project. The purpose of the project was to identify and characterize the modeling of deployment programs within the EERE Technology Development (TD) programs, address possible improvements to the modeling process, and note gaps in knowledge in which future research is needed.
INITIAL STUDY OF HPAC MODELED DISPERSION DRIVEN BY MM5 WITH AND WITHOUT URBAN CANOPY PARAMETERIZATIONS

EPA Science Inventory

Improving the accuracy and capability of transport and dispersion models in urban areas is essential for current and future urban applications. These models must reflect more realistically the presence and details of urban canopy features. Such features markedly influence the flo...
Chemistry-Climate Models of the Stratosphere

NASA Technical Reports Server (NTRS)

Austin, J.; Shindell, D.; Bruehl, C.; Dameris, M.; Manzini, E.; Nagashima, T.; Newman, P.; Pawson, S.; Pitari, G.; Rozanov, E.;

2001-01-01

Over the last decade, improved computer power has allowed three-dimensional models of the stratosphere to be developed that can be used to simulate polar ozone levels over long periods. This paper compares the meteorology between these models, and discusses the future of polar ozone levels over the next 50 years.

How Well Does LCA Model Land Use Impacts on Biodiversity?--A Comparison with Approaches from Ecology and Conservation.

PubMed

Curran, Michael; de Souza, Danielle Maia; Antón, Assumpció; Teixeira, Ricardo F M; Michelsen, Ottar; Vidal-Legaz, Beatriz; Sala, Serenella; Milà i Canals, Llorenç

2016-03-15

The modeling of land use impacts on biodiversity is considered a priority in life cycle assessment (LCA). Many diverging approaches have been proposed in an expanding literature on the topic. The UNEP/SETAC Life Cycle Initiative is engaged in building consensus on a shared modeling framework to highlight best-practice and guide model application by practitioners. In this paper, we evaluated the performance of 31 models from both the LCA and the ecology/conservation literature (20 from LCA, 11 from non-LCA fields) according to a set of criteria reflecting (i) model completeness, (ii) biodiversity representation, (iii) impact pathway coverage, (iv) scientific quality, and (v) stakeholder acceptance. We show that LCA models tend to perform worse than those from ecology and conservation (although not significantly), implying room for improvement. We identify seven best-practice recommendations that can be implemented immediately to improve LCA models based on existing approaches in the literature. We further propose building a "consensus model" through weighted averaging of existing information, to complement future development. While our research focuses on conceptual model design, further quantitative comparison of promising models in shared case studies is an essential prerequisite for future informed model choice.
Future nutrient load scenarios for the Baltic Sea due to climate and lifestyle changes.

PubMed

Hägg, Hanna Eriksson; Lyon, Steve W; Wällstedt, Teresia; Mörth, Carl-Magnus; Claremar, Björn; Humborg, Christoph

2014-04-01

Dynamic model simulations of the future climate and projections of future lifestyles within the Baltic Sea Drainage Basin (BSDB) were considered in this study to estimate potential trends in future nutrient loads to the Baltic Sea. Total nitrogen and total phosphorus loads were estimated using a simple proxy based only on human population (to account for nutrient sources) and stream discharges (to account for nutrient transport). This population-discharge proxy provided a good estimate for nutrient loads across the seven sub-basins of the BSDB considered. All climate scenarios considered here produced increased nutrient loads to the Baltic Sea over the next 100 years. There was variation between the climate scenarios such that sub-basin and regional differences were seen in future nutrient runoff depending on the climate model and scenario considered. Regardless, the results of this study indicate that changes in lifestyle brought about through shifts in consumption and population potentially overshadow the climate effects on future nutrient runoff for the entire BSDB. Regionally, however, lifestyle changes appear relatively more important in the southern regions of the BSDB while climatic changes appear more important in the northern regions with regards to future increases in nutrient loads. From a whole-ecosystem management perspective of the BSDB, this implies that implementation of improved and targeted management practices can still bring about improved conditions in the Baltic Sea in the face of a warmer and wetter future climate.
Improving Aerosol and Visibility Forecasting Capabilities Using Current and Future Generations of Satellite Observations

DTIC Science & Technology

2015-08-27

and 2) preparing for the post-MODIS/MISR era using the Geostationary Operational Environmental Satellite (GOES). 3. Improve model representations of...meteorological property retrievals. In this study, using collocated data from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Geostationary
The past, present, and future of urgent matters: lessons learned from a decade of emergency department flow improvement.

PubMed

McClelland, Mark Stephen; Lazar, Danielle; Sears, Vickie; Wilson, Marcia; Siegel, Bruce; Pines, Jesse M

2011-12-01

Over the past decade, emergency departments (ED) have encountered major challenges due to increased crowding and a greater public focus on quality measurement and quality improvement. Responding to these challenges, many EDs have worked to improve their processes and develop new and innovative models of care delivery. Urgent Matters has contributed to ED quality and patient flow improvement by working with hospitals throughout the United States. Recognizing that EDs across the country are struggling with many of the same issues, Urgent Matters-a program funded by the Robert Wood Johnson Foundation (RWJF)-has sought to identify, develop, and disseminate innovative approaches, interventions, and models to improve ED flow and quality. Using a variety of techniques, such as learning networks (collaboratives), national conferences, e-newsletters, webinars, best practices toolkits, and social media, Urgent Matters has served as a thought leader and innovator in ED quality improvement initiatives. The Urgent Matters Seven Success Factors were drawn from the early work done by program participants and propose practical guidelines for implementing and sustaining ED improvement activities. This article chronicles the history, activities, lessons learned, and future of the Urgent Matters program. © 2011 by the Society for Academic Emergency Medicine.
Ocean waves from tropical cyclones in the Gulf of Mexico and the effect of climate change

NASA Astrophysics Data System (ADS)

Appendini, C. M.; Pedrozo-Acuña, A.; Meza-Padilla, R.; Torres-Freyermuth, A.; Cerezo-Mota, R.; López-González, J.

2016-12-01

To generate projections of wave climate associated to tropical cyclones is a challenge due to their short historical record of events, their low occurrence, and the poor wind field resolution in General Circulation Models. Synthetic tropical cyclones provide an alternative to overcome such limitations, improving robust statistics under present and future climates. We use synthetic events to characterize present and future wave climate associated with tropical cyclones in the Gulf of Mexico. The NCEP/NCAR atmospheric reanalysis and the Coupled Model Intercomparison Project Phase 5 models NOAA/GFDL CM3 and UK Met Office HADGEM2-ES, were used to derive present and future wave climate under RCPs 4.5 and 8.5. The results suggest an increase in wave activity for the future climate, particularly for the GFDL model that shows less bias in the present climate, although some areas are expected to decrease the wave energy. The practical implications of determining the future wave climate is exemplified by means of the 100-year design wave, where the use of the present climate may result in under/over design of structures, since the lifespan of a structure includes the future wave climate period.

The High Cost of Low Educational Performance: The Long-Run Economic Impact of Improving PISA Outcomes

ERIC Educational Resources Information Center

Hanushek, Eric A.; Woessmann, Ludger

2010-01-01

While many nations express a commitment to improved educational quality, education often slips down on the policy agenda. Because the benefits of educational investments are seen only in the future, it is possible to underestimate the value and the importance of improvements. This report uses recent economic modelling to relate cognitive…
Impact and cost-effectiveness of current and future tuberculosis diagnostics: the contribution of modelling

PubMed Central

Houben, R.; Cohen, T.; Pai, M.; Cobelens, F.; Vassall, A.; Menzies, N. A.; Gomez, G. B.; Langley, I.; Squire, S. B.; White, R.

2014-01-01

SUMMARY The landscape of diagnostic testing for tuberculosis (TB) is changing rapidly, and stakeholders need urgent guidance on how to develop, deploy and optimize TB diagnostics in a way that maximizes impact and makes best use of available resources. When decisions must be made with only incomplete or preliminary data available, modelling is a useful tool for providing such guidance. Following a meeting of modelers and other key stakeholders organized by the TB Modelling and Analysis Consortium, we propose a conceptual framework for positioning models of TB diagnostics. We use that framework to describe modelling priorities in four key areas: Xpert® MTB/RIF scale-up, target product profiles for novel assays, drug susceptibility testing to support new drug regimens, and the improvement of future TB diagnostic models. If we are to maximize the impact and cost-effectiveness of TB diagnostics, these modelling priorities should figure prominently as targets for future research. PMID:25189546
Improving Localization Accuracy: Successive Measurements Error Modeling

PubMed Central

Abu Ali, Najah; Abu-Elkheir, Mervat

2015-01-01

Vehicle self-localization is an essential requirement for many of the safety applications envisioned for vehicular networks. The mathematical models used in current vehicular localization schemes focus on modeling the localization error itself, and overlook the potential correlation between successive localization measurement errors. In this paper, we first investigate the existence of correlation between successive positioning measurements, and then incorporate this correlation into the modeling positioning error. We use the Yule Walker equations to determine the degree of correlation between a vehicle’s future position and its past positions, and then propose a p-order Gauss–Markov model to predict the future position of a vehicle from its past p positions. We investigate the existence of correlation for two datasets representing the mobility traces of two vehicles over a period of time. We prove the existence of correlation between successive measurements in the two datasets, and show that the time correlation between measurements can have a value up to four minutes. Through simulations, we validate the robustness of our model and show that it is possible to use the first-order Gauss–Markov model, which has the least complexity, and still maintain an accurate estimation of a vehicle’s future location over time using only its current position. Our model can assist in providing better modeling of positioning errors and can be used as a prediction tool to improve the performance of classical localization algorithms such as the Kalman filter. PMID:26140345
The accuracy of climate models' simulated season lengths and the effectiveness of grid scale correction factors

DOE PAGES

Winterhalter, Wade E.

2011-09-01

Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I foundmore » that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.« less
Combustion system CFD modeling at GE Aircraft Engines

NASA Technical Reports Server (NTRS)

Burrus, D.; Mongia, H.; Tolpadi, Anil K.; Correa, S.; Braaten, M.

1995-01-01

This viewgraph presentation discusses key features of current combustion system CFD modeling capabilities at GE Aircraft Engines provided by the CONCERT code; CONCERT development history; modeling applied for designing engine combustion systems; modeling applied to improve fundamental understanding; CONCERT3D results for current production combustors; CONCERT3D model of NASA/GE E3 combustor; HYBRID CONCERT CFD/Monte-Carlo modeling approach; and future modeling directions.
Combustion system CFD modeling at GE Aircraft Engines

NASA Astrophysics Data System (ADS)

Burrus, D.; Mongia, H.; Tolpadi, Anil K.; Correa, S.; Braaten, M.

1995-03-01

This viewgraph presentation discusses key features of current combustion system CFD modeling capabilities at GE Aircraft Engines provided by the CONCERT code; CONCERT development history; modeling applied for designing engine combustion systems; modeling applied to improve fundamental understanding; CONCERT3D results for current production combustors; CONCERT3D model of NASA/GE E3 combustor; HYBRID CONCERT CFD/Monte-Carlo modeling approach; and future modeling directions.
Quantifying the intra-annual uncertainties in climate change assessment over 10 sub-basins across the Pacific Northwest US

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Moradkhani, Hamid; Rana, Arun

2017-04-01

Uncertainty is an inevitable feature of climate change impact assessments. Understanding and quantifying different sources of uncertainty is of high importance, which can help modeling agencies improve the current models and scenarios. In this study, we have assessed the future changes in three climate variables (i.e. precipitation, maximum temperature, and minimum temperature) over 10 sub-basins across the Pacific Northwest US. To conduct the study, 10 statistically downscaled CMIP5 GCMs from two downscaling methods (i.e. BCSD and MACA) were utilized at 1/16 degree spatial resolution for the historical period of 1970-2000 and future period of 2010-2099. For the future projections, two future scenarios of RCP4.5 and RCP8.5 were used. Furthermore, Bayesian Model Averaging (BMA) was employed to develop a probabilistic future projection for each climate variable. Results indicate superiority of BMA simulations compared to individual models. Increasing temperature and precipitation are projected at annual timescale. However, the changes are not uniform among different seasons. Model uncertainty shows to be the major source of uncertainty, while downscaling uncertainty significantly contributes to the total uncertainty, especially in summer.
New temperature model of the Netherlands from new data and novel modelling methodology

NASA Astrophysics Data System (ADS)

Bonté, Damien; Struijk, Maartje; Békési, Eszter; Cloetingh, Sierd; van Wees, Jan-Diederik

2017-04-01

Deep geothermal energy has grown in interest in Western Europe in the last decades, for direct use but also, as the knowledge of the subsurface improves, for electricity generation. In the Netherlands, where the sector took off with the first system in 2005, geothermal energy is seen has a key player for a sustainable future. The knowledge of the temperature subsurface, together with the available flow from the reservoir, is an important factor that can determine the success of a geothermal energy project. To support the development of deep geothermal energy system in the Netherlands, we have made a first assessment of the subsurface temperature based on thermal data but also on geological elements (Bonté et al, 2012). An outcome of this work was ThermoGIS that uses the temperature model. This work is a revision of the model that is used in ThermoGIS. The improvement from the first model are multiple, we have been improving not only the dataset used for the calibration and structural model, but also the methodology trough an improved software (called b3t). The temperature dataset has been updated by integrating temperature on the newly accessible wells. The sedimentary description in the basin has been improved by using an updated and refined structural model and an improved lithological definition. A major improvement in from the methodology used to perform the modelling, with b3t the calibration is made not only using the lithospheric parameters but also using the thermal conductivity of the sediments. The result is a much more accurate definition of the parameters for the model and a perfected handling of the calibration process. The result obtain is a precise and improved temperature model of the Netherlands. The thermal conductivity variation in the sediments associated with geometry of the layers is an important factor of temperature variations and the influence of the Zechtein salt in the north of the country is important. In addition, the radiogenic heat production in the crust shows a significant impact. From the temperature values, also identify in the lower part of the basin, deep convective systems that could be major geothermal energy target in the future.
Improve processes on healthcare: current issues and future trends.

PubMed

Chen, Jason C H; Dolan, Matt; Lin, Binshan

2004-01-01

Information Technology (IT) is a critical resource for improving today's business competitiveness. However, many healthcare providers do not proactively manage or improve the efficiency and effectiveness of their services with IT. Survival in a competitive business environment demands continuous improvements in quality and service, while rigorously maintaining core values. Electronic commerce continues its development, gaining ground as the preferred means of business transactions. Embracing e-healthcare and treating IT as a strategic tool to improve patient safety and the quality of care enables healthcare professionals to benefit from technology formerly used only for management purposes. Numerous improvement initiatives, introduced by both the federal government and the private sector, seek to better the status quo in IT. This paper examines the current IT climate using an enhanced "Built to Last" model, and comments on future IT strategies within the healthcare industry.
GMS-based"Future Time" Rainfall Data Assimilation for Mesoscale Weather Prediction over Korean Peninsula and Future Prospects with GPM Satellite Measurements

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Ou, Mi-Lim

2004-01-01

This study examines the use of satellite-derived nowcasted (short-term forecasted) rainfall over 3-hour time periods to gain an equivalent time increment in initializing a nonhydrostatic mesoscale model used for predicting convective rainfall events over the Korean peninsula. Infrared (IR) window measurements from the Japanese Geostationary Meteorological Satellite (GMS) are used to specify latent heating for a spinup period of the model - but in future time -- thus initializing in advance of actual time in the framework of a prediction scenario. The main scientific objective of the study is to investigate the strengths and weaknesses of this approach insofar as data assimilation, in which the nowcasted assimilation data are derived independently of the prognostic model itself. Although there have been various recent improvements in formulating the dynamics, thermodynamics, and microphysics of mesoscale models, as well as computer advances which allow the use of high resolution cloud-resolving grids and explicit latent heating over regional domains, spinup remains at the forefront of unresolved mesoscale modeling problems. In general, non-realistic spinup limits the skill in predicting the spatial-temporal distribution of convection and precipitation, primarily in the early hours of a. forecast, stemming from standard prognostic variables not representing the initial diabatic heating field produced by the ambient convection and cloud fields. The long-term goal of this research is to improve short-range (12-hour) quantitative precipitation forecasting (QPF) over the Korean peninsula through the use of innovative data assimilation methods based on geosynchronous satellite measurements. As a step in ths direction, a non-standard data assimilation experiment in conjunction with GMS-retrieved nowcasted rainfall information introduced to the mesoscale model is conducted. The 3-hourly precipitation forecast information is assimilated through nudging the associated diabatic heating during the early stages of a forecast period. This procedure is expected to enhance details in the moisture field during model integration, and thus improve spinup performance, assuming the errors in the future time latent heating data ate less than intrinsic model background errors.
Learning from the Past, Looking to the Future: Modeling Social Unrest in Karachi, Pakistan

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

Olson, Jarrod; Kurzrok, Andrew J.; Hund, Gretchen

Social unrest represents a major challenge for policy makers around the globe, as it can quickly escalate from small scale disturbances to highly public protests, riots and even civil war. This research was motivated by a need to understand social instability and to unpack the comments made during a spring 2013 conference hosted by Pacific Northwest National Laboratory’s Center for Global Security and the U.S. Institute for Peace, where policymakers noted that models considering social instability are often not suitable for decision-making. This analysis shows that existing state level models of instability could be improved in spatial scale to themore » city level, even without significantly improved data access. Better data would make this analysis more complete and likely improve the quality of the model. Another challenge with incorporating modeling into decision-making is the need to understand uncertainty in a model. Policy makers are frequently tasked with making decisions without a clear outcome, so characterization of uncertainty is critical. This report describes the work and findings of the project. It took place in three phases: a literature review of social stability research, a “hindsight scan” that looked at historical data, and a “foresight scan” looking at future scenarios.« less
Investigating the Effect of Advanced Automatic Transmissions ...

EPA Pesticide Factsheets

EPA used the validated ALPHA model to predict the effectiveness improvement of real-world transmissions over a baseline four-speed transmission and to predict further improvements possible from future eight-speed transmissions. In preparation for the midterm evaluation (MTE) of the 2017-2025 light-duty GHG emissions rule.
Climate change effects on extreme flows of water supply area in Istanbul: utility of regional climate models and downscaling method.

PubMed

Kara, Fatih; Yucel, Ismail

2015-09-01

This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960-1990) and scenario (2071-2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained.
A behavior change model for internet interventions.

PubMed

Ritterband, Lee M; Thorndike, Frances P; Cox, Daniel J; Kovatchev, Boris P; Gonder-Frederick, Linda A

2009-08-01

The Internet has become a major component to health care and has important implications for the future of the health care system. One of the most notable aspects of the Web is its ability to provide efficient, interactive, and tailored content to the user. Given the wide reach and extensive capabilities of the Internet, researchers in behavioral medicine have been using it to develop and deliver interactive and comprehensive treatment programs with the ultimate goal of impacting patient behavior and reducing unwanted symptoms. To date, however, many of these interventions have not been grounded in theory or developed from behavior change models, and no overarching model to explain behavior change in Internet interventions has yet been published. The purpose of this article is to propose a model to help guide future Internet intervention development and predict and explain behavior changes and symptom improvement produced by Internet interventions. The model purports that effective Internet interventions produce (and maintain) behavior change and symptom improvement via nine nonlinear steps: the user, influenced by environmental factors, affects website use and adherence, which is influenced by support and website characteristics. Website use leads to behavior change and symptom improvement through various mechanisms of change. The improvements are sustained via treatment maintenance. By grounding Internet intervention research within a scientific framework, developers can plan feasible, informed, and testable Internet interventions, and this form of treatment will become more firmly established.
Response to Intervention in Canada: Definitions, the Evidence Base, and Future Directions

ERIC Educational Resources Information Center

McIntosh, Kent; MacKay, Leslie D.; Andreou, Theresa; Brown, Jacqueline A.; Mathews, Susanna; Gietz, Carmen; Bennett, Joanna L.

2011-01-01

Based on challenges with the traditional model of school psychology, response to intervention (RTI) has been advanced as a model of special education eligibility decision making and service delivery that may address the drawbacks of the traditional models of assessment and result in improved outcomes for students. In this article, the RTI model is…
International land Model Benchmarking (ILAMB) Package v002.00

DOE Data Explorer

Collier, Nathaniel [Oak Ridge National Laboratory; Hoffman, Forrest M. [Oak Ridge National Laboratory; Mu, Mingquan [University of California, Irvine; Randerson, James T. [University of California, Irvine; Riley, William J. [Lawrence Berkeley National Laboratory

2016-05-09

As a contribution to International Land Model Benchmarking (ILAMB) Project, we are providing new analysis approaches, benchmarking tools, and science leadership. The goal of ILAMB is to assess and improve the performance of land models through international cooperation and to inform the design of new measurement campaigns and field studies to reduce uncertainties associated with key biogeochemical processes and feedbacks. ILAMB is expected to be a primary analysis tool for CMIP6 and future model-data intercomparison experiments. This team has developed initial prototype benchmarking systems for ILAMB, which will be improved and extended to include ocean model metrics and diagnostics.
International land Model Benchmarking (ILAMB) Package v001.00

DOE Data Explorer

Mu, Mingquan [University of California, Irvine; Randerson, James T. [University of California, Irvine; Riley, William J. [Lawrence Berkeley National Laboratory; Hoffman, Forrest M. [Oak Ridge National Laboratory

2016-05-02

As a contribution to International Land Model Benchmarking (ILAMB) Project, we are providing new analysis approaches, benchmarking tools, and science leadership. The goal of ILAMB is to assess and improve the performance of land models through international cooperation and to inform the design of new measurement campaigns and field studies to reduce uncertainties associated with key biogeochemical processes and feedbacks. ILAMB is expected to be a primary analysis tool for CMIP6 and future model-data intercomparison experiments. This team has developed initial prototype benchmarking systems for ILAMB, which will be improved and extended to include ocean model metrics and diagnostics.
Development of a hybrid modeling approach for predicting intensively managed Douglas-fir growth at multiple scales.

Treesearch

A. Weiskittel; D. Maguire; R. Monserud

2007-01-01

Hybrid models offer the opportunity to improve future growth projections by combining advantages of both empirical and process-based modeling approaches. Hybrid models have been constructed in several regions and their performance relative to a purely empirical approach has varied. A hybrid model was constructed for intensively managed Douglas-fir plantations in the...
Kaizen: a process improvement model for the business of health care and perioperative nursing professionals.

PubMed

Tetteh, Hassan A

2012-01-01

Kaizen is a proven management technique that has a practical application for health care in the context of health care reform and the 2010 Institute of Medicine landmark report on the future of nursing. Compounded productivity is the unique benefit of kaizen, and its principles are change, efficiency, performance of key essential steps, and the elimination of waste through small and continuous process improvements. The kaizen model offers specific instruction for perioperative nurses to achieve process improvement in a five-step framework that includes teamwork, personal discipline, improved morale, quality circles, and suggestions for improvement. Published by Elsevier Inc.
Asymmetric response of tropical cyclone activity to global warming over the North Atlantic and western North Pacific from CMIP5 model projections

NASA Astrophysics Data System (ADS)

Park, Doo-Sun R.; Ho, Chang-Hoi; Chan, Johnny C. L.; Ha, Kyung-Ja; Kim, Hyeong-Seog; Kim, Jinwon; Kim, Joo-Hong

2017-01-01

Recent improvements in the theoretical understanding of the relationship between tropical cyclones (TCs) and their large-scale environments have resulted in significant improvements in the skill for forecasting TC activity at daily and seasonal time-scales. However, future changes in TC activity under a warmer climate remain uncertain, particularly in terms of TC genesis locations and subsequent pathways. Applying a track-pattern-based statistical model to 22 Coupled Model Intercomparison Project Phase 5 (CMIP5) model runs for the historical period and the future period corresponding to the Representative Concentration Pathway 8.5 emissions scenarios, this study shows that in future climate conditions, TC passage frequency will decrease over the North Atlantic, particularly in the Gulf of Mexico, but will increase over the western North Pacific, especially that hits Korea and Japan. Unlike previous studies based on fine-resolution models, an ensemble mean of CMIP5 models projects an increase in TC activity in the western North Pacific, which is owing to enhanced subtropical deep convection and favorable dynamic conditions therein in conjunction with the expansion of the tropics and vice versa for the North Atlantic. Our results suggest that North America will experience less TC landfalls, while northeast Asia will experience more TCs than in the present-day climate.

Asymmetric response of tropical cyclone activity to global warming over the North Atlantic and western North Pacific from CMIP5 model projections.

PubMed

Park, Doo-Sun R; Ho, Chang-Hoi; Chan, Johnny C L; Ha, Kyung-Ja; Kim, Hyeong-Seog; Kim, Jinwon; Kim, Joo-Hong

2017-01-30

Recent improvements in the theoretical understanding of the relationship between tropical cyclones (TCs) and their large-scale environments have resulted in significant improvements in the skill for forecasting TC activity at daily and seasonal time-scales. However, future changes in TC activity under a warmer climate remain uncertain, particularly in terms of TC genesis locations and subsequent pathways. Applying a track-pattern-based statistical model to 22 Coupled Model Intercomparison Project Phase 5 (CMIP5) model runs for the historical period and the future period corresponding to the Representative Concentration Pathway 8.5 emissions scenarios, this study shows that in future climate conditions, TC passage frequency will decrease over the North Atlantic, particularly in the Gulf of Mexico, but will increase over the western North Pacific, especially that hits Korea and Japan. Unlike previous studies based on fine-resolution models, an ensemble mean of CMIP5 models projects an increase in TC activity in the western North Pacific, which is owing to enhanced subtropical deep convection and favorable dynamic conditions therein in conjunction with the expansion of the tropics and vice versa for the North Atlantic. Our results suggest that North America will experience less TC landfalls, while northeast Asia will experience more TCs than in the present-day climate.
Imagining the Future, or How the Standard Model May Survive the Attacks

NASA Astrophysics Data System (ADS)

Hooft, Gerard'T.

After the last missing piece, the Higgs particle, has probably been identified, the Standard Model of the subatomic particles appears to be a quite robust structure, that can survive on its own for a long time to come. Most researchers expect considerable modifications and improvements to come in the near future, but it could also be that the Model will stay essentially as it is. This, however, would also require a change in our thinking, and the question remains whether and how it can be reconciled with our desire for our theories to be "natural".
Imagining the future, or how the Standard Model may survive the attacks

NASA Astrophysics Data System (ADS)

'T Hooft, Gerard

2016-06-01

After the last missing piece, the Higgs particle, has probably been identified, the Standard Model of the subatomic particles appears to be a quite robust structure, that can survive on its own for a long time to come. Most researchers expect considerable modifications and improvements to come in the near future, but it could also be that the Model will stay essentially as it is. This, however, would also require a change in our thinking, and the question remains whether and how it can be reconciled with our desire for our theories to be “natural”.
Human Hemato-Lymphoid System Mice: Current Use and Future Potential for Medicine

PubMed Central

Rongvaux, Anthony; Takizawa, Hitoshi; Strowig, Till; Willinger, Tim; Eynon, Elizabeth E.

2014-01-01

To directly study complex human hemato-lymphoid system physiology and respective system-associated diseases in vivo, human-to-mouse xenotransplantation models for human blood and blood-forming cells and organs have been developed over the past three decades. We here review the fundamental requirements and the remarkable progress made over the past few years in improving these systems, the current major achievements reached by use of these models, and the future challenges to more closely model and study human health and disease and to achieve predictive preclinical testing of both prevention measures and potential new therapies. PMID:23330956
A Collection of Papers on Self-Study and Institutional Improvement, 2003. Volume 2: Organizational Effectiveness and Future Directions. 2003 Edition.

ERIC Educational Resources Information Center

Van Kollenburg, Susan E., Ed.

Papers in this collection were prepared for the annual meeting of the North Central Association of Colleges and Schools. This volume contains papers related to organizational effectiveness and future directions. Chapter 1, "Mission, Planning, and Organizational Change," contains: (1) "Revitalizing Mission: A Collaborative Model" (Stephany…
Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

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

Yu, Miao; Wang, Guiling; Chen, Haishan

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the Northern Hemisphere high latitudes. Including representation of vegetation dynamics is expected to further amplify the model-related uncertainties in projected future changes in surface water and heat fluxes as well as soil moisture content. This is especially the case in the high latitudes of the Northern Hemisphere (e.g., northwestern North America and central North Asia) where the projected vegetation changes are uncertain and in the Tropics (e.g., the Amazon and Congo Basins) where dense vegetation exists. Finally, findings from this study highlight the importance of improving land surface model parameterizations related to soil and snow processes, as well as the importance of improving the accuracy of dynamic vegetation models.« less
Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

DOE PAGES

Yu, Miao; Wang, Guiling; Chen, Haishan

2016-03-01

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the Northern Hemisphere high latitudes. Including representation of vegetation dynamics is expected to further amplify the model-related uncertainties in projected future changes in surface water and heat fluxes as well as soil moisture content. This is especially the case in the high latitudes of the Northern Hemisphere (e.g., northwestern North America and central North Asia) where the projected vegetation changes are uncertain and in the Tropics (e.g., the Amazon and Congo Basins) where dense vegetation exists. Finally, findings from this study highlight the importance of improving land surface model parameterizations related to soil and snow processes, as well as the importance of improving the accuracy of dynamic vegetation models.« less
Workshop on Engineering Turbulence Modeling

NASA Technical Reports Server (NTRS)

Povinelli, Louis A. (Editor); Liou, W. W. (Editor); Shabbir, A. (Editor); Shih, T.-H. (Editor)

1992-01-01

Discussed here is the future direction of various levels of engineering turbulence modeling related to computational fluid dynamics (CFD) computations for propulsion. For each level of computation, there are a few turbulence models which represent the state-of-the-art for that level. However, it is important to know their capabilities as well as their deficiencies in order to help engineers select and implement the appropriate models in their real world engineering calculations. This will also help turbulence modelers perceive the future directions for improving turbulence models. The focus is on one-point closure models (i.e., from algebraic models to higher order moment closure schemes and partial differential equation methods) which can be applied to CFD computations. However, other schemes helpful in developing one-point closure models, are also discussed.
Southeast Atmosphere Studies: learning from model-observation syntheses

NASA Astrophysics Data System (ADS)

Mao, Jingqiu; Carlton, Annmarie; Cohen, Ronald C.; Brune, William H.; Brown, Steven S.; Wolfe, Glenn M.; Jimenez, Jose L.; Pye, Havala O. T.; Ng, Nga Lee; Xu, Lu; McNeill, V. Faye; Tsigaridis, Kostas; McDonald, Brian C.; Warneke, Carsten; Guenther, Alex; Alvarado, Matthew J.; de Gouw, Joost; Mickley, Loretta J.; Leibensperger, Eric M.; Mathur, Rohit; Nolte, Christopher G.; Portmann, Robert W.; Unger, Nadine; Tosca, Mika; Horowitz, Larry W.

2018-02-01

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales.This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.
Southeast Atmosphere Studies: learning from model-observation syntheses

PubMed Central

Mao, Jingqiu; Carlton, Annmarie; Cohen, Ronald C.; Brune, William H.; Brown, Steven S.; Wolfe, Glenn M.; Jimenez, Jose L.; Pye, Havala O. T.; Ng, Nga Lee; Xu, Lu; McNeill, V. Faye; Tsigaridis, Kostas; McDonald, Brian C.; Warneke, Carsten; Guenther, Alex; Alvarado, Matthew J.; de Gouw, Joost; Mickley, Loretta J.; Leibensperger, Eric M.; Mathur, Rohit; Nolte, Christopher G.; Portmann, Robert W.; Unger, Nadine; Tosca, Mika; Horowitz, Larry W.

2018-01-01

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.
Southeast Atmosphere Studies: Learning from Model-Observation Syntheses

NASA Technical Reports Server (NTRS)

Mao, Jingqiu; Carlton, Annmarie; Cohen, Ronald C.; Brune, William H.; Brown, Steven S.; Wolfe, Glenn M.; Jimenez, Jose L.; Pye, Havala O. T.; Ng, Nga Lee; Xu, Lu;

2018-01-01

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

Critical analysis of 3-D organoid in vitro cell culture models for high-throughput drug candidate toxicity assessments.

PubMed

Astashkina, Anna; Grainger, David W

2014-04-01

Drug failure due to toxicity indicators remains among the primary reasons for staggering drug attrition rates during clinical studies and post-marketing surveillance. Broader validation and use of next-generation 3-D improved cell culture models are expected to improve predictive power and effectiveness of drug toxicological predictions. However, after decades of promising research significant gaps remain in our collective ability to extract quality human toxicity information from in vitro data using 3-D cell and tissue models. Issues, challenges and future directions for the field to improve drug assay predictive power and reliability of 3-D models are reviewed. Copyright © 2014 Elsevier B.V. All rights reserved.
Pre-engineering Spaceflight Validation of Environmental Models and the 2005 HZETRN Simulation Code

NASA Technical Reports Server (NTRS)

Nealy, John E.; Cucinotta, Francis A.; Wilson, John W.; Badavi, Francis F.; Dachev, Ts. P.; Tomov, B. T.; Walker, Steven A.; DeAngelis, Giovanni; Blattnig, Steve R.; Atwell, William

2006-01-01

The HZETRN code has been identified by NASA for engineering design in the next phase of space exploration highlighting a return to the Moon in preparation for a Mars mission. In response, a new series of algorithms beginning with 2005 HZETRN, will be issued by correcting some prior limitations and improving control of propagated errors along with established code verification processes. Code validation processes will use new/improved low Earth orbit (LEO) environmental models with a recently improved International Space Station (ISS) shield model to validate computational models and procedures using measured data aboard ISS. These validated models will provide a basis for flight-testing the designs of future space vehicles and systems of the Constellation program in the LEO environment.
Future irrigation expansion outweigh groundwater recharge gains from climate change in semi-arid India.

PubMed

Sishodia, Rajendra P; Shukla, Sanjay; Wani, Suhas P; Graham, Wendy D; Jones, James W

2018-09-01

Simultaneous effects of future climate and irrigation intensification on surface and groundwater systems are not well understood. Efforts are needed to understand the future groundwater availability and associated surface flows under business-as-usual management to formulate policy changes to improve water sustainability. We combine measurements with integrated modeling (MIKE SHE/MIKE11) to evaluate the effects of future climate (2040-2069), with and without irrigation expansion, on water levels and flows in an agricultural watershed in low-storage crystalline aquifer region of south India. Demand and supply management changes, including improved efficiency of irrigation water as well as energy uses, were evaluated. Increased future rainfall (7-43%, from 5 Global Climate Models) with no further expansion of irrigation wells increased the groundwater recharge (10-55%); however, most of the recharge moved out of watershed as increased baseflow (17-154%) with a small increase in net recharge (+0.2mm/year). When increased rainfall was considered with projected increase in irrigation withdrawals, both hydrologic extremes of well drying and flooding were predicted. A 100-year flow event was predicted to be a 5-year event in the future. If irrigation expansion follows the historical trends, earlier and more frequent well drying, a source of farmers' distress in India, was predicted to worsen in the future despite the recharge gains from increased rainfall. Storage and use of excess flows, improved irrigation efficiency with flood to drip conversion in 25% of irrigated area, and reduced energy subsidy (free electricity for 3.5h compared to 7h/day; $1 billion savings) provided sufficient water savings to support future expansion in irrigated areas while mitigating well drying as well as flooding. Reductions in energy subsidy to fund the implementation of economically desirable (high benefit-cost ratio) demand (drip irrigation) and supply (water capture and storage) management was recommended to achieve a sustainable food-water-energy nexus in semi-arid regions. Copyright © 2018 Elsevier B.V. All rights reserved.
Detailed assessment of global transport-energy models’ structures and projections

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

Yeh, Sonia; Mishra, Gouri Shankar; Fulton, Lew

This paper focuses on comparing the frameworks and projections from four major global transportation models with considerable transportation technology and behavioral detail. We analyze and compare the modeling frameworks, underlying data, assumptions, intermediate parameters, and projections to identify the sources of divergence or consistency, as well as key knowledge gaps. We find that there are significant differences in the base-year data and key parameters for future projections, especially for developing countries. These include passenger and freight activity, mode shares, vehicle ownership rates, and even energy consumption by mode, particularly for shipping, aviation and trucking. This may be due in partmore » to a lack of previous efforts to do such consistency-checking and “bench-marking.” We find that the four models differ in terms of the relative roles of various mitigation strategies to achieve a 2°C / 450 ppm CO2e target: the economics-based integrated assessment models favor the use of low carbon fuels as the primary mitigation option followed by efficiency improvements, whereas transport-only and expert-based models favor efficiency improvements of vehicles followed by mode shifts. We offer recommendations for future modeling improvements focusing on (1) reducing data gaps; (2) translating the findings from this study into relevant policy implications such as feasibility of current policy goals, additional policy targets needed, regional vs. global reductions, etc.; (3) modeling strata of demographic groups to improve understanding of vehicle ownership levels, travel behavior, and urban vs. rural considerations; and (4) conducting coordinated efforts in aligning input assumptions and historical data, policy analysis, and modeling insights.« less
Improvements to the Noah Land Surface Model in WRF-CMAQ, and its Application to Future Changes in the Chesapeake Bay Region

EPA Science Inventory

Regional, state, and local environmental regulatory agencies often use Eulerian meteorological and air quality models to investigate the potential impacts of climate, emissions, and land use changes on nutrient loading and air quality. The Noah land surface model in WRF could be...
Comparing large-scale hydrological model predictions with observed streamflow in the Pacific Northwest: effects of climate and groundwater

Treesearch

Mohammad Safeeq; Guillaume S. Mauger; Gordon E. Grant; Ivan Arismendi; Alan F. Hamlet; Se-Yeun Lee

2014-01-01

Assessing uncertainties in hydrologic models can improve accuracy in predicting future streamflow. Here, simulated streamflows using the Variable Infiltration Capacity (VIC) model at coarse (1/16°) and fine (1/120°) spatial resolutions were evaluated against observed streamflows from 217 watersheds. In...
Modelling future improvements in the St. Louis River fishery from sediment remediation and aquatic habitat restoration

EPA Science Inventory

The presence of fish consumption advisories has a negative impact on fishing. In the St. Louis River, an important natural resource management goal is to reduce or eliminate fish consumption advisories by remediating contaminant sediments and improving aquatic habitat. However, w...
New Pedagogical Approaches to Improve Production of Materials in Distance Education.

ERIC Educational Resources Information Center

Mena, Marta

1992-01-01

Analyzes problems involved in the production of instructional materials for distance education and offers new pedagogical approaches to improve production of materials for distance education. Discusses past, present, and future methods used to design instructional materials, proposes models to aid in the production of instructional materials, and…
Parameter estimation with Sandage-Loeb test

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

Geng, Jia-Jia; Zhang, Jing-Fei; Zhang, Xin, E-mail: gengjiajia163@163.com, E-mail: jfzhang@mail.neu.edu.cn, E-mail: zhangxin@mail.neu.edu.cn

2014-12-01

The Sandage-Loeb (SL) test directly measures the expansion rate of the universe in the redshift range of 2 ∼< z ∼< 5 by detecting redshift drift in the spectra of Lyman-α forest of distant quasars. We discuss the impact of the future SL test data on parameter estimation for the ΛCDM, the wCDM, and the w{sub 0}w{sub a}CDM models. To avoid the potential inconsistency with other observational data, we take the best-fitting dark energy model constrained by the current observations as the fiducial model to produce 30 mock SL test data. The SL test data provide an important supplement to the other dark energymore » probes, since they are extremely helpful in breaking the existing parameter degeneracies. We show that the strong degeneracy between Ω{sub m} and H{sub 0} in all the three dark energy models is well broken by the SL test. Compared to the current combined data of type Ia supernovae, baryon acoustic oscillation, cosmic microwave background, and Hubble constant, the 30-yr observation of SL test could improve the constraints on Ω{sub m} and H{sub 0} by more than 60% for all the three models. But the SL test can only moderately improve the constraint on the equation of state of dark energy. We show that a 30-yr observation of SL test could help improve the constraint on constant w by about 25%, and improve the constraints on w{sub 0} and w{sub a} by about 20% and 15%, respectively. We also quantify the constraining power of the SL test in the future high-precision joint geometric constraints on dark energy. The mock future supernova and baryon acoustic oscillation data are simulated based on the space-based project JDEM. We find that the 30-yr observation of SL test would help improve the measurement precision of Ω{sub m}, H{sub 0}, and w{sub a} by more than 70%, 20%, and 60%, respectively, for the w{sub 0}w{sub a}CDM model.« less

Improved formalism for precision Higgs coupling fits

NASA Astrophysics Data System (ADS)

Barklow, Tim; Fujii, Keisuke; Jung, Sunghoon; Karl, Robert; List, Jenny; Ogawa, Tomohisa; Peskin, Michael E.; Tian, Junping

2018-03-01

Future e+e- colliders give the promise of model-independent determinations of the couplings of the Higgs boson. In this paper, we present an improved formalism for extracting Higgs boson couplings from e+e- data, based on the effective field theory description of corrections to the Standard Model. We apply this formalism to give projections of Higgs coupling accuracies for stages of the International Linear Collider and for other proposed e+e- colliders.
EFFECTS OF CLIMATE CHANGE ON WEATHER AND WATER

EPA Science Inventory

Information regarding weather and hydrological processes and how they may change in the future is available from a variety of dynamically downscaled climate models. Current studies are helping to improve the use of such models for regional climate impact studies by testing the s...
Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Singh, Vijay P.; Xia, Youlong

2018-03-01

Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.
Research and Development Trend of Shape Control for Cold Rolling Strip

NASA Astrophysics Data System (ADS)

Wang, Dong-Cheng; Liu, Hong-Min; Liu, Jun

2017-09-01

Shape is an important quality index of cold rolling strip. Up to now, many problems in the shape control domain have not been solved satisfactorily, and a review on the research progress in the shape control domain can help to seek new breakthrough directions. In the past 10 years, researches and applications of shape control models, shape control means, shape detection technology, and shape control system have achieved significant progress. In the aspect of shape control models, the researches in the past improve the accuracy, speed and robustness of the models. The intelligentization of shape control models should be strengthened in the future. In the aspect of the shape control means, the researches in the past focus on the roll optimization, mill type selection, process optimization, local strip shape control, edge drop control, and so on. In the future, more attention should be paid to the coordination control of both strip shape and other quality indexes, and the refinement of control objective should be strengthened. In the aspects of shape detection technology and shape control system, some new types of shape detection meters and shape control systems are developed and have successfully industrial applications. In the future, the standardization of shape detection technology and shape control system should be promoted to solve the problem of compatibility. In general, the four expected development trends of shape control for cold rolling strip in the future are intelligentization, coordination, refinement, and standardization. The proposed research provides new breakthrough directions for improving shape quality.
Strategies for Development of Palliative Care From the Perspectives of General Population and Health Care Professionals: A Japanese Outreach Palliative Care Trial of Integrated Regional Model Study.

PubMed

Yoshida, Saran; Miyashita, Mitsunori; Morita, Tatsuya; Akizuki, Nobuya; Akiyama, Miki; Shirahige, Yutaka; Ichikawa, Takayuki; Eguchi, Kenji

2015-09-01

This study primarily aimed to identify future actions required to promote palliative care in Japan. The future actions regarded as effective by the general population were "improve physicians' skill in palliative care" (61%), "create a counseling center for cancer" (61%), and "improve nurses' skill in palliative care" (60%). In contrast, future actions regarded as effective by the health care professionals were "set up a Web site that provides information about cancer" (72%), "promote consultation with specialists in palliative care" (71%), and "open an outpatient department specializing in palliative care" (70%). The results suggest (1) development and maintenance of settings; (2) enhancement of palliative care education and training programs for health care providers; and (3) improvement in distributing information about cancer and regional palliative care resources to the general population. © The Author(s) 2014.
Can generic knee joint models improve the measurement of osteoarthritic knee kinematics during squatting activity?

PubMed

Clément, Julien; Dumas, Raphaël; Hagemeister, Nicola; de Guise, Jaques A

2017-01-01

Knee joint kinematics derived from multi-body optimisation (MBO) still requires evaluation. The objective of this study was to corroborate model-derived kinematics of osteoarthritic knees obtained using four generic knee joint models used in musculoskeletal modelling - spherical, hinge, degree-of-freedom coupling curves and parallel mechanism - against reference knee kinematics measured by stereo-radiography. Root mean square errors ranged from 0.7° to 23.4° for knee rotations and from 0.6 to 9.0 mm for knee displacements. Model-derived knee kinematics computed from generic knee joint models was inaccurate. Future developments and experiments should improve the reliability of osteoarthritic knee models in MBO and musculoskeletal modelling.
A synopsis of climate change effects on groundwater recharge

NASA Astrophysics Data System (ADS)

Smerdon, Brian D.

2017-12-01

Six review articles published between 2011 and 2016 on groundwater and climate change are briefly summarized. This synopsis focuses on aspects related to predicting changes to groundwater recharge conditions, with several common conclusions between the review articles being noted. The uncertainty of distribution and trend in future precipitation from General Circulation Models (GCMs) results in varying predictions of recharge, so much so that modelling studies are often not able to predict the magnitude and direction (increase or decrease) of future recharge conditions. Evolution of modelling approaches has led to the use of multiple GCMs and hydrologic models to create an envelope of future conditions that reflects the probability distribution. The choice of hydrologic model structure and complexity, and the choice of emissions scenario, has been investigated and somewhat resolved; however, recharge results remain sensitive to downscaling methods. To overcome uncertainty and provide practical use in water management, the research community indicates that modelling at a mesoscale, somewhere between watersheds and continents, is likely ideal. Improvements are also suggested for incorporating groundwater processes within GCMs.
NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.

2007-12-01

National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high spatial and temporal resolution remote sensing datasets; improved time-series meteorological inputs required for crop growth models; and regional prediction capability through geo-processing-based yield modeling.
Crops in silico: A community wide multi-scale computational modeling framework of plant canopies

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Christensen, A.; Borkiewic, K.; Yiwen, X.; Ellis, A.; Panneerselvam, B.; Kannan, K.; Shrivastava, S.; Cox, D.; Hart, J.; Marshall-Colon, A.; Long, S.

2016-12-01

Current crop models predict a looming gap between supply and demand for primary foodstuffs over the next 100 years. While significant yield increases were achieved in major food crops during the early years of the green revolution, the current rates of yield increases are insufficient to meet future projected food demand. Furthermore, with projected reduction in arable land, decrease in water availability, and increasing impacts of climate change on future food production, innovative technologies are required to sustainably improve crop yield. To meet these challenges, we are developing Crops in silico (Cis), a biologically informed, multi-scale, computational modeling framework that can facilitate whole plant simulations of crop systems. The Cis framework is capable of linking models of gene networks, protein synthesis, metabolic pathways, physiology, growth, and development in order to investigate crop response to different climate scenarios and resource constraints. This modeling framework will provide the mechanistic details to generate testable hypotheses toward accelerating directed breeding and engineering efforts to increase future food security. A primary objective for building such a framework is to create synergy among an inter-connected community of biologists and modelers to create a realistic virtual plant. This framework advantageously casts the detailed mechanistic understanding of individual plant processes across various scales in a common scalable framework that makes use of current advances in high performance and parallel computing. We are currently designing a user friendly interface that will make this tool equally accessible to biologists and computer scientists. Critically, this framework will provide the community with much needed tools for guiding future crop breeding and engineering, understanding the emergent implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment.
From ENSEMBLES to CORDEX: exploring the progress for hydrological impact research for the upper Danube basin

NASA Astrophysics Data System (ADS)

Stanzel, Philipp; Kling, Harald

2017-04-01

EURO-CORDEX Regional Climate Model (RCM) data are available as result of the latest initiative of the climate modelling community to provide ever improved simulations of past and future climate in Europe. The spatial resolution of the climate models increased from 25 x 25 km in the previous coordinated initiative, ENSEMBLES, to 12 x 12 km in the CORDEX EUR-11 simulations. This higher spatial resolution might yield improved representation of the historic climate, especially in complex mountainous terrain, improving applicability in impact studies. CORDEX scenario simulations are based on Representative Concentration Pathways, while ENSEMBLES applied the SRES greenhouse gas emission scenarios. The new emission scenarios might lead to different projections of future climate. In this contribution we explore these two dimensions of development from ENSEMBLES to CORDEX - representation of the past and projections for the future - in the context of a hydrological climate change impact study for the Danube River. We replicated previous hydrological simulations that used ENSEMBLES data of 21 RCM simulations under SRES A1B emission scenario as meteorological input data (Kling et al. 2012), and now applied CORDEX EUR-11 data of 16 RCM simulations under RCP4.5 and RCP8.5 emission scenarios. The climate variables precipitation and temperature were used to drive a monthly hydrological model of the upper Danube basin upstream of Vienna (100,000 km2). RCM data was bias corrected and downscaled to the scale of hydrological model units. Results with CORDEX data were compared with results with ENSEMBLES data, analysing both the driving meteorological input and the resulting discharge projections. Results with CORDEX data show no general improvement in the accuracy of representing historic climatic features, despite the increase in spatial model resolution. The tendency of ENSEMBLES scenario projections of increasing precipitation in winter and decreasing precipitation in summer is reproduced with the CORDEX RCMs, albeit with slightly higher precipitation in the CORDEX data. The distinct pattern of future change in discharge seasonality - increasing winter discharge and decreasing summer discharge - is confirmed with the new CORDEX data, with a range of projections very similar to the range projected by the ENSEMBLES RCMs. References: Kling, H., Fuchs, M., Paulin, M. 2012. Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios. Journal of Hydrology 424-425, 264-277.
Workshop on challenges, insights, and future directions for mouse and humanized models in cancer immunology and immunotherapy: a report from the associated programs of the 2016 annual meeting for the Society for Immunotherapy of cancer.

PubMed

Zloza, Andrew; Karolina Palucka, A; Coussens, Lisa M; Gotwals, Philip J; Headley, Mark B; Jaffee, Elizabeth M; Lund, Amanda W; Sharpe, Arlene H; Sznol, Mario; Wainwright, Derek A; Wong, Kwok-Kin; Bosenberg, Marcus W

2017-09-19

Understanding how murine models can elucidate the mechanisms underlying antitumor immune responses and advance immune-based drug development is essential to advancing the field of cancer immunotherapy. The Society for Immunotherapy of Cancer (SITC) convened a workshop titled, "Challenges, Insights, and Future Directions for Mouse and Humanized Models in Cancer Immunology and Immunotherapy" as part of the SITC 31st Annual Meeting and Associated Programs on November 10, 2016 in National Harbor, MD. The workshop focused on key issues in optimizing models for cancer immunotherapy research, with discussions on the strengths and weaknesses of current models, approaches to improve the predictive value of mouse models, and advances in cancer modeling that are anticipated in the near future. This full-day program provided an introduction to the most common immunocompetent and humanized models used in cancer immunology and immunotherapy research, and addressed the use of models to evaluate immune-targeting therapies. Here, we summarize the workshop presentations and subsequent panel discussion.
Vehicle Modeling for Future Generation Transportation Simulation

DOT National Transportation Integrated Search

2009-05-10

Recent development of inter-vehicular wireless communication technologies have motivated many innovative applications aiming at significantly increasing traffic throughput and improving highway safety. Powerful traffic simulation is an indispensable ...
Large-Ensemble modeling of past and future variations of the Antarctic Ice Sheet with a coupled ice-Earth-sea level model

NASA Astrophysics Data System (ADS)

Pollard, David; DeConto, Robert; Gomez, Natalya

2016-04-01

To date, most modeling of the Antarctic Ice Sheet's response to future warming has been calibrated using recent and modern observations. As an alternate approach, we apply a hybrid 3-D ice sheet-shelf model to the last deglacial retreat of Antarctica, making use of geologic data of the last ~20,000 years to test the model against the large-scale variations during this period. The ice model is coupled to a global Earth-sea level model to improve modeling of the bedrock response and to capture ocean-ice gravitational interactions. Following several recent ice-sheet studies, we use Large Ensemble (LE) statistical methods, performing sets of 625 runs from 30,000 years to present with systematically varying model parameters. Objective scores for each run are calculated using modern data and past reconstructed grounding lines, relative sea level records, cosmogenic elevation-age data and uplift rates. The LE results are analyzed to calibrate 4 particularly uncertain model parameters that concern marginal ice processes and interaction with the ocean. LE's are extended into the future with climates following RCP scenarios. An additional scoring criterion tests the model's ability to reproduce estimated sea-level high stands in the warm mid-Pliocene, for which drastic retreat mechanisms of hydrofracturing and ice-cliff failure are needed in the model. The LE analysis provides future sea-level-rise envelopes with well-defined parametric uncertainty bounds. Sensitivities of future LE results to Pliocene sea-level estimates, coupling to the Earth-sea level model, and vertical profiles of Earth properties, will be presented.
Improvements and new features in the PDF module

NASA Technical Reports Server (NTRS)

Norris, Andrew T.

1995-01-01

This viewgraph presentation discusses what models are used in this package and what their advantages and disadvantages are, how the probability density function (PDF) model is implemented and the features of the program, and what can be expected in the future from the NASA Lewis PDF code.
High efficiency silicon solar cell review

NASA Technical Reports Server (NTRS)

Godlewski, M. P. (Editor)

1975-01-01

An overview is presented of the current research and development efforts to improve the performance of the silicon solar cell. The 24 papers presented reviewed experimental and analytic modeling work which emphasizes the improvment of conversion efficiency and the reduction of manufacturing costs. A summary is given of the round-table discussion, in which the near- and far-term directions of future efficiency improvements were discussed.
HSR Model Deformation Measurements from Subsonic to Supersonic Speeds

NASA Technical Reports Server (NTRS)

Burner, A. W.; Erickson, G. E.; Goodman, W. L.; Fleming, G. A.

1999-01-01

This paper describes the video model deformation technique (VMD) used at five NASA facilities and the projection moire interferometry (PMI) technique used at two NASA facilities. Comparisons between the two techniques for model deformation measurements are provided. Facilities at NASA-Ames and NASA-Langley where deformation measurements have been made are presented. Examples of HSR model deformation measurements from the Langley Unitary Wind Tunnel, Langley 16-foot Transonic Wind Tunnel, and the Ames 12-foot Pressure Tunnel are presented. A study to improve and develop new targeting schemes at the National Transonic Facility is also described. The consideration of milled targets for future HSR models is recommended when deformation measurements are expected to be required. Finally, future development work for VMD and PMI is addressed.
Modelling the impact of future socio-economic and climate change scenarios on river microbial water quality.

PubMed

Islam, M M Majedul; Iqbal, Muhammad Shahid; Leemans, Rik; Hofstra, Nynke

2018-03-01

Microbial surface water quality is important, as it is related to health risk when the population is exposed through drinking, recreation or consumption of irrigated vegetables. The microbial surface water quality is expected to change with socio-economic development and climate change. This study explores the combined impacts of future socio-economic and climate change scenarios on microbial water quality using a coupled hydrodynamic and water quality model (MIKE21FM-ECOLab). The model was applied to simulate the baseline (2014-2015) and future (2040s and 2090s) faecal indicator bacteria (FIB: E. coli and enterococci) concentrations in the Betna river in Bangladesh. The scenarios comprise changes in socio-economic variables (e.g. population, urbanization, land use, sanitation and sewage treatment) and climate variables (temperature, precipitation and sea-level rise). Scenarios have been developed building on the most recent Shared Socio-economic Pathways: SSP1 and SSP3 and Representative Concentration Pathways: RCP4.5 and RCP8.5 in a matrix. An uncontrolled future results in a deterioration of the microbial water quality (+75% by the 2090s) due to socio-economic changes, such as higher population growth, and changes in rainfall patterns. However, microbial water quality improves under a sustainable scenario with improved sewage treatment (-98% by the 2090s). Contaminant loads were more influenced by changes in socio-economic factors than by climatic change. To our knowledge, this is the first study that combines climate change and socio-economic development scenarios to simulate the future microbial water quality of a river. This approach can also be used to assess future consequences for health risks. Copyright © 2017 The Authors. Published by Elsevier GmbH.. All rights reserved.
Improvement of Reynolds-Stress and Triple-Product Lag Models

NASA Technical Reports Server (NTRS)

Olsen, Michael E.; Lillard, Randolph P.

2017-01-01

The Reynolds-stress and triple product Lag models were created with a normal stress distribution which was denied by a 4:3:2 distribution of streamwise, spanwise and wall normal stresses, and a ratio of r(sub w) = 0.3k in the log layer region of high Reynolds number flat plate flow, which implies R11(+)= [4/(9/2)*.3] approximately 2.96. More recent measurements show a more complex picture of the log layer region at high Reynolds numbers. The first cut at improving these models along with the direction for future refinements is described. Comparison with recent high Reynolds number data shows areas where further work is needed, but also shows inclusion of the modeled turbulent transport terms improve the prediction where they influence the solution. Additional work is needed to make the model better match experiment, but there is significant improvement in many of the details of the log layer behavior.
[Optimization of the parameters of microcirculatory structural adaptation model based on improved quantum-behaved particle swarm optimization algorithm].

PubMed

Pan, Qing; Yao, Jialiang; Wang, Ruofan; Cao, Ping; Ning, Gangmin; Fang, Luping

2017-08-01

The vessels in the microcirculation keep adjusting their structure to meet the functional requirements of the different tissues. A previously developed theoretical model can reproduce the process of vascular structural adaptation to help the study of the microcirculatory physiology. However, until now, such model lacks the appropriate methods for its parameter settings with subsequent limitation of further applications. This study proposed an improved quantum-behaved particle swarm optimization (QPSO) algorithm for setting the parameter values in this model. The optimization was performed on a real mesenteric microvascular network of rat. The results showed that the improved QPSO was superior to the standard particle swarm optimization, the standard QPSO and the previously reported Downhill algorithm. We conclude that the improved QPSO leads to a better agreement between mathematical simulation and animal experiment, rendering the model more reliable in future physiological studies.
In vivo models in breast cancer research: progress, challenges and future directions

PubMed Central

Holen, Ingunn; Speirs, Valerie; Morrissey, Bethny

2017-01-01

ABSTRACT Research using animal model systems has been instrumental in delivering improved therapies for breast cancer, as well as in generating new insights into the mechanisms that underpin development of the disease. A large number of different models are now available, reflecting different types and stages of the disease; choosing which one to use depends on the specific research question(s) to be investigated. Based on presentations and discussions from leading experts who attended a recent workshop focused on in vivo models of breast cancer, this article provides a perspective on the many varied uses of these models in breast cancer research, their strengths, associated challenges and future directions. Among the questions discussed were: how well do models represent the different stages of human disease; how can we model the involvement of the human immune system and microenvironment in breast cancer; what are the appropriate models of metastatic disease; can we use models to carry out preclinical drug trials and identify pathways responsible for drug resistance; and what are the limitations of patient-derived xenograft models? We briefly outline the areas where the existing breast cancer models require improvement in light of the increased understanding of the disease process, reflecting the drive towards more personalised therapies and identification of mechanisms of drug resistance. PMID:28381598

Improving the Use of Species Distribution Models in Conservation Planning and Management under Climate Change

PubMed Central

Porfirio, Luciana L.; Harris, Rebecca M. B.; Lefroy, Edward C.; Hugh, Sonia; Gould, Susan F.; Lee, Greg; Bindoff, Nathaniel L.; Mackey, Brendan

2014-01-01

Choice of variables, climate models and emissions scenarios all influence the results of species distribution models under future climatic conditions. However, an overview of applied studies suggests that the uncertainty associated with these factors is not always appropriately incorporated or even considered. We examine the effects of choice of variables, climate models and emissions scenarios can have on future species distribution models using two endangered species: one a short-lived invertebrate species (Ptunarra Brown Butterfly), and the other a long-lived paleo-endemic tree species (King Billy Pine). We show the range in projected distributions that result from different variable selection, climate models and emissions scenarios. The extent to which results are affected by these choices depends on the characteristics of the species modelled, but they all have the potential to substantially alter conclusions about the impacts of climate change. We discuss implications for conservation planning and management, and provide recommendations to conservation practitioners on variable selection and accommodating uncertainty when using future climate projections in species distribution models. PMID:25420020
Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

DOE PAGES

Xu, Xiaofeng; Yuan, Fengming; Hanson, Paul J.; ...

2016-01-28

A number of numerical models have been developed to quantify the magnitude, over the past 4 decades, such that we have investigated the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH 4) fluxes within terrestrial ecosystems. These CH 4 models are also used for integrating multi-scale CH 4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH 4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvementmore » and application. Our key findings are that (1) the focus of CH 4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH 4 processes and their environmental controls, and (3) significant data–model and model–model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Furthermore three areas for future improvements and applications of terrestrial CH 4 models are that (1) CH 4 models should more explicitly represent the mechanisms underlying land–atmosphere CH 4 exchange, with an emphasis on improving and validating individual CH 4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH 4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. Finally, these improvements in CH 4 models would be beneficial for the Earth system models and further simulation of climate–carbon cycle feedbacks.« less
Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling.

PubMed

Mainali, Kumar P; Warren, Dan L; Dhileepan, Kunjithapatham; McConnachie, Andrew; Strathie, Lorraine; Hassan, Gul; Karki, Debendra; Shrestha, Bharat B; Parmesan, Camille

2015-12-01

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species' native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our 'best' model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium. However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. © 2015 John Wiley & Sons Ltd.
ARM - Midlatitude Continental Convective Clouds

DOE Data Explorer

Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-19

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.
ARM - Midlatitude Continental Convective Clouds (comstock-hvps)

DOE Data Explorer

Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-06

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.
Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Service (KMS)

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

2014-01-01

SPoRT/SERVIR/RCMRD/KMS Collaboration: Builds off strengths of each organization. SPoRT: Transition of satellite, modeling and verification capabilities; SERVIR-Africa/RCMRD: International capacity-building expertise; KMS: Operational organization with regional weather forecasting expertise in East Africa. Hypothesis: Improved land-surface initialization over Eastern Africa can lead to better temperature, moisture, and ultimately precipitation forecasts in NWP models. KMS currently initializes Weather Research and Forecasting (WRF) model with NCEP/Global Forecast System (GFS) model 0.5-deg initial / boundary condition data. LIS will provide much higher-resolution land-surface data at a scale more representative to regional WRF configuration. Future implementation of real-time NESDIS/VIIRS vegetation fraction to further improve land surface representativeness.
Improved formalism for precision Higgs coupling fits

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

Barklow, Tim; Fujii, Keisuke; Jung, Sunghoon

Future e +e – colliders give the promise of model-independent determinations of the couplings of the Higgs boson. In this paper, we present an improved formalism for extracting Higgs boson couplings from e +e – data, based on the effective field theory description of corrections to the Standard Model. Lastly, we apply this formalism to give projections of Higgs coupling accuracies for stages of the International Linear Collider and for other proposed e +e – colliders.
Improved formalism for precision Higgs coupling fits

DOE PAGES

Barklow, Tim; Fujii, Keisuke; Jung, Sunghoon; ...

2018-03-20

Future e +e – colliders give the promise of model-independent determinations of the couplings of the Higgs boson. In this paper, we present an improved formalism for extracting Higgs boson couplings from e +e – data, based on the effective field theory description of corrections to the Standard Model. Lastly, we apply this formalism to give projections of Higgs coupling accuracies for stages of the International Linear Collider and for other proposed e +e – colliders.
Towards the ecotourism: a decision support model for the assessment of sustainability of mountain huts in the Alps.

PubMed

Stubelj Ars, Mojca; Bohanec, Marko

2010-12-01

This paper studies mountain hut infrastructure in the Alps as an important element of ecotourism in the Alpine region. To improve the decision-making process regarding the implementation of future infrastructure and improvement of existing infrastructure in the vulnerable natural environment of mountain ecosystems, a new decision support model has been developed. The methodology is based on qualitative multi-attribute modelling supported by the DEXi software. The integrated rule-based model is hierarchical and consists of two submodels that cover the infrastructure of the mountain huts and that of the huts' surroundings. The final goal for the designed tool is to help minimize the ecological footprint of tourists in environmentally sensitive and undeveloped mountain areas and contribute to mountain ecotourism. The model has been tested in the case study of four mountain huts in Triglav National Park in Slovenia. Study findings provide a new empirical approach to evaluating existing mountain infrastructure and predicting improvements for the future. The assessment results are of particular interest for decision makers in protected areas, such as Alpine national parks managers and administrators. In a way, this model proposes an approach to the management assessment of mountain huts with the main aim of increasing the quality of life of mountain environment visitors as well as the satisfaction of tourists who may eventually become ecotourists. Copyright © 2010 Elsevier Ltd. All rights reserved.
Applying Collaborative Learning and Quality Improvement to Public Health: Lessons from the Collaborative Improvement and Innovation Network (CoIIN) to Reduce Infant Mortality.

PubMed

Ghandour, Reem M; Flaherty, Katherine; Hirai, Ashley; Lee, Vanessa; Walker, Deborah Klein; Lu, Michael C

2017-06-01

Infant mortality remains a significant public health problem in the U.S. The Collaborative Improvement & Innovation Network (CoIIN) model is an innovative approach, using the science of quality improvement and collaborative learning, which was applied across 13 Southern states in Public Health Regions IV and VI to reduce infant mortality and improve birth outcomes. We provide an in-depth discussion of the history, development, implementation, and adaptation of the model based on the experience of the original CoIIN organizers and participants. In addition to the political genesis and functional components of the initiative, 8 key lessons related to staffing, planning, and implementing future CoIINs are described in detail. This paper reports the findings from a process evaluation of the model. Data on the states' progress toward reducing infant mortality and improving birth outcomes were collected through a survey in the final months of a 24-month implementation period, as well as through ongoing team communications. The peer-to-peer exchange and platform for collaborative learning, as well as the sharing of data across the states, were major strengths and form the foundation for future CoIIN efforts. A lasting legacy of the initiative is the unique application and sharing of provisional "real time" data to inform "real time" decision-making. The CoIIN model of collaborative learning, QI, and innovation offers a promising approach to strengthening partnerships within and across states, bolstering data systems to inform and track progress more rapidly, and ultimately accelerating improvement toward healthier communities, States, and the Nation as a whole.
Planning intensive care unit design using computer simulation modeling: optimizing integration of clinical, operational, and architectural requirements.

PubMed

OʼHara, Susan

2014-01-01

Nurses have increasingly been regarded as critical members of the planning team as architects recognize their knowledge and value. But the nurses' role as knowledge experts can be expanded to leading efforts to integrate the clinical, operational, and architectural expertise through simulation modeling. Simulation modeling allows for the optimal merge of multifactorial data to understand the current state of the intensive care unit and predict future states. Nurses can champion the simulation modeling process and reap the benefits of a cost-effective way to test new designs, processes, staffing models, and future programming trends prior to implementation. Simulation modeling is an evidence-based planning approach, a standard, for integrating the sciences with real client data, to offer solutions for improving patient care.
The role of self-improvement and self-evaluation motives in social comparisons with idealised female bodies in the media.

PubMed

Halliwell, Emma; Dittmar, Helga

2005-09-01

This study investigates the effect of social comparisons with media models on women's body image based on either self-evaluation or self-improvement motives. Ninety-eight women, for whom appearance was a relevant comparison dimension, viewed advertisements that did, or did not, feature idealised models, after being prompted to engage in self-evaluation or self-improvement comparisons. The results indicate that, when focusing on self-evaluation, comparisons with thin models are associated with higher body-focused anxiety than viewing no model advertisements. In contrast, when focusing on self-improvement, comparisons with thin models are not associated with higher body-focused anxiety than viewing no models. Furthermore, women's general tendency to engage in social comparisons moderated the effects of self-evaluative comparisons with models, so that women who did not habitually engage in social comparisons were most strongly affected. It is suggested that motive for social comparison may explain previous inconsistencies in the experimental exposure literature and warrants more careful attention in future research.
The Agricultural Model Intercomparison and Improvement Project: Phase I Activities by a Global Community of Science. Chapter 1

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia E.; Jones, James W.; Hatfield, Jerry L.; Antle, John M.; Ruane, Alexander C.; Mutter, Carolyn Z.

2015-01-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) was founded in 2010. Its mission is to improve substantially the characterization of world food security as affected by climate variability and change, and to enhance adaptation capacity in both developing and developed countries. The objectives of AgMIP are to: Incorporate state-of-the-art climate, crop/livestock, and agricultural economic model improvements into coordinated multi-model regional and global assessments of future climate impacts and adaptation and other key aspects of the food system. Utilize multiple models, scenarios, locations, crops/livestock, and participants to explore uncertainty and the impact of data and methodological choices. Collaborate with regional experts in agronomy, animal sciences, economics, and climate to build a strong basis for model applications, addressing key climate related questions and sustainable intensification farming systems. Improve scientific and adaptive capacity in modeling for major agricultural regions in the developing and developed world, with a focus on vulnerable regions. Improve agricultural data and enhance data-sharing based on their intercomparison and evaluation using best scientific practices. Develop modeling frameworks to identify and evaluate promising adaptation technologies and policies and to prioritize strategies.
Possible future changes in South East Australian frost frequency: an inter-comparison of statistical downscaling approaches

NASA Astrophysics Data System (ADS)

Crimp, Steven; Jin, Huidong; Kokic, Philip; Bakar, Shuvo; Nicholls, Neville

2018-04-01

Anthropogenic climate change has already been shown to effect the frequency, intensity, spatial extent, duration and seasonality of extreme climate events. Understanding these changes is an important step in determining exposure, vulnerability and focus for adaptation. In an attempt to support adaptation decision-making we have examined statistical modelling techniques to improve the representation of global climate model (GCM) derived projections of minimum temperature extremes (frosts) in Australia. We examine the spatial changes in minimum temperature extreme metrics (e.g. monthly and seasonal frost frequency etc.), for a region exhibiting the strongest station trends in Australia, and compare these changes with minimum temperature extreme metrics derived from 10 GCMs, from the Coupled Model Inter-comparison Project Phase 5 (CMIP 5) datasets, and via statistical downscaling. We compare the observed trends with those derived from the "raw" GCM minimum temperature data as well as examine whether quantile matching (QM) or spatio-temporal (spTimerQM) modelling with Quantile Matching can be used to improve the correlation between observed and simulated extreme minimum temperatures. We demonstrate, that the spTimerQM modelling approach provides correlations with observed daily minimum temperatures for the period August to November of 0.22. This represents an almost fourfold improvement over either the "raw" GCM or QM results. The spTimerQM modelling approach also improves correlations with observed monthly frost frequency statistics to 0.84 as opposed to 0.37 and 0.81 for the "raw" GCM and QM results respectively. We apply the spatio-temporal model to examine future extreme minimum temperature projections for the period 2016 to 2048. The spTimerQM modelling results suggest the persistence of current levels of frost risk out to 2030, with the evidence of continuing decadal variation.
Conceptual Processes for Linking Eutrophication and Network Models

DTIC Science & Technology

2006-08-01

recommends a general procedure for future endeavors in this area. BACKGROUND: In recent years new ideas for nutrient management to control...network model. Coupling these two models will provide managers a new perspective on how to improve management strategies and help answer questions such...Dorothy H. Tillman, Dr. Carl F. Cerco, and Mr. Mark R. Noel of the Water Quality and Contaminant Modeling Branch, Enviromental Laboratory (EL
Biodiversity and Climate Modeling Workshop Series: Identifying gaps and needs for improving large-scale biodiversity models

NASA Astrophysics Data System (ADS)

Weiskopf, S. R.; Myers, B.; Beard, T. D.; Jackson, S. T.; Tittensor, D.; Harfoot, M.; Senay, G. B.

2017-12-01

At the global scale, well-accepted global circulation models and agreed-upon scenarios for future climate from the Intergovernmental Panel on Climate Change (IPCC) are available. In contrast, biodiversity modeling at the global scale lacks analogous tools. While there is great interest in development of similar bodies and efforts for international monitoring and modelling of biodiversity at the global scale, equivalent modelling tools are in their infancy. This lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity to bring together climate, ecosystem, and biodiversity modeling experts to promote development of integrated approaches in modeling global biodiversity. Improved models are needed to understand how we are progressing towards the Aichi Biodiversity Targets, many of which are not on track to meet the 2020 goal, threatening global biodiversity conservation, monitoring, and sustainable use. We brought together biodiversity, climate, and remote sensing experts to try to 1) identify lessons learned from the climate community that can be used to improve global biodiversity models; 2) explore how NASA and other remote sensing products could be better integrated into global biodiversity models and 3) advance global biodiversity modeling, prediction, and forecasting to inform the Aichi Biodiversity Targets, the 2030 Sustainable Development Goals, and the Intergovernmental Platform on Biodiversity and Ecosystem Services Global Assessment of Biodiversity and Ecosystem Services. The 1st In-Person meeting focused on determining a roadmap for effective assessment of biodiversity model projections and forecasts by 2030 while integrating and assimilating remote sensing data and applying lessons learned, when appropriate, from climate modeling. Here, we present the outcomes and lessons learned from our first E-discussion and in-person meeting and discuss the next steps for future meetings.
Current and future pluvial flood hazard analysis for the city of Antwerp

NASA Astrophysics Data System (ADS)

Willems, Patrick; Tabari, Hossein; De Niel, Jan; Van Uytven, Els; Lambrechts, Griet; Wellens, Geert

2016-04-01

For the city of Antwerp in Belgium, higher rainfall extremes were observed in comparison with surrounding areas. The differences were found statistically significant for some areas and may be the result of the heat island effect in combination with the higher concentrations of aerosols. A network of 19 rain gauges but with varying records length (the longest since the 1960s) and continuous radar data for 10 years were combined to map the spatial variability of rainfall extremes over the city at various durations from 15 minutes to 1 day together with the uncertainty. The improved spatial rainfall information was used as input in the sewer system model of the city to analyze the frequency of urban pluvial floods. Comparison with historical flood observations from various sources (fire brigade and media) confirmed that the improved spatial rainfall information also improved sewer impact results on both the magnitude and frequency of the sewer floods. Next to these improved urban flood impact results for recent and current climatological conditions, the new insights on the local rainfall microclimate were also helpful to enhance future projections on rainfall extremes and pluvial floods in the city. This was done by improved statistical downscaling of all available CMIP5 global climate model runs (160 runs) for the 4 RCP scenarios, as well as the available EURO-CORDEX regional climate model runs. Two types of statistical downscaling methods were applied for that purpose (a weather typing based method, and a quantile perturbation approach), making use of the microclimate results and its dependency on specific weather types. Changes in extreme rainfall intensities were analyzed and mapped as a function of the RCP scenario, together with the uncertainty, decomposed in the uncertainties related to the climate models, the climate model initialization or limited length of the 30-year time series (natural climate variability) and the statistical downscaling (albeit limited to two types of methods). These were finally transferred into future pluvial flash flood hazard maps for the city together with the uncertainties, and are considered as basis for spatial planning and adaptation.
How To Assess The Future Tree-Cover Potential For Reforestation Planning In Semi-Arid Regions? An Attempt Using The Vegetation Model ORCHIDEE

NASA Astrophysics Data System (ADS)

Rajaud, A.; De Noblet-Ducoudré, N.

2015-12-01

More and more reforestation projects are undertaken at local to continental scales to fight desertification, to address development challenges, and to improve local living conditions in tropical semi-arid regions. These regions are very sensitive to climatic changes and the potential for maintaining tree-covers will be altered in the next decades. Therefore, reforestation planning needs predicting the future "climatic tree-cover potential": the optimum tree-fraction sustainable in future climatic states. Global circulation models projections provide possible future climatologies for the 21st century. These can be used at the global scale to force a land-surface model, which in turn simulates the vegetation development under these conditions. The tree cover leading to an optimum development may then be identified. We propose here to run a state-of-the-art model and to assess the span and the relevance of the answers that can be obtained for reforestation planning. The ORCHIDEE vegetation model is chosen here to allow a multi-criteria evaluation of the optimum cover, as it returns surface climate state variables as well as vegetation functioning and biomass products. It is forced with global climate data (WFDEI and CRU) for the 20th century and models projections (CMIP5 outputs) for the 21st century. At the grid-cell resolution of the forcing climate data, tree-covers ranging from 0 to 100% are successively prescribed. A set of indicators is then derived from the model outputs, meant for modulating reforestation strategies according to the regional priorities (e.g. maximize the biomass production or decrease the surface air temperature). The choice of indicators and the relevance of the final answers provided will be collectively assessed by the climate scientists and reforestation project management experts from the KINOME social enterprise (http://en.kinome.fr). Such feedback will point towards the model most urging needs for improvement.
Understanding and quantifying foliar temperature acclimation for Earth System Models

NASA Astrophysics Data System (ADS)

Smith, N. G.; Dukes, J.

2015-12-01

Photosynthesis and respiration on land are the two largest carbon fluxes between the atmosphere and Earth's surface. The parameterization of these processes represent major uncertainties in the terrestrial component of the Earth System Models used to project future climate change. Research has shown that much of this uncertainty is due to the parameterization of the temperature responses of leaf photosynthesis and autotrophic respiration, which are typically based on short-term empirical responses. Here, we show that including longer-term responses to temperature, such as temperature acclimation, can help to reduce this uncertainty and improve model performance, leading to drastic changes in future land-atmosphere carbon feedbacks across multiple models. However, these acclimation formulations have many flaws, including an underrepresentation of many important global flora. In addition, these parameterizations were done using multiple studies that employed differing methodology. As such, we used a consistent methodology to quantify the short- and long-term temperature responses of maximum Rubisco carboxylation (Vcmax), maximum rate of Ribulos-1,5-bisphosphate regeneration (Jmax), and dark respiration (Rd) in multiple species representing each of the plant functional types used in global-scale land surface models. Short-term temperature responses of each process were measured in individuals acclimated for 7 days at one of 5 temperatures (15-35°C). The comparison of short-term curves in plants acclimated to different temperatures were used to evaluate long-term responses. Our analyses indicated that the instantaneous response of each parameter was highly sensitive to the temperature at which they were acclimated. However, we found that this sensitivity was larger in species whose leaves typically experience a greater range of temperatures over the course of their lifespan. These data indicate that models using previous acclimation formulations are likely incorrectly simulating leaf carbon exchange responses to future warming. Therefore, our data, if used to parameterize large-scale models, are likely to provide an even greater improvement in model performance, resulting in more reliable projections of future carbon-clime feedbacks.
Io's Magnetospheric Interaction: An MHD Model with Day-Night Asymmetry

NASA Technical Reports Server (NTRS)

Kabin, K.; Combi, M. R.; Gombosi, T. I.; DeZeeuw, D. L.; Hansen, K. C.; Powell, K. G.

2001-01-01

In this paper we present the results of all improved three-dimensional MHD model for Io's interaction with Jupiter's magnetosphere. We have included the day-night asymmetry into the spatial distribution of our mass-loading, which allowed us to reproduce several smaller features or the Galileo December 1995 data set. The calculation is performed using our newly modified description of the pick-up processes that accounts for the effects of the corotational electric field existing in the Jovian magnetosphere. This change in the formulation of the source terms for the MHD equations resulted in significant improvements in the comparison with the Galileo measurements. We briefly discuss the limitations of our model and possible future improvements.

A first-order analysis of the potential role of CO2 fertilization to affect the global carbon budget: A comparison of four terrestrial biosphere models

USGS Publications Warehouse

Kicklighter, D.W.; Bruno, M.; Donges, S.; Esser, G.; Heimann, Martin; Helfrich, J.; Ift, F.; Joos, F.; Kaduk, J.; Kohlmaier, G.H.; McGuire, A.D.; Melillo, J.M.; Meyer, R.; Moore, B.; Nadler, A.; Prentice, I.C.; Sauf, W.; Schloss, A.L.; Sitch, S.; Wittenberg, U.; Wurth, G.

1999-01-01

We compared the simulated responses of net primary production, heterotrophic respiration, net ecosystem production and carbon storage in natural terrestrial ecosystems to historical (1765 to 1990) and projected (1990 to 2300) changes of atmospheric CO2 concentration of four terrestrial biosphere models: the Bern model, the Frankfurt Biosphere Model (FBM), the High-Resolution Biosphere Model (HRBM) and the Terrestrial Ecosystem Model (TEM). The results of the model intercomparison suggest that CO2 fertilization of natural terrestrial vegetation has the potential to account for a large fraction of the so-called 'missing carbon sink' of 2.0 Pg C in 1990. Estimates of this potential are reduced when the models incorporate the concept that CO2 fertilization can be limited by nutrient availability. Although the model estimates differ on the potential size (126 to 461 Pg C) of the future terrestrial sink caused by CO2 fertilization, the results of the four models suggest that natural terrestrial ecosystems will have a limited capacity to act as a sink of atmospheric CO2 in the future as a result of physiological constraints and nutrient constraints on NPP. All the spatially explicit models estimate a carbon sink in both tropical and northern temperate regions, but the strength of these sinks varies over time. Differences in the simulated response of terrestrial ecosystems to CO2 fertilization among the models in this intercomparison study reflect the fact that the models have highlighted different aspects of the effect of CO2 fertilization on carbon dynamics of natural terrestrial ecosystems including feedback mechanisms. As interactions with nitrogen fertilization, climate change and forest regrowth may play an important role in simulating the response of terrestrial ecosystems to CO2 fertilization, these factors should be included in future analyses. Improvements in spatially explicit data sets, whole-ecosystems experiments and the availability of net carbon exchange measurements across the globe will also help to improve future evaluations of the role of CO2 fertilization on terrestrial carbon storage.
Modeling the Earth system in the Mission to Planet Earth era

NASA Technical Reports Server (NTRS)

Unninayar, Sushel; Bergman, Kenneth H.

1993-01-01

A broad overview is made of global earth system modeling in the Mission to Planet Earth (MTPE) era for the multidisciplinary audience encompassed by the Global Change Research Program (GCRP). Time scales of global system fluctuation and change are described in Section 2. Section 3 provides a rubric for modeling the global earth system, as presently understood. The ability of models to predict the future state of the global earth system and the extent to which their predictions are reliable are covered in Sections 4 and 5. The 'engineering' use of global system models (and predictions) is covered in Section 6. Section 7 covers aspects of an increasing need for improved transform algorithms and better methods to assimilate this information into global models. Future monitoring and data requirements are detailed in Section 8. Section 9 covers the NASA-initiated concept 'Mission to Planet Earth,' which employs space and ground based measurement systems to provide the scientific basis for understanding global change. Section 10 concludes this review with general remarks concerning the state of global system modeling and observing technology and the need for future research.
Developing a Consensus-Driven, Core Competency Model to Shape Future Audio Engineering Technology Curriculum: A Web-Based Modified Delphi Study

ERIC Educational Resources Information Center

Tough, David T.

2009-01-01

The purpose of this online study was to create a ranking of essential core competencies and technologies required by AET (audio engineering technology) programs 10 years in the future. The study was designed to facilitate curriculum development and improvement in the rapidly expanding number of small to medium sized audio engineering technology…
Teaching-as-Research Internships: A Model for the Development of Future Chemistry Faculty and the Improvement of Teaching in Science, Technology, Engineering, and Math

ERIC Educational Resources Information Center

Gillian-Daniel, Donald L.; Walz, Kenneth A.

2016-01-01

Over the past decade, the University of Wisconsin-Madison (UW-Madison) and Madison Area Technical College (Madison College) partnered to create an internship pathway for graduate students pursuing careers as future science, technology, engineering and math (STEM) faculty members. Since 2003, 10 doctoral students from the university completed…
"The Good, the Bad and the Ugly": A Model for Reflective Teaching Practices in Coaching Pedagogy

ERIC Educational Resources Information Center

Gordon, Evelyn J.

2017-01-01

Coaching should go beyond drills and preparing for the big game. One question many coaches have asked themselves is, "How do I get better?" One way to ensure that future coaches (current students) in sport coaching education are thinking of ways to improve for the future is to teach them to think about the past. This is where reflection…
Synchronous orbit power technology needs

NASA Technical Reports Server (NTRS)

Slifer, L. W., Jr.; Billerbeck, W. J.

1979-01-01

The needs are defined for future geosynchronous orbit spacecraft power subsystem components, including power generation, energy storage, and power processing. A review of the rapid expansion of the satellite communications field provides a basis for projection into the future. Three projected models, a mission model, an orbit transfer vehicle model, and a mass model for power subsystem components are used to define power requirements and mass limitations for future spacecraft. Based upon these three models, the power subsystems for a 10 kw, 10 year life, dedicated spacecraft and for a 20 kw, 20 year life, multi-mission platform are analyzed in further detail to establish power density requirements for the generation, storage and processing components of power subsystems as related to orbit transfer vehicle capabilities. Comparison of these requirements to state of the art design values shows that major improvements, by a factor of 2 or more, are needed to accomplish the near term missions. However, with the advent of large transfer vehicles, these requirements are significantly reduced, leaving the long lifetime requirement, associated with reliability and/or refurbishment, as the primary development need. A few technology advances, currently under development, are noted with regard to their impacts on future capability.
Can metric-based approaches really improve multi-model climate projections? A perfect model framework applied to summer temperature change in France.

NASA Astrophysics Data System (ADS)

Boé, Julien; Terray, Laurent

2014-05-01

Ensemble approaches for climate change projections have become ubiquitous. Because of large model-to-model variations and, generally, lack of rationale for the choice of a particular climate model against others, it is widely accepted that future climate change and its impacts should not be estimated based on a single climate model. Generally, as a default approach, the multi-model ensemble mean (MMEM) is considered to provide the best estimate of climate change signals. The MMEM approach is based on the implicit hypothesis that all the models provide equally credible projections of future climate change. This hypothesis is unlikely to be true and ideally one would want to give more weight to more realistic models. A major issue with this alternative approach lies in the assessment of the relative credibility of future climate projections from different climate models, as they can only be evaluated against present-day observations: which present-day metric(s) should be used to decide which models are "good" and which models are "bad" in the future climate? Once a supposedly informative metric has been found, other issues arise. What is the best statistical method to combine multiple models results taking into account their relative credibility measured by a given metric? How to be sure in the end that the metric-based estimate of future climate change is not in fact less realistic than the MMEM? It is impossible to provide strict answers to those questions in the climate change context. Yet, in this presentation, we propose a methodological approach based on a perfect model framework that could bring some useful elements of answer to the questions previously mentioned. The basic idea is to take a random climate model in the ensemble and treat it as if it were the truth (results of this model, in both past and future climate, are called "synthetic observations"). Then, all the other members from the multi-model ensemble are used to derive thanks to a metric-based approach a posterior estimate of climate change, based on the synthetic observation of the metric. Finally, it is possible to compare the posterior estimate to the synthetic observation of future climate change to evaluate the skill of the method. The main objective of this presentation is to describe and apply this perfect model framework to test different methodological issues associated with non-uniform model weighting and similar metric-based approaches. The methodology presented is general, but will be applied to the specific case of summer temperature change in France, for which previous works have suggested potentially useful metrics associated with soil-atmosphere and cloud-temperature interactions. The relative performances of different simple statistical approaches to combine multiple model results based on metrics will be tested. The impact of ensemble size, observational errors, internal variability, and model similarity will be characterized. The potential improvements associated with metric-based approaches compared to the MMEM is terms of errors and uncertainties will be quantified.
Improving the representation of photosynthesis in Earth system models

NASA Astrophysics Data System (ADS)

Rogers, A.; Medlyn, B. E.; Dukes, J.; Bonan, G. B.; von Caemmerer, S.; Dietze, M.; Kattge, J.; Leakey, A. D.; Mercado, L. M.; Niinemets, U.; Prentice, I. C. C.; Serbin, S.; Sitch, S.; Way, D. A.; Zaehle, S.

2015-12-01

Continued use of fossil fuel drives an accelerating increase in atmospheric CO2 concentration ([CO2]) and is the principal cause of global climate change. Many of the observed and projected impacts of rising [CO2] portend increasing environmental and economic risk, yet the uncertainty surrounding the projection of our future climate by Earth System Models (ESMs) is unacceptably high. Improving confidence in our estimation of future [CO2] is essential if we seek to project global change with greater confidence. There are critical uncertainties over the long term response of terrestrial CO2 uptake to global change, more specifically, over the size of the terrestrial carbon sink and over its sensitivity to rising [CO2] and temperature. Reducing the uncertainty associated with model representation of the largest CO2 flux on the planet is therefore an essential part of improving confidence in projections of global change. Here we have examined model representation of photosynthesis in seven process models including several global models that underlie the representation of photosynthesis in the land surface model component of ESMs that were part of the recent Fifth Assessment Report from the IPCC. Our approach was to focus on how physiological responses are represented by these models, and to better understand how structural and parametric differences drive variation in model responses to light, CO2, nutrients, temperature, vapor pressure deficit and soil moisture. We challenged each model to produce leaf and canopy responses to these factors to help us identify areas in which current process knowledge and emerging data sets could be used to improve model skill, and also identify knowledge gaps in current understanding that directly impact model outputs. We hope this work will provide a roadmap for the scientific activity that is necessary to advance process representation, parameterization and scaling of photosynthesis in the next generation of Earth System Models.
Agent-Based Modeling in Public Health: Current Applications and Future Directions.

PubMed

Tracy, Melissa; Cerdá, Magdalena; Keyes, Katherine M

2018-04-01

Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.
Health-based risk adjustment: improving the pharmacy-based cost group model by adding diagnostic cost groups.

PubMed

Prinsze, Femmeke J; van Vliet, René C J A

Since 1991, risk-adjusted premium subsidies have existed in the Dutch social health insurance sector, which covered about two-thirds of the population until 2006. In 2002, pharmacy-based cost groups (PCGs) were included in the demographic risk adjustment model, which improved the goodness-of-fit, as measured by the R2, to 11.5%. The model's R2 reached 22.8% in 2004, when inpatient diagnostic information was added in the form of diagnostic cost groups (DCGs). PCGs and DCGs appear to be complementary in their ability to predict future costs. PCGs particularly improve the R2 for outpatient expenses, whereas DCGs improve the R2 for inpatient expenses. In 2006, this system of risk-adjusted premium subsidies was extended to cover the entire population.
Marie McMahan: AECT President 1978-1979

ERIC Educational Resources Information Center

Audiovisual Instruction, 1978

1978-01-01

The 1978-79 president, Marie McMahan, discusses a model of the interrelationships of the diverse groups within the association for the future improvement of communications, involvement, and professional preparation within AECT. (CMV)
Figures of merit for present and future dark energy probes

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

Mortonson, Michael J.; Huterer, Dragan; Hu, Wayne

2010-09-15

We compare current and forecasted constraints on dynamical dark energy models from Type Ia supernovae and the cosmic microwave background using figures of merit based on the volume of the allowed dark energy parameter space. For a two-parameter dark energy equation of state that varies linearly with the scale factor, and assuming a flat universe, the area of the error ellipse can be reduced by a factor of {approx}10 relative to current constraints by future space-based supernova data and CMB measurements from the Planck satellite. If the dark energy equation of state is described by a more general basis ofmore » principal components, the expected improvement in volume-based figures of merit is much greater. While the forecasted precision for any single parameter is only a factor of 2-5 smaller than current uncertainties, the constraints on dark energy models bounded by -1{<=}w{<=}1 improve for approximately 6 independent dark energy parameters resulting in a reduction of the total allowed volume of principal component parameter space by a factor of {approx}100. Typical quintessence models can be adequately described by just 2-3 of these parameters even given the precision of future data, leading to a more modest but still significant improvement. In addition to advances in supernova and CMB data, percent-level measurement of absolute distance and/or the expansion rate is required to ensure that dark energy constraints remain robust to variations in spatial curvature.« less
The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6

NASA Astrophysics Data System (ADS)

Gillett, Nathan P.; Shiogama, Hideo; Funke, Bernd; Hegerl, Gabriele; Knutti, Reto; Matthes, Katja; Santer, Benjamin D.; Stone, Daithi; Tebaldi, Claudia

2016-10-01

Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of future climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.
Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions

PubMed Central

Lawley, Mark A.; Siscovick, David S.; Zhang, Donglan; Pagán, José A.

2016-01-01

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions. PMID:27236380
Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions.

PubMed

Li, Yan; Lawley, Mark A; Siscovick, David S; Zhang, Donglan; Pagán, José A

2016-05-26

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.
Future changes in hydro-climatic extremes in the Upper Indus, Ganges, and Brahmaputra River basins

PubMed Central

Lutz, Arthur F.; Nepal, Santosh; Khanal, Sonu; Pradhananga, Saurav; Shrestha, Arun B.; Immerzeel, Walter W.

2017-01-01

Future hydrological extremes, such as floods and droughts, may pose serious threats for the livelihoods in the upstream domains of the Indus, Ganges, Brahmaputra. For this reason, the impacts of climate change on future hydrological extremes is investigated in these river basins. We use a fully-distributed cryospheric-hydrological model to simulate current and future hydrological fluxes and force the model with an ensemble of 8 downscaled General Circulation Models (GCMs) that are selected from the RCP4.5 and RCP8.5 scenarios. The model is calibrated on observed daily discharge and geodetic mass balances. The climate forcing and the outputs of the hydrological model are used to evaluate future changes in climatic extremes, and hydrological extremes by focusing on high and low flows. The outcomes show an increase in the magnitude of climatic means and extremes towards the end of the 21st century where climatic extremes tend to increase stronger than climatic means. Future mean discharge and high flow conditions will very likely increase. These increases might mainly be the result of increasing precipitation extremes. To some extent temperature extremes might also contribute to increasing discharge extremes, although this is highly dependent on magnitude of change in temperature extremes. Low flow conditions may occur less frequently, although the uncertainties in low flow projections can be high. The results of this study may contribute to improved understanding on the implications of climate change for the occurrence of future hydrological extremes in the Hindu Kush–Himalayan region. PMID:29287098
Leaders in Future and Current Technology Teaming Up to Improve Ethanol

Science.gov Websites

and NREL expertise to: Develop improvements in process throughput and water management for dry mill , Complete an overall process engineering model of the dry mill technology that identifies new ways to and operation of "dry mill" plants that currently produce ethanol from corn starch. Dry
Modeling Interdependent and Periodic Real-World Action Sequences

PubMed Central

Kurashima, Takeshi; Althoff, Tim; Leskovec, Jure

2018-01-01

Mobile health applications, including those that track activities such as exercise, sleep, and diet, are becoming widely used. Accurately predicting human actions in the real world is essential for targeted recommendations that could improve our health and for personalization of these applications. However, making such predictions is extremely difficult due to the complexities of human behavior, which consists of a large number of potential actions that vary over time, depend on each other, and are periodic. Previous work has not jointly modeled these dynamics and has largely focused on item consumption patterns instead of broader types of behaviors such as eating, commuting or exercising. In this work, we develop a novel statistical model, called TIPAS, for Time-varying, Interdependent, and Periodic Action Sequences. Our approach is based on personalized, multivariate temporal point processes that model time-varying action propensities through a mixture of Gaussian intensities. Our model captures short-term and long-term periodic interdependencies between actions through Hawkes process-based self-excitations. We evaluate our approach on two activity logging datasets comprising 12 million real-world actions (e.g., eating, sleep, and exercise) taken by 20 thousand users over 17 months. We demonstrate that our approach allows us to make successful predictions of future user actions and their timing. Specifically, TIPAS improves predictions of actions, and their timing, over existing methods across multiple datasets by up to 156%, and up to 37%, respectively. Performance improvements are particularly large for relatively rare and periodic actions such as walking and biking, improving over baselines by up to 256%. This demonstrates that explicit modeling of dependencies and periodicities in real-world behavior enables successful predictions of future actions, with implications for modeling human behavior, app personalization, and targeting of health interventions. PMID:29780977
AP-8 trapped proton environment for solar maximum and solar minimum. [Computer accessible models

NASA Technical Reports Server (NTRS)

Sawyer, D. M.; Vette, J. I.

1976-01-01

Data sets from Ov-3 and Azur indicate a need for improvement in models of the stably trapped proton flux with energies between 0.1 and 400 MeV. Two computer accessible models are described: AP8MAX and AP8MIN. The models are presented in the form of nomographs, B-L plots, R-lambda plots, and equatorial radial profiles. Nomographs of the orbit-integrated fluxes are also discussed. The models are compared with each other, with the data, and with previous AP models. Requirements for future improvements include more complete data coverage and periodic comparisons with new data sets as they become available. The machine-sensible format in which the models are available are described.
Dynamic linear models using the Kalman filter for early detection and early warning of malaria outbreaks

NASA Astrophysics Data System (ADS)

Merkord, C. L.; Liu, Y.; DeVos, M.; Wimberly, M. C.

2015-12-01

Malaria early detection and early warning systems are important tools for public health decision makers in regions where malaria transmission is seasonal and varies from year to year with fluctuations in rainfall and temperature. Here we present a new data-driven dynamic linear model based on the Kalman filter with time-varying coefficients that are used to identify malaria outbreaks as they occur (early detection) and predict the location and timing of future outbreaks (early warning). We fit linear models of malaria incidence with trend and Fourier form seasonal components using three years of weekly malaria case data from 30 districts in the Amhara Region of Ethiopia. We identified past outbreaks by comparing the modeled prediction envelopes with observed case data. Preliminary results demonstrated the potential for improved accuracy and timeliness over commonly-used methods in which thresholds are based on simpler summary statistics of historical data. Other benefits of the dynamic linear modeling approach include robustness to missing data and the ability to fit models with relatively few years of training data. To predict future outbreaks, we started with the early detection model for each district and added a regression component based on satellite-derived environmental predictor variables including precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and land surface temperature (LST) and spectral indices from the Moderate Resolution Imaging Spectroradiometer (MODIS). We included lagged environmental predictors in the regression component of the model, with lags chosen based on cross-correlation of the one-step-ahead forecast errors from the first model. Our results suggest that predictions of future malaria outbreaks can be improved by incorporating lagged environmental predictors.

Hydrologic Design in the Anthropocene

NASA Astrophysics Data System (ADS)

Vogel, R. M.; Farmer, W. H.; Read, L.

2014-12-01

In an era dubbed the Anthropocene, the natural world is being transformed by a myriad of human influences. As anthropogenic impacts permeate hydrologic systems, hydrologists are challenged to fully account for such changes and develop new methods of hydrologic design. Deterministic watershed models (DWM), which can account for the impacts of changes in land use, climate and infrastructure, are becoming increasing popular for the design of flood and/or drought protection measures. As with all models that are calibrated to existing datasets, DWMs are subject to model error or uncertainty. In practice, the model error component of DWM predictions is typically ignored yet DWM simulations which ignore model error produce model output which cannot reproduce the statistical properties of the observations they are intended to replicate. In the context of hydrologic design, we demonstrate how ignoring model error can lead to systematic downward bias in flood quantiles, upward bias in drought quantiles and upward bias in water supply yields. By reincorporating model error, we document how DWM models can be used to generate results that mimic actual observations and preserve their statistical behavior. In addition to use of DWM for improved predictions in a changing world, improved communication of the risk and reliability is also needed. Traditional statements of risk and reliability in hydrologic design have been characterized by return periods, but such statements often assume that the annual probability of experiencing a design event remains constant throughout the project horizon. We document the general impact of nonstationarity on the average return period and reliability in the context of hydrologic design. Our analyses reveal that return periods do not provide meaningful expressions of the likelihood of future hydrologic events. Instead, knowledge of system reliability over future planning horizons can more effectively prepare society and communicate the likelihood of future hydrologic events of interest.
Evaluation of Mid-Size Male Hybrid III Models for use in Spaceflight Occupant Protection Analysis

NASA Technical Reports Server (NTRS)

Putnam, J.; Somers, J.; Wells, J.; Newby, N.; Currie-Gregg, N.; Lawrence, C.

2016-01-01

Introduction: In an effort to improve occupant safety during dynamic phases of spaceflight, the National Aeronautics and Space Administration (NASA) has worked to develop occupant protection standards for future crewed spacecraft. One key aspect of these standards is the identification of injury mechanisms through anthropometric test devices (ATDs). Within this analysis, both physical and computational ATD evaluations are required to reasonably encompass the vast range of loading conditions any spaceflight crew may encounter. In this study the accuracy of publically available mid-size male HIII ATD finite element (FE) models are evaluated within applicable loading conditions against extensive sled testing performed on their physical counterparts. Methods: A series of sled tests were performed at the Wright Patterson Air force Base (WPAFB) employing variations of magnitude, duration, and impact direction to encompass the dynamic loading range for expected spaceflight. FE simulations were developed to the specifications of the test setup and driven using measured acceleration profiles. Both fast and detailed FE models of the mid-size male HIII were ran to quantify differences in their accuracy and thus assess the applicability of each within this field. Results: Preliminary results identify the dependence of model accuracy on loading direction, magnitude, and rate. Additionally the accuracy of individual response metrics are shown to vary across each model within evaluated test conditions. Causes for model inaccuracy are identified based on the observed relationships. Discussion: Computational modeling provides an essential component to ATD injury metric evaluation used to ensure the safety of future spaceflight occupants. The assessment of current ATD models lays the groundwork for how these models can be used appropriately in the future. Identification of limitations and possible paths for improvement aid in the development of these effective analysis tools.
Evaluation of Mid-Size Male Hybrid III Models for use in Spaceflight Occupant Protection Analysis

NASA Technical Reports Server (NTRS)

Putnam, Jacob B.; Sommers, Jeffrey T.; Wells, Jessica A.; Newby, Nathaniel J.; Currie-Gregg, Nancy J.; Lawrence, Chuck

2016-01-01

In an effort to improve occupant safety during dynamic phases of spaceflight, the National Aeronautics and Space Administration (NASA) has worked to develop occupant protection standards for future crewed spacecraft. One key aspect of these standards is the identification of injury mechanisms through anthropometric test devices (ATDs). Within this analysis, both physical and computational ATD evaluations are required to reasonably encompass the vast range of loading conditions any spaceflight crew may encounter. In this study the accuracy of publically available mid-size male HIII ATD finite element (FE) models are evaluated within applicable loading conditions against extensive sled testing performed on their physical counterparts. Methods: A series of sled tests were performed at the Wright Patterson Air force Base (WPAFB) employing variations of magnitude, duration, and impact direction to encompass the dynamic loading range for expected spaceflight. FE simulations were developed to the specifications of the test setup and driven using measured acceleration profiles. Both fast and detailed FE models of the mid-size male HIII were ran to quantify differences in their accuracy and thus assess the applicability of each within this field. Results: Preliminary results identify the dependence of model accuracy on loading direction, magnitude, and rate. Additionally the accuracy of individual response metrics are shown to vary across each model within evaluated test conditions. Causes for model inaccuracy are identified based on the observed relationships. Discussion: Computational modeling provides an essential component to ATD injury metric evaluation used to ensure the safety of future spaceflight occupants. The assessment of current ATD models lays the groundwork for how these models can be used appropriately in the future. Identification of limitations and possible paths for improvement aid in the development of these effective analysis tools.
Species distribution modeling based on the automated identification of citizen observations.

PubMed

Botella, Christophe; Joly, Alexis; Bonnet, Pierre; Monestiez, Pascal; Munoz, François

2018-02-01

A species distribution model computed with automatically identified plant observations was developed and evaluated to contribute to future ecological studies. We used deep learning techniques to automatically identify opportunistic plant observations made by citizens through a popular mobile application. We compared species distribution modeling of invasive alien plants based on these data to inventories made by experts. The trained models have a reasonable predictive effectiveness for some species, but they are biased by the massive presence of cultivated specimens. The method proposed here allows for fine-grained and regular monitoring of some species of interest based on opportunistic observations. More in-depth investigation of the typology of the observations and the sampling bias should help improve the approach in the future.
What We Talk About When We Talk About Drought: Tree-ring Perspectives on Model-Data Comparisons in Hydroclimate Research

NASA Astrophysics Data System (ADS)

Cook, B.; Anchukaitis, K. J.

2017-12-01

Comparative analyses of paleoclimate reconstructions and climate model simulations can provide valuable insights into past and future climate events. Conducting meaningful and quantitative comparisons, however, can be difficult for a variety of reasons. Here, we use tree-ring based hydroclimate reconstructions to discuss some best practices for paleoclimate-model comparisons, highlighting recent studies that have successfully used this approach. These analyses have improved our understanding of the Medieval-era megadroughts, ocean forcing of large scale drought patterns, and even climate change contributions to future drought risk. Additional work is needed, however, to better reconcile and formalize uncertainties across observed, modeled, and reconstructed variables. In this regard, process based forward models of proxy-systems will likely be a critical tool moving forward.
Current and future constraints on extended Bekenstein-type models for a varying fine-structure constant

NASA Astrophysics Data System (ADS)

Alves, C. S.; Leite, A. C. O.; Martins, C. J. A. P.; Silva, T. A.; Berge, S. A.; Silva, B. S. A.

2018-01-01

There is a growing interest in astrophysical tests of the stability of dimensionless fundamental couplings, such as the fine-structure constant α , as an optimal probe of new physics. The imminent arrival of the ESPRESSO spectrograph will soon enable significant gains in the precision and accuracy of these tests and widen the range of theoretical models that can be tightly constrained. Here we illustrate this by studying proposed extensions of the Bekenstein-type models for the evolution of α that allow different couplings of the scalar field to both dark matter and dark energy. We use a combination of current astrophysical and local laboratory data (from tests with atomic clocks) to show that these couplings are constrained to parts per million level, with the constraints being dominated by the atomic clocks. We also quantify the expected improvements from ESPRESSO and other future spectrographs, and briefly discuss possible observational strategies, showing that these facilities can improve current constraints by more than an order of magnitude.
Modeling the Effects of Drought, Fire, Beetles, and Management on Future Carbon Cycling in the Western US

NASA Astrophysics Data System (ADS)

Buotte, P.; Law, B. E.; Hicke, J. A.; Hudiburg, T. W.; Levis, S.; Kent, J.

2017-12-01

Fire and beetle outbreaks can have substantial impacts on forest structure, composition, and function and these types of disturbances are expected to increase in the future. Therefore understanding the ecological impacts of these disturbances into the future is important. We used ecosystem process modeling to estimate the future occurrence of fire and beetle outbreaks and their impacts on forest resilience and carbon sequestration. We modified the Community Land Model (CLM4.5) to better represent forest growth and mortality in the western US through multiple avenues: 1) we increased the ecological resolution to recognize 14 forest types common to the region; 2) we improved CLM4.5's ability to handle drought stress by adding forest type-specific controls on stomatal conductance and increased rates of leaf shed during periods of low soil moisture; 3) we developed and implemented a mechanistic model of beetle population growth and subsequent tree mortality; 4) we modified the current fire module to account for more refined forest types; and 5) we developed multiple scenarios of harvest based on past harvest rates and proposed changes in land management policies. We ran CLM4.5 in offline mode with climate forcing data. We compare future forest growth rates and carbon sequestration with historical metrics to estimate the combined influence of future disturbances on forest composition and carbon sequestration in the western US.
Improving assessment and modelling of climate change impacts on global terrestrial biodiversity.

PubMed

McMahon, Sean M; Harrison, Sandy P; Armbruster, W Scott; Bartlein, Patrick J; Beale, Colin M; Edwards, Mary E; Kattge, Jens; Midgley, Guy; Morin, Xavier; Prentice, I Colin

2011-05-01

Understanding how species and ecosystems respond to climate change has become a major focus of ecology and conservation biology. Modelling approaches provide important tools for making future projections, but current models of the climate-biosphere interface remain overly simplistic, undermining the credibility of projections. We identify five ways in which substantial advances could be made in the next few years: (i) improving the accessibility and efficiency of biodiversity monitoring data, (ii) quantifying the main determinants of the sensitivity of species to climate change, (iii) incorporating community dynamics into projections of biodiversity responses, (iv) accounting for the influence of evolutionary processes on the response of species to climate change, and (v) improving the biophysical rule sets that define functional groupings of species in global models. Published by Elsevier Ltd.
Improved Crystal Quality by Detached Solidification in Microgravity

NASA Technical Reports Server (NTRS)

Regel, Liya L.; Wilcox, William R.

1999-01-01

Directional solidification in microgravity has often led to ingots that grew with little or no contact with the ampoule wall. When this occurred, crystallographic perfection was usually greatly improved -- often by several orders of magnitude. Unfortunately, until recently the true mechanisms underlying detached solidification were unknown. As a consequence, flight experiments yielded erratic results. Within the past four years, we have developed a new theoretical model that explains many of the flight results. This model gives rise to predictions of the conditions required to yield detached solidification, both in microgravity and on earth. A discussion of models of detachment, the meniscus models and results of theoretical modeling, and future plans are presented.
Improvement of capabilities of the Distributed Electrochemistry Modeling Tool for investigating SOFC long term performance

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

Gonzalez Galdamez, Rinaldo A.; Recknagle, Kurtis P.

2012-04-30

This report provides an overview of the work performed for Solid Oxide Fuel Cell (SOFC) modeling during the 2012 Winter/Spring Science Undergraduate Laboratory Internship at Pacific Northwest National Laboratory (PNNL). A brief introduction on the concept, operation basics and applications of fuel cells is given for the general audience. Further details are given regarding the modifications and improvements of the Distributed Electrochemistry (DEC) Modeling tool developed by PNNL engineers to model SOFC long term performance. Within this analysis, a literature review on anode degradation mechanisms is explained and future plans of implementing these into the DEC modeling tool are alsomore » proposed.« less
Comparing projections of industrial energy demand and greenhouse gas emissions in long-term energy models

DOE PAGES

Edelenbosch, O. Y.; Kermeli, K.; Crijns-Graus, W.; ...

2017-01-09

The industry sector consumes more energy and emits more greenhouse gas (GHG) emissions than any other end-use sector. Integrated assessment models (IAMs) and energy system models have been widely used to evaluate climate policy at a global level, and include a representation of industrial energy use. In this study, the projected industrial energy use and accompanying GHG emissions, as well as the model structure of multiple long-term energy models are compared. The models show varying degrees to which energy consumption is decoupled from GDP growth in the future. In all models, the sector remains mostly (>50%) reliant on fossil energymore » through 2100 in a reference scenario (i.e., absent emissions mitigation policies), though there is significant divergence in the projected ability to switch to alternative fuels to mitigate GHG emissions. Among the set analyzed here, the more technologically detailed models tend to have less capacity for switching from fossil fuels to electricity. This highlights the importance of understanding of economy-wide mitigation responses and costs as an area for future improvement. Analyzing industry subsector material and energy use details can improve the ability to interpret results, and provide insight in feasibility of how emissions reduction can be achieved.« less
Comparing projections of industrial energy demand and greenhouse gas emissions in long-term energy models

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

Edelenbosch, O. Y.; Kermeli, K.; Crijns-Graus, W.

The industry sector consumes more energy and emits more greenhouse gas (GHG) emissions than any other end-use sector. Integrated assessment models (IAMs) and energy system models have been widely used to evaluate climate policy at a global level, and include a representation of industrial energy use. In this study, the projected industrial energy use and accompanying GHG emissions, as well as the model structure of multiple long-term energy models are compared. The models show varying degrees to which energy consumption is decoupled from GDP growth in the future. In all models, the sector remains mostly (>50%) reliant on fossil energymore » through 2100 in a reference scenario (i.e., absent emissions mitigation policies), though there is significant divergence in the projected ability to switch to alternative fuels to mitigate GHG emissions. Among the set analyzed here, the more technologically detailed models tend to have less capacity for switching from fossil fuels to electricity. This highlights the importance of understanding of economy-wide mitigation responses and costs as an area for future improvement. Analyzing industry subsector material and energy use details can improve the ability to interpret results, and provide insight in feasibility of how emissions reduction can be achieved.« less
Acceptance versus Change in Behavior Therapy: An Interview with Neil Jacobson.

ERIC Educational Resources Information Center

Hines, Max

1998-01-01

Neil Jacobson is a leader in research-based efforts to improve behavioral couples therapy. This interview focuses on his professional journey toward an integrative model, as well as his thoughts about the future directions of behavioral therapy and family counseling. The integrative-couples therapy model is described and discussed. (Author/EMK)
Chapter Innovators Guide, 2000: Models of Innovation Award Winners.

ERIC Educational Resources Information Center

National FFA Organization, Indianapolis, IN.

This guide presents the Future Farmers of America (FFA) 2000 Model of Innovation award winners' projects. Chapters demonstrated abilities to identify goals and objectives, create a workable plan of action, attain and evaluate results, and identify items learned and ways to improve. Chapter 1 discusses the FFA National Chapter Award program that…
Big A Systems Architecture - From Strategy to Design: Systems Architecting in DoD

DTIC Science & Technology

2013-04-01

and modeling standards such as Systems Modeling Language ( SysML ). These tools have great potential to facilitate col- laboration and improve the...MBSE and SysML to Big “A” systems architecting and the potential ben- efits to acquisition outcomes are planned to be the subject of a future article
Collaborative Project: Building improved optimized parameter estimation algorithms to improve methane and nitrogen fluxes in a climate model

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

Mahowald, Natalie

Soils in natural and managed ecosystems and wetlands are well known sources of methane, nitrous oxides, and reactive nitrogen gases, but the magnitudes of gas flux to the atmosphere are still poorly constrained. Thus, the reasons for the large increases in atmospheric concentrations of methane and nitrous oxide since the preindustrial time period are not well understood. The low atmospheric concentrations of methane and nitrous oxide, despite being more potent greenhouse gases than carbon dioxide, complicate empirical studies to provide explanations. In addition to climate concerns, the emissions of reactive nitrogen gases from soils are important to the changing nitrogenmore » balance in the earth system, subject to human management, and may change substantially in the future. Thus improved modeling of the emission fluxes of these species from the land surface is important. Currently, there are emission modules for methane and some nitrogen species in the Community Earth System Model’s Community Land Model (CLM-ME/N); however, there are large uncertainties and problems in the simulations, resulting in coarse estimates. In this proposal, we seek to improve these emission modules by combining state-of-the-art process modules for emissions, available data, and new optimization methods. In earth science problems, we often have substantial data and knowledge of processes in disparate systems, and thus we need to combine data and a general process level understanding into a model for projections of future climate that are as accurate as possible. The best methodologies for optimization of parameters in earth system models are still being developed. In this proposal we will develop and apply surrogate algorithms that a) were especially developed for computationally expensive simulations like CLM-ME/N models; b) were (in the earlier surrogate optimization Stochastic RBF) demonstrated to perform very well on computationally expensive complex partial differential equations in earth science with limited numbers of simulations; and, c) will be (as part of the proposed research) significantly improved both by adding asynchronous parallelism, early truncation of unsuccessful simulations, and the improvement of both serial and parallel performance by the use of derivative and sensitivity information from global and local surrogate approximations S(x). The algorithm development and testing will be focused on the CLM-ME/N model application, but the methods are general and are expected to also perform well on optimization for parameter estimation of other climate models and other classes of continuous multimodal optimization problems arising from complex simulation models. In addition, this proposal will compile available datasets of emissions of methane, nitrous oxides and reactive nitrogen species and develop protocols for site level comparisons with the CLM-ME/N. Once the model parameters are optimized against site level data, the model will be simulated at the global level and compared to atmospheric concentration measurements for the current climate, and future emissions will be estimated using climate change as simulated by the CESM. This proposal combines experts in earth system modeling, optimization, computer science, and process level understanding of soil gas emissions in an interdisciplinary team in order to improve the modeling of methane and nitrogen gas emissions. This proposal thus meets the requirements of the SciDAC RFP, by integrating state-of-the-art computer science and earth system to build an improved earth system model.« less
Opportunities for future supernova studies of cosmic acceleration.

PubMed

Weller, J; Albrecht, A

2001-03-05

We investigate the potential of a future supernova data set, as might be obtained by the proposed SNAP satellite, to discriminate among different "dark energy" theories that describe an accelerating Universe. We find that many such models can be distinguished with a fit to the effective pressure-to-density ratio w of this energy. More models can be distinguished when the effective slope dw/dz of a changing w is also fit, but only if our knowledge of the current mass density Omega(m) is improved. We investigate the use of "fitting functions" to interpret luminosity distance data from supernova searches.
Evidence base and future research directions in the management of low back pain.

PubMed

Abbott, Allan

2016-03-18

Low back pain (LBP) is a prevalent and costly condition. Awareness of valid and reliable patient history taking, physical examination and clinical testing is important for diagnostic accuracy. Stratified care which targets treatment to patient subgroups based on key characteristics is reliant upon accurate diagnostics. Models of stratified care that can potentially improve treatment effects include prognostic risk profiling for persistent LBP, likely response to specific treatment based on clinical prediction models or suspected underlying causal mechanisms. The focus of this editorial is to highlight current research status and future directions for LBP diagnostics and stratified care.
US Navy Global and Regional Wave Modeling

DTIC Science & Technology

2014-09-01

Future plans call for increasing the resolution to 0.5 degree, upgrading to WW3 version 4, and including the ...NAVOCEANO WW3 system is in the early stages, and a number of key shortcomings have been identified for future improvement. The multigrid sys- tem...J. Shriver, R. Helber, P. Spence, S . Carroll, O.M. Smedstad, and B. Lunde. 2011. Validation Test Report for the Navy Coupled Ocean
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.

Divergent projections of future land use in the United States arising from different models and scenarios

USGS Publications Warehouse

Sohl, Terry L.; Wimberly, Michael; Radeloff, Volker C.; Theobald, David M.; Sleeter, Benjamin M.

2016-01-01

A variety of land-use and land-cover (LULC) models operating at scales from local to global have been developed in recent years, including a number of models that provide spatially explicit, multi-class LULC projections for the conterminous United States. This diversity of modeling approaches raises the question: how consistent are their projections of future land use? We compared projections from six LULC modeling applications for the United States and assessed quantitative, spatial, and conceptual inconsistencies. Each set of projections provided multiple scenarios covering a period from roughly 2000 to 2050. Given the unique spatial, thematic, and temporal characteristics of each set of projections, individual projections were aggregated to a common set of basic, generalized LULC classes (i.e., cropland, pasture, forest, range, and urban) and summarized at the county level across the conterminous United States. We found very little agreement in projected future LULC trends and patterns among the different models. Variability among scenarios for a given model was generally lower than variability among different models, in terms of both trends in the amounts of basic LULC classes and their projected spatial patterns. Even when different models assessed the same purported scenario, model projections varied substantially. Projections of agricultural trends were often far above the maximum historical amounts, raising concerns about the realism of the projections. Comparisons among models were hindered by major discrepancies in categorical definitions, and suggest a need for standardization of historical LULC data sources. To capture a broader range of uncertainties, ensemble modeling approaches are also recommended. However, the vast inconsistencies among LULC models raise questions about the theoretical and conceptual underpinnings of current modeling approaches. Given the substantial effects that land-use change can have on ecological and societal processes, there is a need for improvement in LULC theory and modeling capabilities to improve acceptance and use of regional- to national-scale LULC projections for the United States and elsewhere.
Accounting for Landscape Heterogeneity Improves Spatial Predictions of Tree Vulnerability to Drought

NASA Astrophysics Data System (ADS)

Schwantes, A. M.; Parolari, A.; Swenson, J. J.; Johnson, D. M.; Domec, J. C.; Jackson, R. B.; Pelak, N. F., III; Porporato, A. M.

2017-12-01

Globally, as climate change continues, forest vulnerability to droughts and heatwaves is increasing, but vulnerability differs regionally and locally depending on landscape position. However, most models used in forecasting forest responses to heatwaves and droughts do not incorporate relevant spatial processes. To improve predictions of spatial tree vulnerability, we employed a non-linear stochastic model of soil moisture dynamics across a landscape, accounting for spatial differences in aspect, topography, and soils. Our unique approach integrated plant hydraulics and landscape processes, incorporating effects from lateral redistribution of water using a topographic index and radiation and temperature differences attributable to aspect. Across a watershed in central Texas we modeled dynamic water stress for a dominant tree species, Juniperus ashei. We compared our results to a detailed spatial dataset of drought-impacted areas (>25% canopy loss) derived from remote sensing during the severe 2011 drought. We then projected future dynamic water stress through the 21st century using climate projections from 10 global climate models under two scenarios, and compared models with and without landscape heterogeneity. Within this watershed, 42% of J. ashei dominated systems were impacted by the 2011 drought. Modeled dynamic water stress tracked these spatial patterns of observed drought-impacted areas. Total accuracy increased from 59%, when accounting only for soil variability, to 73% when including lateral redistribution of water and radiation and temperature effects. Dynamic water stress was projected to increase through the 21st century, with only minimal buffering from the landscape. During the hotter and more severe droughts projected in the 21st century, up to 90% of the watershed crossed a dynamic water stress threshold associated with canopy loss in 2011. Favorable microsites may exist across a landscape where trees can persist; however, if future droughts are too severe, the buffering capacity of a heterogenous landscape could be overwhelmed. Incorporating spatial data will improve projections of future tree water stress and identification of potential resilient refugia.
A model for estimating the impact of changes in children's vaccines.

PubMed

Simpson, K N; Biddle, A K; Rabinovich, N R

1995-12-01

To assist in strategic planning for the improvement of vaccines and vaccine programs, an economic model was developed and tested that estimates the potential impact of vaccine innovations on health outcomes and costs associated with vaccination and illness. A multistep, iterative process of data extraction/integration was used to develop the model and the scenarios. Parameter replication, sensitivity analysis, and expert review were used to validate the model. The greatest impact on the improvement of health is expected to result from the production of less reactogenic vaccines that require fewer inoculations for immunity. The greatest economic impact is predicted from improvements that decrease the number of inoculations required. Scenario analysis may be useful for integrating health outcomes and economic data into decision making. For childhood infections, this analysis indicates that large cost savings can be achieved in the future if we can improve vaccine efficacy so that the number of required inoculations is reduced. Such an improvement represents a large potential "payback" for the United States and might benefit other countries.
Response of acid mobilization of iron-containing mineral dust to improvement of air quality projected in the future

NASA Astrophysics Data System (ADS)

Ito, A.; Xu, L.

2014-04-01

Acidification of dust aerosols may increase aerosol iron (Fe) solubility, which is linked to mineral properties. Combustion aerosols can also elevate aerosol iron solubility when aerosol loading is low. Here, we use an atmospheric chemical transport model to investigate the deposition of filterable iron and its response to changes in anthropogenic emissions of both combustion aerosols and precursor gases. By introducing three classes of iron-containing minerals into the detailed aerosol chemistry model, we provide a theoretical examination of the effects of different dissolution behaviors on the acid mobilization of iron. Comparisons of modeled Fe dissolution curves with the measured dissolution rates for African, east Asian, and Australian dust samples show overall good agreement under acidic conditions. The improved treatment of Fe in mineral dust and its dissolution scheme results in reasonable predictive capability for iron solubility over the oceans in the Northern Hemisphere. Our model results suggest that the improvement of air quality projected in the future will lead to a decrease of the filterable iron deposition from iron-containing mineral dust to the eastern North Pacific due to less acidification in Asian dust, which is mainly associated with the reduction of nitrogen oxides (NOx) emissions. These results could have important implications for iron fertilization of phytoplankton growth, and highlight the necessity of improving the process-based quantitative understanding of the response of the chemical modification in iron-containing minerals to environmental changes.
Communicating Ocean Sciences to Informal Audiences (COSIA): Universities, Oceanographic Institutions, Science Centers and Aquariums Working Together to Improve Ocean Education and Public Outreach

NASA Astrophysics Data System (ADS)

Glenn, S.; McDonnell, J.; Halversen, C.; Zimmerman, T.; Ingram, L.

2007-12-01

Ocean observatories have already demonstrated their ability to maintain long-term time series, capture episodic events, provide context for improved shipboard sampling, and improve accessibility to a broader range of participants. Communicating Ocean Sciences, an already existing college course from COSEE-California has demonstrated its ability to teach future scientists essential communication skills. The NSF-funded Communicating Ocean Sciences to Informal Audiences (COSIA) project has leveraged these experiences and others to demonstrate a long-term model for promoting effective science communication skills and techniques applicable to diverse audiences. The COSIA effort is one of the pathfinders for ensuring that the new scientific results from the increasing U.S. investments in ocean observatories is effectively communicated to the nation, and will serve as a model for other fields. Our presentation will describe a long-term model for promoting effective science communication skills and techniques applicable to diverse audiences. COSIA established partnerships between informal science education institutions and universities nationwide to facilitate quality outreach by scientists and the delivery of rigorous, cutting edge science by informal educators while teaching future scientists (college students) essential communication skills. The COSIA model includes scientist-educator partnerships that develop and deliver a college course that teaches communication skills through the understanding of learning theory specifically related to informal learning environments and the practice of these skills at aquariums and science centers. The goals of COSIA are to: provide a model for establishing substantive, long-term partnerships between scientists and informal science education institutions to meet their respective outreach needs; provide future scientists with experiences delivering outreach and promoting the broader impact of research; and provide diverse role models and inquiry-based ocean sciences activities for children and families visiting informal institutions. The following COSIA partners have taught the course: Hampton University - Virginia Aquarium; Oregon State University - Hatfield Marine Science Visitor's Center; Rutgers University - Liberty Science Center; University of California, Berkeley - Lawrence Hall of Science; University of Southern California - Aquarium of the Pacific; and Scripps Institution of Oceanography - Birch Aquarium. Communicating Ocean Sciences has also been taught at Stanford, Woods Hole Oceanographic Institute, University of Oregon (GK-12 program), University of Washington, and others. Data from surveys of students demonstrates improvement in their understanding of how people learn and how to effectively communicate. Providing college students with a background in current learning theory, and applying that theory through practical science communication experiences, will empower future generations of scientists to meet the communication challenges they will encounter in their careers.
The effects of future nationwide forest transition to discharge in the 21st century with regard to general circulation model climate change scenarios.

PubMed

Mouri, Goro; Nakano, Katsuhiro; Tsuyama, Ikutaro; Tanaka, Nobuyuki

2016-08-01

Forest disturbance (or land-cover change) and climatic variability are commonly recognised as two major drivers interactively influencing hydrology in forested watersheds. Future climate changes and corresponding changes in forest type and distribution are expected to generate changes in rainfall runoff that pose a threat to river catchments. It is therefore important to understand how future climate changes will effect average rainfall distribution and temperature and what effect this will have upon forest types across Japan. Recent deforestation of the present-day coniferous forest and expected increases in evergreen forest are shown to influence runoff processes and, therefore, to influence future runoff conditions. We strongly recommend that variations in forest type be considered in future plans to ameliorate projected climate changes. This will help to improve water retention and storage capacities, enhance the flood protection function of forests, and improve human health. We qualitatively assessed future changes in runoff including the effects of variation in forest type across Japan. Four general circulation models (GCMs) were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields: the Model for Interdisciplinary Research on Climate (MIROC), the Meteorological Research Institute Atmospheric General Circulation Model (MRI-GCM), the Hadley Centre Global Environment Model (HadGEM), and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model. The simulations consisted of an ensemble including multiple physics configurations and different reference concentration pathways (RCP2.6, 4.5, and 8.5), the results of which have produced monthly data sets for the whole of Japan. The impacts of future climate changes on forest type in Japan are based on the balance amongst changes in rainfall distribution, temperature and hydrological factors. Methods for assessing the impact of such changes include the Catchment Simulator modelling frameworks based on the Minimal Advanced Treatments of Surface Interaction and Runoff (MATSIRO) model, which was expanded to estimate discharge by incorporating the effects of forest-type transition across the whole of Japan. The results indicated that, by the 2090s, annual runoff will increase above present-day values. Increases in annual variation in runoff by the 2090s was predicted to be around 14.1% when using the MRI-GCM data and 44.4% when using the HadGEM data. Analysis by long-term projection showed the largest increases in runoff in the 2090s were related to the type of forest, such as evergreen. Increased runoff can have negative effects on both society and the environment, including increased flooding events, worsened water quality, habitat destruction and changes to the forest moisture-retaining function. Prediction of the impacts of future climate change on water generation is crucial for effective environmental planning and management. Copyright © 2016 Elsevier Inc. All rights reserved.
Re-Shuffling of Species with Climate Disruption: A No-Analog Future for California Birds?

PubMed Central

Stralberg, Diana; Jongsomjit, Dennis; Howell, Christine A.; Snyder, Mark A.; Alexander, John D.; Wiens, John A.; Root, Terry L.

2009-01-01

By facilitating independent shifts in species' distributions, climate disruption may result in the rapid development of novel species assemblages that challenge the capacity of species to co-exist and adapt. We used a multivariate approach borrowed from paleoecology to quantify the potential change in California terrestrial breeding bird communities based on current and future species-distribution models for 60 focal species. Projections of future no-analog communities based on two climate models and two species-distribution-model algorithms indicate that by 2070 over half of California could be occupied by novel assemblages of bird species, implying the potential for dramatic community reshuffling and altered patterns of species interactions. The expected percentage of no-analog bird communities was dependent on the community scale examined, but consistent geographic patterns indicated several locations that are particularly likely to host novel bird communities in the future. These no-analog areas did not always coincide with areas of greatest projected species turnover. Efforts to conserve and manage biodiversity could be substantially improved by considering not just future changes in the distribution of individual species, but including the potential for unprecedented changes in community composition and unanticipated consequences of novel species assemblages. PMID:19724641
Genetic Diversity and Ecological Niche Modelling of Wild Barley: Refugia, Large-Scale Post-LGM Range Expansion and Limited Mid-Future Climate Threats?

PubMed Central

Russell, Joanne; van Zonneveld, Maarten; Dawson, Ian K.; Booth, Allan; Waugh, Robbie; Steffenson, Brian

2014-01-01

Describing genetic diversity in wild barley (Hordeum vulgare ssp. spontaneum) in geographic and environmental space in the context of current, past and potential future climates is important for conservation and for breeding the domesticated crop (Hordeum vulgare ssp. vulgare). Spatial genetic diversity in wild barley was revealed by both nuclear- (2,505 SNP, 24 nSSR) and chloroplast-derived (5 cpSSR) markers in 256 widely-sampled geo-referenced accessions. Results were compared with MaxEnt-modelled geographic distributions under current, past (Last Glacial Maximum, LGM) and mid-term future (anthropogenic scenario A2, the 2080s) climates. Comparisons suggest large-scale post-LGM range expansion in Central Asia and relatively small, but statistically significant, reductions in range-wide genetic diversity under future climate. Our analyses support the utility of ecological niche modelling for locating genetic diversity hotspots and determine priority geographic areas for wild barley conservation under anthropogenic climate change. Similar research on other cereal crop progenitors could play an important role in tailoring conservation and crop improvement strategies to support future human food security. PMID:24505252
Improving estuary models by reducing uncertainties associated with river flows

NASA Astrophysics Data System (ADS)

Robins, Peter E.; Lewis, Matt J.; Freer, Jim; Cooper, David M.; Skinner, Christopher J.; Coulthard, Tom J.

2018-07-01

To mitigate against future changes to estuaries such as water quality, catchment and estuary models can be coupled to simulate the transport of harmful pathogenic viruses, pollutants and nutrients from their terrestrial sources, through the estuary and to the coast. To predict future changes to estuaries, daily mean river flow projections are typically used. We show that this approach cannot resolve higher frequency discharge events that have large impacts to estuarine dilution, contamination and recovery for two contrasting estuaries. We therefore characterise sub-daily scale flow variability and propagate this through an estuary model to provide robust estimates of impacts for the future. River flow data (35-year records at 15-min sampling) were used to characterise variabilities in storm hydrograph shapes and simulate the estuarine response. In particular, we modelled a fast-responding catchment-estuary system (Conwy, UK), where the natural variability in hydrograph shapes generated large variability in estuarine circulation that was not captured when using daily-averaged river forcing. In the extreme, the freshwater plume from a 'flash' flood (lasting <12 h) was underestimated by up to 100% - and the response to nutrient loading was underestimated further still. A model of a slower-responding system (Humber, UK), where hydrographs typically last 2-4 days, showed less variability in estuarine circulation and good approximation with daily-averaged flow forcing. Our result has implications for entire system impact modelling; when we determine future changes to estuaries, some systems will need higher resolution future river flow estimates.
Improving simulated long-term responses of vegetation to temperature and precipitation extremes using the ACME land model

NASA Astrophysics Data System (ADS)

Ricciuto, D. M.; Warren, J.; Guha, A.

2017-12-01

While carbon and energy fluxes in current Earth system models generally have reasonable instantaneous responses to extreme temperature and precipitation events, they often do not adequately represent the long-term impacts of these events. For example, simulated net primary productivity (NPP) may decrease during an extreme heat wave or drought, but may recover rapidly to pre-event levels following the conclusion of the extreme event. However, field measurements indicate that long-lasting damage to leaves and other plant components often occur, potentially affecting the carbon and energy balance for months after the extreme event. The duration and frequency of such extreme conditions is likely to shift in the future, and therefore it is critical for Earth system models to better represent these processes for more accurate predictions of future vegetation productivity and land-atmosphere feedbacks. Here we modify the structure of the Accelerated Climate Model for Energy (ACME) land surface model to represent long-term impacts and test the improved model against observations from experiments that applied extreme conditions in growth chambers. Additionally, we test the model against eddy covariance measurements that followed extreme conditions at selected locations in North America, and against satellite-measured vegetation indices following regional extreme events.
Launch and Landing Effects Ground Operations (LLEGO) Model

NASA Technical Reports Server (NTRS)

2008-01-01

LLEGO is a model for understanding recurring launch and landing operations costs at Kennedy Space Center for human space flight. Launch and landing operations are often referred to as ground processing, or ground operations. Currently, this function is specific to the ground operations for the Space Shuttle Space Transportation System within the Space Shuttle Program. The Constellation system to follow the Space Shuttle consists of the crewed Orion spacecraft atop an Ares I launch vehicle and the uncrewed Ares V cargo launch vehicle. The Constellation flight and ground systems build upon many elements of the existing Shuttle flight and ground hardware, as well as upon existing organizations and processes. In turn, the LLEGO model builds upon past ground operations research, modeling, data, and experience in estimating for future programs. Rather than to simply provide estimates, the LLEGO model s main purpose is to improve expenses by relating complex relationships among functions (ground operations contractor, subcontractors, civil service technical, center management, operations, etc.) to tangible drivers. Drivers include flight system complexity and reliability, as well as operations and supply chain management processes and technology. Together these factors define the operability and potential improvements for any future system, from the most direct to the least direct expenses.
Modeling paradigms for medical diagnostic decision support: a survey and future directions.

PubMed

Wagholikar, Kavishwar B; Sundararajan, Vijayraghavan; Deshpande, Ashok W

2012-10-01

Use of computer based decision tools to aid clinical decision making, has been a primary goal of research in biomedical informatics. Research in the last five decades has led to the development of Medical Decision Support (MDS) applications using a variety of modeling techniques, for a diverse range of medical decision problems. This paper surveys literature on modeling techniques for diagnostic decision support, with a focus on decision accuracy. Trends and shortcomings of research in this area are discussed and future directions are provided. The authors suggest that-(i) Improvement in the accuracy of MDS application may be possible by modeling of vague and temporal data, research on inference algorithms, integration of patient information from diverse sources and improvement in gene profiling algorithms; (ii) MDS research would be facilitated by public release of de-identified medical datasets, and development of opensource data-mining tool kits; (iii) Comparative evaluations of different modeling techniques are required to understand characteristics of the techniques, which can guide developers in choice of technique for a particular medical decision problem; and (iv) Evaluations of MDS applications in clinical setting are necessary to foster physicians' utilization of these decision aids.
Use of the Job Model Concept to Guide Job Description Procedures for Army Officers.

ERIC Educational Resources Information Center

Whitmore, Paul G.

The objective of Work Unit SKYGUARD has been to facilitate the development of an improved Air Defense Officers Advanced Course (C-22) by the U.S. Army Air Defense School. Focus is on techniques for improving the completeness and relevance of the instructional objectives with respect to future job requirements. The job description procedures…
Unmanned Aerial Systems (UAS) Evaluation of Routine Atmospheric Sounding Measurements using Unmanned Systems (ERASMUS)

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

De Boer, Gijs

Data were collected to improve understanding of the Arctic troposphere, and to provide researchers with a focused case-study period for future observational and modeling studies pertaining to Arctic atmospheric processes.
Artificial Intelligent Platform as Decision Tool for Asset Management, Operations and Maintenance.

PubMed

2018-01-04

An Artificial Intelligence (AI) system has been developed and implemented for water, wastewater and reuse plants to improve management of sensors, short and long term maintenance plans, asset and investment management plans. It is based on an integrated approach to capture data from different computer systems and files. It adds a layer of intelligence to the data. It serves as a repository of key current and future operations and maintenance conditions that a plant needs have knowledge of. With this information, it is able to simulate the configuration of processes and assets for those conditions to improve or optimize operations, maintenance and asset management, using the IViewOps (Intelligent View of Operations) model. Based on the optimization through model runs, it is able to create output files that can feed data to other systems and inform the staff regarding optimal solutions to the conditions experienced or anticipated in the future.
The Navy Oceanic Vertical Aerosol Model

DTIC Science & Technology

1993-12-01

development of models from the basic research community in the future. Another area of concern is the use of the model in close-in coastal areas. Compensation...34windows" exist in the molecular absorption of the electromagnetic energy through which trans- missions in IR communication can take place. In these...commercial market ) will greatly improve the overall operation of the model. It will do this in conjunction with the optical visibility by pinning down
Team-Based Care with Pharmacists to Improve Blood Pressure: a Review of Recent Literature.

PubMed

Kennelty, Korey A; Polgreen, Linnea A; Carter, Barry L

2018-01-18

We review studies published since 2014 that examined team-based care strategies and involved pharmacists to improve blood pressure (BP). We then discuss opportunities and challenges to sustainment of team-based care models in primary care clinics. Multiple studies presented in this review have demonstrated that team-based care including pharmacists can improve BP management. Studies highlighted the cost-effectiveness of a team-based pharmacy intervention for BP control in primary care clinics. Little information was found on factors influencing sustainability of team-based care interventions to improve BP control. Future work is needed to determine the best populations to target with team-based BP programs and how to implement team-based approaches utilizing pharmacists in diverse clinical settings. Future studies need to not only identify unmet clinical needs but also address reimbursement issues and stakeholder engagement that may impact sustainment of team-based care interventions.
Predicting healthcare trajectories from medical records: A deep learning approach.

PubMed

Pham, Trang; Tran, Truyen; Phung, Dinh; Venkatesh, Svetha

2017-05-01

Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, stored in electronic medical records are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors and models patient health state trajectories by the memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces methods to handle irregularly timed events by moderating the forgetting and consolidation of memory. DeepCare also explicitly models medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden - diabetes and mental health - the results show improved prediction accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.
State-based versus reward-based motivation in younger and older adults.

PubMed

Worthy, Darrell A; Cooper, Jessica A; Byrne, Kaileigh A; Gorlick, Marissa A; Maddox, W Todd

2014-12-01

Recent decision-making work has focused on a distinction between a habitual, model-free neural system that is motivated toward actions that lead directly to reward and a more computationally demanding goal-directed, model-based system that is motivated toward actions that improve one's future state. In this article, we examine how aging affects motivation toward reward-based versus state-based decision making. Participants performed tasks in which one type of option provided larger immediate rewards but the alternative type of option led to larger rewards on future trials, or improvements in state. We predicted that older adults would show a reduced preference for choices that led to improvements in state and a greater preference for choices that maximized immediate reward. We also predicted that fits from a hybrid reinforcement-learning model would indicate greater model-based strategy use in younger than in older adults. In line with these predictions, older adults selected the options that maximized reward more often than did younger adults in three of the four tasks, and modeling results suggested reduced model-based strategy use. In the task where older adults showed similar behavior to younger adults, our model-fitting results suggested that this was due to the utilization of a win-stay-lose-shift heuristic rather than a more complex model-based strategy. Additionally, within older adults, we found that model-based strategy use was positively correlated with memory measures from our neuropsychological test battery. We suggest that this shift from state-based to reward-based motivation may be due to age related declines in the neural structures needed for more computationally demanding model-based decision making.
Vulnerable Population Challenges in the Transformation of Cancer Care.

PubMed

Meneses, Karen; Landier, Wendy; Dionne-Odom, J Nicholas

2016-05-01

To consider current trends and future strategies that will bring about change in cancer care delivery for vulnerable populations. Institute of Medicine reports, literature review, clinical practice observations and experiences. Vulnerable populations are older adults, both minorities and the underserved, children, and individuals at end of life. These groups pose unique challenges that require health system changes and innovative nursing models to assure access to patient-centered care in the future. In the future, attention to the needs of vulnerable populations, the growing aging cancer population and the improved outcomes in the pediatric and adolescent cancer population will all require new nursing services and models of care. System changes where nursing roles are critical to support the transition to earlier palliative care are projected. Copyright © 2016 Elsevier Inc. All rights reserved.

Performance improvement CME for quality: challenges inherent to the process.

PubMed

Vakani, Farhan Saeed; O'Beirne, Ronan

2015-01-01

The purpose of this paper is to discuss the perspective debates upon the real-time challenges for a three-staged Performance Improvement Continuing Medical Education (PI-CME) model, an innovative and potential approach for future CME, to inform providers to think, prepare and to act proactively. In this discussion, the challenges associated for adopting the American Medical Association's three-staged PI-CME model are reported. Not many institutions in USA are using a three-staged performance improvement model and then customizing it to their own healthcare context for the specific targeted audience. They integrate traditional CME methods with performance and quality initiatives, and linking with CME credits. Overall the US health system is interested in a structured PI-CME model with the potential to improve physicians practicing behaviors. Knowing the dearth of evidence for applying this structured performance improvement methodology into the design of CME activities, and the lack of clarity on challenges inherent to the process that learners and providers encounter. This paper establishes all-important first step to render the set of challenges for a three-staged PI-CME model.
Future Wildfire and Managed Fire Interactions in the Lake Tahoe Basin

NASA Astrophysics Data System (ADS)

Scheller, R.; Kretchun, A.

2017-12-01

Managing large forested landscape in the context of a changing climate and altered disturbance regimes presents new challenges and require integrated assessments of forest disturbance, management, succession, and the carbon cycle. Successful management under these circumstances will require information about trade-offs among multiple objectives and opportunities for spatially optimized landscape-scale management. Improved information about the effects of climate on forest communities, disturbance feedbacks, and the effectiveness of mitigation strategies enables actionable options for landscape managers. We evaluated the effects of fire suppression, wildfires, and forest fuel (thinning) treatments on the long-term carbon storage potential for Lake Tahoe Basin (LTB) forests under various climate futures. We simulated management scenarios that encompass fuel treatments across the larger landscape, beyond the Wildland Urban Interface. We improved upon current fire modeling under climate change via an integrated fire modeling module that, a) explicitly captures the influence of climate, fuels, topography, active fire management (e.g., fire suppression), and fuel treatments, and b) can be parameterized from available data, e.g., remote sensing, field reporting, fire databases, expert opinion. These improvements increase geographic flexibility and decrease reliance on broad historical fire regime statistics - imperfect targets for a no analog future and require minimal parameterization and calibration. We assessed the interactions among fuel treatments, prescribe fire, fire suppression, and stochastically recurring wildfires. Predicted changes in climate and ignition patterns in response to future climatic conditions, vegetation dynamics, and fuel treatments indicate larger potential long-term effects on C emissions, forest structure, and forest composition than prior studies.
Attribution of future US ozone pollution to regional emissions, climate change, long-range transport, and model deficiency

NASA Astrophysics Data System (ADS)

He, H.; Liang, X.-Z.; Lei, H.; Wuebbles, D. J.

2014-10-01

A regional chemical transport model (CTM) is used to quantify the relative contributions of future US ozone pollution from regional emissions, climate change, long-range transport (LRT) of pollutants, and model deficiency. After incorporating dynamic lateral boundary conditions (LBCs) from a global CTM, the representation of present-day US ozone pollution is notably improved. This nested system projects substantial surface ozone trends for 2050's: 6-10 ppbv decreases under the "clean" A1B scenario and ~15 ppbv increases under the "dirty" A1Fi scenario. Among the total trends, regional emissions changes dominate, contributing negative 20-50% in A1B and positive 20-40% in A1Fi, while LRT effects through chemical LBCs and climate changes account for respectively 15-50% and 10-30% in both scenarios. The projection uncertainty due to model biases is region dependent, ranging from -10 to 50%. It is shown that model biases of present-day simulations can propagate into future projections systematically but nonlinearly, and the accurate specification of LBCs is essential for US ozone projections.
Integrating ecophysiology and forest landscape models to improve projections of drought effects under climate change

Treesearch

Eric J. Gustafson; Arjan M.G. De Bruijn; Robert E. Pangle; Jean-Marc Limousin; Nate G. McDowell; William T. Pockman; Brian R. Sturtevant; Jordan D. Muss; Mark E. Kubiske

2015-01-01

Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy-makers to make projections of future ecosystem dynamics under alternative management or policy options, but the links between the fundamental drivers and...
Forecasting timber, biomass, and tree carbon pools with the output of state and transition models

Treesearch

Xiaoping Zhou; Miles A. Hemstrom

2012-01-01

The Integrated Landscape Assessment Project (ILAP) uses spatial vegetation data and state and transition models (STM) to forecast future vegetation conditions and the interacting effects of natural disturbances and management activities. Results from ILAP will help land managers, planners, and policymakers evaluate management strategies that reduce fire risk, improve...
Standard Model and New physics for ɛ'k/ɛk

NASA Astrophysics Data System (ADS)

Kitahara, Teppei

2018-05-01

The first result of the lattice simulation and improved perturbative calculations have pointed to a discrepancy between data on ɛ'k/ɛk and the standard-model (SM) prediction. Several new physics (NP) models can explain this discrepancy, and such NP models are likely to predict deviations of ℬ(K → πvv) from the SM predictions, which can be probed precisely in the near future by NA62 and KOTO experiments. We present correlations between ɛ'k/ɛk and ℬ(K → πvv) in two types of NP scenarios: a box dominated scenario and a Z-penguin dominated one. It is shown that different correlations are predicted and the future precision measurements of K → πvv can distinguish both scenarios.
Minimum and Maximum Potential Contributions to Future Sea Level Rise from Polar Ice Sheets

NASA Astrophysics Data System (ADS)

Deconto, R. M.; Pollard, D.

2017-12-01

New climate and ice-sheet modeling, calibrated to past changes in sea-level, is painting a stark picture of the future fate of the great polar ice sheets if greenhouse gas emissions continue unabated. This is especially true for Antarctica, where a substantial fraction of the ice sheet rests on bedrock more than 500-meters below sea level. Here, we explore the sensitivity of the polar ice sheets to a warming atmosphere and ocean under a range of future greenhouse gas emissions scenarios. The ice sheet-climate-ocean model used here considers time-evolving changes in surface mass balance and sub-ice oceanic melting, ice deformation, grounding line retreat on reverse-sloped bedrock (Marine Ice Sheet Instability), and newly added processes including hydrofracturing of ice shelves in response to surface meltwater and rain, and structural collapse of thick, marine-terminating ice margins with tall ice-cliff faces (Marine Ice Cliff Instability). The simulations improve on previous work by using 1) improved atmospheric forcing from a Regional Climate Model and 2) a much wider range of model physical parameters within the bounds of modern observations of ice dynamical processes (particularly calving rates) and paleo constraints on past ice-sheet response to warming. Approaches to more precisely define the climatic thresholds capable of triggering rapid and potentially irreversible ice-sheet retreat are also discussed, as is the potential for aggressive mitigation strategies like those discussed at the 2015 Paris Climate Conference (COP21) to substantially reduce the risk of extreme sea-level rise. These results, including physics that consider both ice deformation (creep) and calving (mechanical failure of marine terminating ice) expand on previously estimated limits of maximum rates of future sea level rise based solely on kinematic constraints of glacier flow. At the high end, the new results show the potential for more than 2m of global mean sea level rise by 2100, implying that physically plausible upper limits on future sea-level rise might need to be reconsidered.
Advanced Practice Nursing Committee on Process Improvement in Trauma: An Innovative Application of the Strong Model.

PubMed

West, Sarah Katherine

2016-01-01

This article aims to summarize the successes and future implications for a nurse practitioner-driven committee on process improvement in trauma. The trauma nurse practitioner is uniquely positioned to recognize the need for clinical process improvement and enact change within the clinical setting. Application of the Strong Model of Advanced Practice proves to actively engage the trauma nurse practitioner in process improvement initiatives. Through enhancing nurse practitioner professional engagement, the committee aims to improve health care delivery to the traumatically injured patient. A retrospective review of the committee's first year reveals trauma nurse practitioner success in the domains of direct comprehensive care, support of systems, education, and leadership. The need for increased trauma nurse practitioner involvement has been identified for the domains of research and publication.
Using palaeoclimate data to improve models of the Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Phipps, Steven; King, Matt; Roberts, Jason; White, Duanne

2017-04-01

Ice sheet models are the most descriptive tools available to simulate the future evolution of the Antarctic Ice Sheet (AIS), including its contribution towards changes in global sea level. However, our knowledge of the dynamics of the coupled ice-ocean-lithosphere system is inevitably limited, in part due to a lack of observations. Furthemore, to build computationally efficient models that can be run for multiple millennia, it is necessary to use simplified descriptions of ice dynamics. Ice sheet modelling is therefore an inherently uncertain exercise. The past evolution of the AIS provides an opportunity to constrain the description of physical processes within ice sheet models and, therefore, to constrain our understanding of the role of the AIS in driving changes in global sea level. We use the Parallel Ice Sheet Model (PISM) to demonstrate how palaeoclimate data can improve our ability to predict the future evolution of the AIS. A 50-member perturbed-physics ensemble is generated, spanning uncertainty in the parameterisations of three key physical processes within the model: (i) the stress balance within the ice sheet, (ii) basal sliding and (iii) calving of ice shelves. A Latin hypercube approach is used to optimally sample the range of uncertainty in parameter values. This perturbed-physics ensemble is used to simulate the evolution of the AIS from the Last Glacial Maximum ( 21,000 years ago) to present. Palaeoclimate records are then used to determine which ensemble members are the most realistic. This allows us to use data on past climates to directly constrain our understanding of the past contribution of the AIS towards changes in global sea level. Critically, it also allows us to determine which ensemble members are likely to generate the most realistic projections of the future evolution of the AIS.
Using paleoclimate data to improve models of the Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

King, M. A.; Phipps, S. J.; Roberts, J. L.; White, D.

2016-12-01

Ice sheet models are the most descriptive tools available to simulate the future evolution of the Antarctic Ice Sheet (AIS), including its contribution towards changes in global sea level. However, our knowledge of the dynamics of the coupled ice-ocean-lithosphere system is inevitably limited, in part due to a lack of observations. Furthemore, to build computationally efficient models that can be run for multiple millennia, it is necessary to use simplified descriptions of ice dynamics. Ice sheet modeling is therefore an inherently uncertain exercise. The past evolution of the AIS provides an opportunity to constrain the description of physical processes within ice sheet models and, therefore, to constrain our understanding of the role of the AIS in driving changes in global sea level. We use the Parallel Ice Sheet Model (PISM) to demonstrate how paleoclimate data can improve our ability to predict the future evolution of the AIS. A large, perturbed-physics ensemble is generated, spanning uncertainty in the parameterizations of four key physical processes within ice sheet models: ice rheology, ice shelf calving, and the stress balances within ice sheets and ice shelves. A Latin hypercube approach is used to optimally sample the range of uncertainty in parameter values. This perturbed-physics ensemble is used to simulate the evolution of the AIS from the Last Glacial Maximum ( 21,000 years ago) to present. Paleoclimate records are then used to determine which ensemble members are the most realistic. This allows us to use data on past climates to directly constrain our understanding of the past contribution of the AIS towards changes in global sea level. Critically, it also allows us to determine which ensemble members are likely to generate the most realistic projections of the future evolution of the AIS.
Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform.

PubMed

Marshall-Colon, Amy; Long, Stephen P; Allen, Douglas K; Allen, Gabrielle; Beard, Daniel A; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A J; Cox, Donna J; Hart, John C; Hirst, Peter M; Kannan, Kavya; Katz, Daniel S; Lynch, Jonathan P; Millar, Andrew J; Panneerselvam, Balaji; Price, Nathan D; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J; Voit, Eberhard O; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.
Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform

PubMed Central

Marshall-Colon, Amy; Long, Stephen P.; Allen, Douglas K.; Allen, Gabrielle; Beard, Daniel A.; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A. J.; Cox, Donna J.; Hart, John C.; Hirst, Peter M.; Kannan, Kavya; Katz, Daniel S.; Lynch, Jonathan P.; Millar, Andrew J.; Panneerselvam, Balaji; Price, Nathan D.; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G.; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J.; Voit, Eberhard O.; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop. PMID:28555150
A systematic review of cost-effectiveness modeling of pharmaceutical therapies in neuropathic pain: variation in practice, key challenges, and recommendations for the future.

PubMed

Critchlow, Simone; Hirst, Matthew; Akehurst, Ron; Phillips, Ceri; Philips, Zoe; Sullivan, Will; Dunlop, Will C N

2017-02-01

Complexities in the neuropathic-pain care pathway make the condition difficult to manage and difficult to capture in cost-effectiveness models. The aim of this study is to understand, through a systematic review of previous cost-effectiveness studies, some of the key strengths and limitations in data and modeling practices in neuropathic pain. Thus, the aim is to guide future research and practice to improve resource allocation decisions and encourage continued investment to find novel and effective treatments for patients with neuropathic pain. The search strategy was designed to identify peer-reviewed cost-effectiveness evaluations of non-surgical, pharmaceutical therapies for neuropathic pain published since January 2000, accessing five key databases. All identified publications were reviewed and screened according to pre-defined eligibility criteria. Data extraction was designed to reflect key data challenges and approaches to modeling in neuropathic pain and based on published guidelines. The search strategy identified 20 cost-effectiveness analyses meeting the inclusion criteria, of which 14 had original model structures. Cost-effectiveness modeling in neuropathic pain is established and increasing across multiple jurisdictions; however, amongst these studies, there is substantial variation in modeling approach, and there are common limitations. Capturing the effect of treatments upon health outcomes, particularly health-related quality-of-life, is challenging, and the health effects of multiple lines of ineffective treatment, common for patients with neuropathic pain, have not been consistently or robustly modeled. To improve future economic modeling in neuropathic pain, further research is suggested into the effect of multiple lines of treatment and treatment failure upon patient outcomes and subsequent treatment effectiveness; the impact of treatment-emergent adverse events upon patient outcomes; and consistent and appropriate pain measures to inform models. The authors further encourage transparent reporting of inputs used to inform cost-effectiveness models, with robust, comprehensive and clear uncertainty analysis and, where feasible, open-source modeling is encouraged.
IMPROVED ALGORITHMS FOR RADAR-BASED RECONSTRUCTION OF ASTEROID SHAPES

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

Greenberg, Adam H.; Margot, Jean-Luc

We describe our implementation of a global-parameter optimizer and Square Root Information Filter into the asteroid-modeling software shape. We compare the performance of our new optimizer with that of the existing sequential optimizer when operating on various forms of simulated data and actual asteroid radar data. In all cases, the new implementation performs substantially better than its predecessor: it converges faster, produces shape models that are more accurate, and solves for spin axis orientations more reliably. We discuss potential future changes to improve shape's fitting speed and accuracy.
Projected future changes in vegetation in western North America in the 21st century

USGS Publications Warehouse

Xiaoyan, Jiang; Rauscher, Sara A.; Ringler, Todd D.; Lawrence, David M.; Williams, A. Park; Allen, Craig D.; Steiner, Allison L.; Cai, D. Michael; McDowell, Nate G.

2013-01-01

Rapid and broad-scale forest mortality associated with recent droughts, rising temperature, and insect outbreaks has been observed over western North America (NA). Climate models project additional future warming and increasing drought and water stress for this region. To assess future potential changes in vegetation distributions in western NA, the Community Earth System Model (CESM) coupled with its Dynamic Global Vegetation Model (DGVM) was used under the future A2 emissions scenario. To better span uncertainties in future climate, eight sea surface temperature (SST) projections provided by phase 3 of the Coupled Model Intercomparison Project (CMIP3) were employed as boundary conditions. There is a broad consensus among the simulations, despite differences in the simulated climate trajectories across the ensemble, that about half of the needleleaf evergreen tree coverage (from 24% to 11%) will disappear, coincident with a 14% (from 11% to 25%) increase in shrubs and grasses by the end of the twenty-first century in western NA, with most of the change occurring over the latter half of the twenty-first century. The net impact is a ~6 GtC or about 50% decrease in projected ecosystem carbon storage in this region. The findings suggest a potential for a widespread shift from tree-dominated landscapes to shrub and grass-dominated landscapes in western NA because of future warming and consequent increases in water deficits. These results highlight the need for improved process-based understanding of vegetation dynamics, particularly including mortality and the subsequent incorporation of these mechanisms into earth system models to better quantify the vulnerability of western NA forests under climate change.
Future U.S. ozone projections dependence on regional emissions, climate change, long-range transport and differences in modeling design

NASA Astrophysics Data System (ADS)

He, Hao; Liang, Xin-Zhong; Lei, Hang; Wuebbles, Donald J.

2016-03-01

A consistent modeling framework with nested global and regional chemical transport models (CTMs) is used to separate and quantitatively assess the relative contributions to projections of future U.S. ozone pollution from the effects of emissions changes, climate change, long-range transport (LRT) of pollutants, and differences in modeling design. After incorporating dynamic lateral boundary conditions (LBCs) from a global CTM, a regional CTM's representation of present-day U.S. ozone pollution is notably improved, especially relative to results from the regional CTM with fixed LBCs or from the global CTM alone. This nested system of global and regional CTMs projects substantial surface ozone trends for the 2050's: 6-10 ppb decreases under the 'clean' A1B scenario and ∼15 ppb increases under the 'dirty' A1Fi scenario. Among the total trends of future ozone, regional emissions changes dominate, contributing negative 25-60% in A1B and positive 30-45% in A1Fi. Comparatively, climate change contributes positive 10-30%, while LRT effects through changing chemical LBCs account for positive 15-20% in both scenarios, suggesting introducing dynamic LBCs could influence projections of the U.S. future ozone pollution with a magnitude comparable to effects of climate change alone. The contribution to future ozone projections due to differences in modeling design, including model formulations, emissions treatments, and other factors between the global and the nested regional CTMs, is regionally dependent, ranging from negative 20% to positive 25%. It is shown that the model discrepancies for present-day simulations between global and regional CTMs can propagate into future U.S. ozone projections systematically but nonlinearly, especially in California and the Southeast. Therefore in addition to representations of emissions change and climate change, accurate treatment of LBCs for the regional CTM is essential for projecting the future U.S. ozone pollution.
It's all in the timing: modeling isovolumic contraction through development and disease with a dynamic dual electromechanical bioreactor system.

PubMed

Morgan, Kathy Ye; Black, Lauren Deems

2014-01-01

This commentary discusses the rationale behind our recently reported work entitled "Mimicking isovolumic contraction with combined electromechanical stimulation improves the development of engineered cardiac constructs," introduces new data supporting our hypothesis, and discusses future applications of our bioreactor system. The ability to stimulate engineered cardiac tissue in a bioreactor system that combines both electrical and mechanical stimulation offers a unique opportunity to simulate the appropriate dynamics between stretch and contraction and model isovolumic contraction in vitro. Our previous study demonstrated that combined electromechanical stimulation that simulated the timing of isovolumic contraction in healthy tissue improved force generation via increased contractile and calcium handling protein expression and improved hypertrophic pathway activation. In new data presented here, we further demonstrate that modification of the timing between electrical and mechanical stimulation to mimic a non-physiological process negatively impacts the functionality of the engineered constructs. We close by exploring the various disease states that have altered timing between the electrical and mechanical stimulation signals as potential future directions for the use of this system.
DOE unveils climate model in advance of global test

NASA Astrophysics Data System (ADS)

Popkin, Gabriel

2018-05-01

The world's growing collection of climate models has a high-profile new entry. Last week, after nearly 4 years of work, the U.S. Department of Energy (DOE) released computer code and initial results from an ambitious effort to simulate the Earth system. The new model is tailored to run on future supercomputers and designed to forecast not just how climate will change, but also how those changes might stress energy infrastructure. Results from an upcoming comparison of global models may show how well the new entrant works. But so far it is getting a mixed reception, with some questioning the need for another model and others saying the $80 million effort has yet to improve predictions of the future climate. Even the project's chief scientist, Ruby Leung of the Pacific Northwest National Laboratory in Richland, Washington, acknowledges that the model is not yet a leader.
Do Savings Mediate Changes in Adolescents' Future Orientation and Health-Related Outcomes? Findings From Randomized Experiment in Uganda.

PubMed

Karimli, Leyla; Ssewamala, Fred M

2015-10-01

This present study tests the proposition that an economic strengthening intervention for families caring for AIDS-orphaned adolescents would positively affect adolescent future orientation and psychosocial outcomes through increased asset accumulation (in this case, by increasing family savings). Using longitudinal data from the cluster-randomized experiment, we ran generalized estimating equation models with robust standard errors clustering on individual observations. To examine whether family savings mediate the effect of the intervention on adolescents' future orientation and psychosocial outcomes, analyses were conducted in three steps: (1) testing the effect of intervention on mediator; (2) testing the effect of mediator on outcomes, controlling for the intervention; and (3) testing the significance of mediating effect using Sobel-Goodman method. Asymmetric confidence intervals for mediated effect were obtained through bootstrapping-to address the assumption of normal distribution. Results indicate that participation in a matched Child Savings Account (CSA) program improved adolescents' future orientation and psychosocial outcomes by reducing hopelessness, enhancing self-concept, and improving adolescents' confidence about their educational plans. However, the positive intervention effect on adolescent future orientation and psychosocial outcomes was not transmitted through saving. In other words, participation in the matched CSA program improved adolescent future orientation and psychosocial outcomes regardless of its impact on reported savings. Further research is necessary to understand exactly how participation in economic strengthening interventions, for example, those that employ matched CSAs, shape adolescent future orientation and psychosocial outcomes: what, if not savings, transmits the treatment effect and how? Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
Do savings mediate changes in adolescents’ future orientation and health-related outcomes? Findings from randomized experiment in Uganda

PubMed Central

Karimli, Leyla; Ssewamala, Fred M.

2015-01-01

Purpose This present study tests the proposition that an economic strengthening intervention for families caring for AIDS-orphaned adolescents would positively affect adolescent future orientation and psychosocial outcomes through increased asset-accumulation (in this case, by increasing family savings). Methods Using longitudinal data from the cluster-randomized experiment we ran generalized estimating equation (GEE) models with robust standard errors clustering on individual observations. To examine whether family savings mediate the effect of the intervention on adolescents’ future orientation and psychosocial outcomes, analyses were conducted in three steps: (1) testing the effect of intervention on mediator; (2) testing the effect of mediator on outcomes, controlling for the intervention; and (3) testing the significance of mediating effect using Sobel-Goodman method. Asymmetric confidence intervals for mediated effect were obtained through bootstrapping—to address the assumption of normal distribution. Results Results indicate that participation in a matched Child Savings Account program improved adolescents’ future orientation and psychosocial outcomes by reducing hopelessness, enhancing self-concept, and improving adolescents’ confidence about their educational plans. However, the positive intervention effect on adolescent future orientation and psychosocial outcomes was not transmitted through saving. In other words, participation in the matched Child Savings Account program improved adolescent future orientation and psychosocial outcomes regardless of its impact on reported savings. Conclusions Further research is necessary to understand exactly how participation in economic strengthening interventions, for example, those that employ matched Child Savings Accounts, shape adolescent future orientation and psychosocial outcomes: what, if not savings, transmits the treatment effect and how? PMID:26271162

Hearing: The Future of Sensory Rehabilitation?

PubMed

Skoe, Erika

2017-11-06

A new randomized, double-blind controlled study has found that playing a video game modeled from sensory foraging behavior can improve the aging brain's ability to hear complex signals hidden in background noise. Copyright © 2017 Elsevier Ltd. All rights reserved.
Using a safety forecast model to calculate future safety metrics.

DOT National Transportation Integrated Search

2017-05-01

This research sought to identify a process to improve long-range planning prioritization by using forecasted : safety metrics in place of the existing Utah Department of Transportation Safety Indexa metric based on historical : crash data. The res...
Questioning the Relevance of Model-Based Probability Statements on Extreme Weather and Future Climate

NASA Astrophysics Data System (ADS)

Smith, L. A.

2007-12-01

We question the relevance of climate-model based Bayesian (or other) probability statements for decision support and impact assessment on spatial scales less than continental and temporal averages less than seasonal. Scientific assessment of higher resolution space and time scale information is urgently needed, given the commercial availability of "products" at high spatiotemporal resolution, their provision by nationally funded agencies for use both in industry decision making and governmental policy support, and their presentation to the public as matters of fact. Specifically we seek to establish necessary conditions for probability forecasts (projections conditioned on a model structure and a forcing scenario) to be taken seriously as reflecting the probability of future real-world events. We illustrate how risk management can profitably employ imperfect models of complicated chaotic systems, following NASA's study of near-Earth PHOs (Potentially Hazardous Objects). Our climate models will never be perfect, nevertheless the space and time scales on which they provide decision- support relevant information is expected to improve with the models themselves. Our aim is to establish a set of baselines of internal consistency; these are merely necessary conditions (not sufficient conditions) that physics based state-of-the-art models are expected to pass if their output is to be judged decision support relevant. Probabilistic Similarity is proposed as one goal which can be obtained even when our models are not empirically adequate. In short, probabilistic similarity requires that, given inputs similar to today's empirical observations and observational uncertainties, we expect future models to produce similar forecast distributions. Expert opinion on the space and time scales on which we might reasonably expect probabilistic similarity may prove of much greater utility than expert elicitation of uncertainty in parameter values in a model that is not empirically adequate; this may help to explain the reluctance of experts to provide information on "parameter uncertainty." Probability statements about the real world are always conditioned on some information set; they may well be conditioned on "False" making them of little value to a rational decision maker. In other instances, they may be conditioned on physical assumptions not held by any of the modellers whose model output is being cast as a probability distribution. Our models will improve a great deal in the next decades, and our insight into the likely climate fifty years hence will improve: maintaining the credibility of the science and the coherence of science based decision support, as our models improve, require a clear statement of our current limitations. What evidence do we have that today's state-of-the-art models provide decision-relevant probability forecasts? What space and time scales do we currently have quantitative, decision-relevant information on for 2050? 2080?
The Model Analyst’s Toolkit: Scientific Model Development, Analysis, and Validation

DTIC Science & Technology

2015-02-20

being integrated within MAT, including Granger causality. Granger causality tests whether a data series helps when predicting future values of another...relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 424-438. Granger, C. W. (1980). Testing ... testing dataset. This effort is described in Section 3.2. 3.1. Improvements in Granger Causality User Interface Various metrics of causality are
Thermal modelling using discrete vasculature for thermal therapy: a review

PubMed Central

Kok, H.P.; Gellermann, J.; van den Berg, C.A.T.; Stauffer, P.R.; Hand, J.W.; Crezee, J.

2013-01-01

Reliable temperature information during clinical hyperthermia and thermal ablation is essential for adequate treatment control, but conventional temperature measurements do not provide 3D temperature information. Treatment planning is a very useful tool to improve treatment quality and substantial progress has been made over the last decade. Thermal modelling is a very important and challenging aspect of hyperthermia treatment planning. Various thermal models have been developed for this purpose, with varying complexity. Since blood perfusion is such an important factor in thermal redistribution of energy in in vivo tissue, thermal simulations are most accurately performed by modelling discrete vasculature. This review describes the progress in thermal modelling with discrete vasculature for the purpose of hyperthermia treatment planning and thermal ablation. There has been significant progress in thermal modelling with discrete vasculature. Recent developments have made real-time simulations possible, which can provide feedback during treatment for improved therapy. Future clinical application of thermal modelling with discrete vasculature in hyperthermia treatment planning is expected to further improve treatment quality. PMID:23738700
The determination of the orbit of the Japanese satellite Ajisai and the GEM-T1 and GEM-T2 gravity field models

NASA Technical Reports Server (NTRS)

Sanchez, Braulio V.

1990-01-01

The Japanese Experimental Geodetic Satellite Ajisai was launched on August 12, 1986. In response to the TOPEX-POSEIDON mission requirements, the GSFC Space Geodesy Branch and its associates are producing improved models of the Earth's gravitational field. With the launch of Ajisai, precise laser data is now available which can be used to test many current gravity models. The testing of the various gravity field models show improvements of more than 70 percent in the orbital fits when using GEM-T1 and GEM-T2 relative to results obtained with the earlier GEM-10B model. The GEM-T2 orbital fits are at the 13-cm level (RMS). The results of the tests with the various versions of the GEM-T1 model indicate that the addition of satellite altimetry and surface gravity anomalies as additional data types should improve future gravity field models.
Mouse brain magnetic resonance microscopy: Applications in Alzheimer disease.

PubMed

Lin, Lan; Fu, Zhenrong; Xu, Xiaoting; Wu, Shuicai

2015-05-01

Over the past two decades, various Alzheimer's disease (AD) trangenetic mice models harboring genes with mutation known to cause familial AD have been created. Today, high-resolution magnetic resonance microscopy (MRM) technology is being widely used in the study of AD mouse models. It has greatly facilitated and advanced our knowledge of AD. In this review, most of the attention is paid to fundamental of MRM, the construction of standard mouse MRM brain template and atlas, the detection of amyloid plaques, following up on brain atrophy and the future applications of MRM in transgenic AD mice. It is believed that future testing of potential drugs in mouse models with MRM will greatly improve the predictability of drug effect in preclinical trials. © 2015 Wiley Periodicals, Inc.
The interplay of climate and land use change affects the distribution of EU bumblebees.

PubMed

Marshall, Leon; Biesmeijer, Jacobus C; Rasmont, Pierre; Vereecken, Nicolas J; Dvorak, Libor; Fitzpatrick, Una; Francis, Frédéric; Neumayer, Johann; Ødegaard, Frode; Paukkunen, Juho P T; Pawlikowski, Tadeusz; Reemer, Menno; Roberts, Stuart P M; Straka, Jakub; Vray, Sarah; Dendoncker, Nicolas

2018-01-01

Bumblebees in Europe have been in steady decline since the 1900s. This decline is expected to continue with climate change as the main driver. However, at the local scale, land use and land cover (LULC) change strongly affects the occurrence of bumblebees. At present, LULC change is rarely included in models of future distributions of species. This study's objective is to compare the roles of dynamic LULC change and climate change on the projected distribution patterns of 48 European bumblebee species for three change scenarios until 2100 at the scales of Europe, and Belgium, Netherlands and Luxembourg (BENELUX). We compared three types of models: (1) only climate covariates, (2) climate and static LULC covariates and (3) climate and dynamic LULC covariates. The climate and LULC change scenarios used in the models include, extreme growth applied strategy (GRAS), business as might be usual and sustainable European development goals. We analysed model performance, range gain/loss and the shift in range limits for all bumblebees. Overall, model performance improved with the introduction of LULC covariates. Dynamic models projected less range loss and gain than climate-only projections, and greater range loss and gain than static models. Overall, there is considerable variation in species responses and effects were most pronounced at the BENELUX scale. The majority of species were predicted to lose considerable range, particularly under the extreme growth scenario (GRAS; overall mean: 64% ± 34). Model simulations project a number of local extinctions and considerable range loss at the BENELUX scale (overall mean: 56% ± 39). Therefore, we recommend species-specific modelling to understand how LULC and climate interact in future modelling. The efficacy of dynamic LULC change should improve with higher thematic and spatial resolution. Nevertheless, current broad scale representations of change in major land use classes impact modelled future distribution patterns. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science.

PubMed

Jones, James W; Antle, John M; Basso, Bruno; Boote, Kenneth J; Conant, Richard T; Foster, Ian; Godfray, H Charles J; Herrero, Mario; Howitt, Richard E; Janssen, Sander; Keating, Brian A; Munoz-Carpena, Rafael; Porter, Cheryl H; Rosenzweig, Cynthia; Wheeler, Tim R

2017-07-01

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.
Toward a New Generation of Agricultural System Data, Models, and Knowledge Products: State of Agricultural Systems Science

NASA Technical Reports Server (NTRS)

Jones, James W.; Antle, John M.; Basso, Bruno; Boote, Kenneth J.; Conant, Richard T.; Foster, Ian; Godfray, H. Charles J.; Herrero, Mario; Howitt, Richard E.; Janssen, Sander;

2016-01-01

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.

Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science

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

Jones, James W.; Antle, John M.; Basso, Bruno

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and needmore » to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.« less
An empirical perspective for understanding climate change impacts in Switzerland

USGS Publications Warehouse

Henne, Paul; Bigalke, Moritz; Büntgen, Ulf; Colombaroli, Daniele; Conedera, Marco; Feller, Urs; Frank, David; Fuhrer, Jürg; Grosjean, Martin; Heiri, Oliver; Luterbacher, Jürg; Mestrot, Adrien; Rigling, Andreas; Rössler, Ole; Rohr, Christian; Rutishauser, This; Schwikowski, Margit; Stampfli, Andreas; Szidat, Sönke; Theurillat, Jean-Paul; Weingartner, Rolf; Wilcke, Wolfgan; Tinner, Willy

2018-01-01

Planning for the future requires a detailed understanding of how climate change affects a wide range of systems at spatial scales that are relevant to humans. Understanding of climate change impacts can be gained from observational and reconstruction approaches and from numerical models that apply existing knowledge to climate change scenarios. Although modeling approaches are prominent in climate change assessments, observations and reconstructions provide insights that cannot be derived from simulations alone, especially at local to regional scales where climate adaptation policies are implemented. Here, we review the wealth of understanding that emerged from observations and reconstructions of ongoing and past climate change impacts in Switzerland, with wider applicability in Europe. We draw examples from hydrological, alpine, forest, and agricultural systems, which are of paramount societal importance, and are projected to undergo important changes by the end of this century. For each system, we review existing model-based projections, present what is known from observations, and discuss how empirical evidence may help improve future projections. A particular focus is given to better understanding thresholds, tipping points and feedbacks that may operate on different time scales. Observational approaches provide the grounding in evidence that is needed to develop local to regional climate adaptation strategies. Our review demonstrates that observational approaches should ideally have a synergistic relationship with modeling in identifying inconsistencies in projections as well as avenues for improvement. They are critical for uncovering unexpected relationships between climate and agricultural, natural, and hydrological systems that will be important to society in the future.
Lessons Learned from Radioactive Waste Storage and Disposal Facilities

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

Esh, David W.; Bradford, Anna H.

2008-01-15

The safety of radioactive waste disposal facilities and the decommissioning of complex sites may be predicated on the performance of engineered and natural barriers. For assessing the safety of a waste disposal facility or a decommissioned site, a performance assessment or similar analysis is often completed. The analysis is typically based on a site conceptual model that is developed from site characterization information, observations, and, in many cases, expert judgment. Because waste disposal facilities are sited, constructed, monitored, and maintained, a fair amount of data has been generated at a variety of sites in a variety of natural systems. Thismore » paper provides select examples of lessons learned from the observations developed from the monitoring of various radioactive waste facilities (storage and disposal), and discusses the implications for modeling of future waste disposal facilities that are yet to be constructed or for the development of dose assessments for the release of decommissioning sites. Monitoring has been and continues to be performed at a variety of different facilities for the disposal of radioactive waste. These include facilities for the disposal of commercial low-level waste (LLW), reprocessing wastes, and uranium mill tailings. Many of the lessons learned and problems encountered provide a unique opportunity to improve future designs of waste disposal facilities, to improve dose modeling for decommissioning sites, and to be proactive in identifying future problems. Typically, an initial conceptual model was developed and the siting and design of the disposal facility was based on the conceptual model. After facility construction and operation, monitoring data was collected and evaluated. In many cases the monitoring data did not comport with the original site conceptual model, leading to additional investigation and changes to the site conceptual model and modifications to the design of the facility. The following cases are discussed: commercial LLW disposal facilities; uranium mill tailings disposal facilities; and reprocessing waste storage and disposal facilities. The observations developed from the monitoring and maintenance of waste disposal and storage facilities provide valuable lessons learned for the design and modeling of future waste disposal facilities and the decommissioning of complex sites.« less
Impact of revised and potential future albedo estimates on CCSM3 simulations of growing-season surface temperature fields for North America

Treesearch

Warren E. Heilman; David Y. Hollinger; Xiuping Li; Xindi Bain; Shiyuan. Zhong

2010-01-01

Recently published albedo research has resulted in improved growing-season albedo estimates for forest and grassland vegetation. The impact of these improved estimates on the ability of climate models to simulate growing-season surface temperature patterns is unknown. We have developed a set of current-climate surface temperature scenarios for North America using the...
Evidence base and future research directions in the management of low back pain

PubMed Central

Abbott, Allan

2016-01-01

Low back pain (LBP) is a prevalent and costly condition. Awareness of valid and reliable patient history taking, physical examination and clinical testing is important for diagnostic accuracy. Stratified care which targets treatment to patient subgroups based on key characteristics is reliant upon accurate diagnostics. Models of stratified care that can potentially improve treatment effects include prognostic risk profiling for persistent LBP, likely response to specific treatment based on clinical prediction models or suspected underlying causal mechanisms. The focus of this editorial is to highlight current research status and future directions for LBP diagnostics and stratified care. PMID:27004162
Design aspects of harmonic drive gear and performance improvement of its by problems identification: A review

NASA Astrophysics Data System (ADS)

Routh, Bikash

2018-04-01

The present paper aims at review on different aspects of harmonic drive gear to identify literature gap for future research. The present article is started first making the comparative study of harmonic drive gear over conventional gear, highlighting its historical background, its application, limitation etc. and then describing working principle of each and every components of it with detail dimensioning and modelling. The present article is further extended to study the different design aspects i.e. synthesis of tooth profiles, lubrication, stress, strain, torque, load sharing, kinematics error and vibration in details etc., identifying problems and then suggesting future perspective for the performance improvement of harmonic drive gear.
Control technology for future aircraft propulsion systems

NASA Technical Reports Server (NTRS)

Zeller, J. R.; Szuch, J. R.; Merrill, W. C.; Lehtinen, B.; Soeder, J. F.

1984-01-01

The need for a more sophisticated engine control system is discussed. The improvements in better thrust-to-weight ratios demand the manipulation of more control inputs. New technological solutions to the engine control problem are practiced. The digital electronic engine control (DEEC) system is a step in the evolution to digital electronic engine control. Technology issues are addressed to ensure a growth in confidence in sophisticated electronic controls for aircraft turbine engines. The need of a control system architecture which permits propulsion controls to be functionally integrated with other aircraft systems is established. Areas of technology studied include: (1) control design methodology; (2) improved modeling and simulation methods; and (3) implementation technologies. Objectives, results and future thrusts are summarized.
The Agriculture Model Intercomparison and Improvement Project (AgMIP) (Invited)

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2010-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation exercise for historical model intercomparison and future climate change conditions with participation of multiple crop and world agricultural trade modeling groups around the world. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Historical period results will spur model improvement and interaction among major modeling groups, while future period results will lead directly to tests of adaptation and mitigation strategies across a range of scales. AgMIP will consist of a multi-scale impact assessment utilizing the latest methods for climate and agricultural scenario generation. Scenarios and modeling protocols will be distributed on the web, and multi-model results will be collated and analyzed to ensure the widest possible coverage of agricultural crops and regions. AgMIP will place regional changes in agricultural production in a global context that reflects new trading opportunities, imbalances, and shortages in world markets resulting from climate change and other driving forces for food supply. Such projections are essential inputs from the Vulnerability, Impacts, and Adaptation (VIA) research community to the Intergovernmental Panel on Climate Change Fifth Assessment (AR5), now underway, and the UN Framework Convention on Climate Change. They will set the context for local-scale vulnerability and adaptation studies, supply test scenarios for national-scale development of trade policy instruments, provide critical information on changing supply and demand for water resources, and elucidate interactive effects of climate change and land use change. AgMIP will not only provide crucially-needed new global estimates of how climate change will affect food supply and hunger in the agricultural regions of the world, but it will also build the capabilities of developing countries to estimate how climate change will affect their supply and demand for food.
Which downscaled rainfall data for climate change impact studies in urban areas? Review of current approaches and trends

NASA Astrophysics Data System (ADS)

Gooré Bi, Eustache; Gachon, Philippe; Vrac, Mathieu; Monette, Frédéric

2017-02-01

Changes in extreme precipitation should be one of the primary impacts of climate change (CC) in urban areas. To assess these impacts, rainfall data from climate models are commonly used. The main goal of this paper is to report on the state of knowledge and recent works on the study of CC impacts with a focus on urban areas, in order to produce an integrated review of various approaches to which future studies can then be compared or constructed. Model output statistics (MOS) methods are increasingly used in the literature to study the impacts of CC in urban settings. A review of previous works highlights the non-stationarity nature of future climate data, underscoring the need to revise urban drainage system design criteria. A comparison of these studies is made difficult, however, by the numerous sources of uncertainty arising from a plethora of assumptions, scenarios, and modeling options. All the methods used do, however, predict increased extreme precipitation in the future, suggesting potential risks of combined sewer overflow frequencies, flooding, and back-up in existing sewer systems in urban areas. Future studies must quantify more accurately the different sources of uncertainty by improving downscaling and correction methods. New research is necessary to improve the data validation process, an aspect that is seldom reported in the literature. Finally, the potential application of non-stationarity conditions into generalized extreme value (GEV) distribution should be assessed more closely, which will require close collaboration between engineers, hydrologists, statisticians, and climatologists, thus contributing to the ongoing reflection on this issue of social concern.
Residential energy demand models: Current status and future improvements

NASA Astrophysics Data System (ADS)

Peabody, G.

1980-12-01

Two models currently used to analyze energy use by the residential sector are described. The ORNL model is used to forecast energy use by fuel type for various end uses on a yearly basis. The MATH/CHRDS model analyzes variations in energy expenditures by households of various socioeconomic and demographic characteristics. The essential features of the ORNL and MATH/CHRDS models are retained in a proposed model and integrated into a framework that is more flexible than either model. The important determinants of energy use by households are reviewed.

Future developments in biliary stenting

PubMed Central

Hair, Clark D; Sejpal, Divyesh V

2013-01-01

Biliary stenting has evolved dramatically over the past 30 years. Advancements in stent design have led to prolonged patency and improved efficacy. However, biliary stenting is still affected by occlusion, migration, anatomical difficulties, and the need for repeat procedures. Multiple novel plastic biliary stent designs have recently been introduced with the primary goals of reduced migration and improved ease of placement. Self-expandable bioabsorbable stents are currently being investigated in animal models. Although not US Food and Drug Administration approved for benign disease, fully covered self-expandable metal stents are increasingly being used in a variety of benign biliary conditions. In malignant disease, developments are being made to improve ease of placement and stent patency for both hilar and distal biliary strictures. The purpose of this review is to describe recent developments and future directions of biliary stenting. PMID:23837001
Perspectives On Dilution Jet Mixing

NASA Technical Reports Server (NTRS)

Holdeman, J. D.; Srinivasan, R.

1990-01-01

NASA recently completed program of measurements and modeling of mixing of transverse jets with ducted crossflow, motivated by need to design or tailor temperature pattern at combustor exit in gas turbine engines. Objectives of program to identify dominant physical mechanisms governing mixing, extend empirical models to provide near-term predictive capability, and compare numerical code calculations with data to guide future analysis improvement efforts.
Institutional Transformation Model

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

2015-10-19

Reducing the energy consumption of large institutions with dozens to hundreds of existing buildings while maintaining and improving existing infrastructure is a critical economic and environmental challenge. SNL's Institutional Transformation (IX) work integrates facilities and infrastructure sustainability technology capabilities and collaborative decision support modeling approaches to help facilities managers at Sandia National Laboratories (SNL) simulate different future energy reduction strategies and meet long term energy conservation goals.
PET motion correction in context of integrated PET/MR: Current techniques, limitations, and future projections.

PubMed

Gillman, Ashley; Smith, Jye; Thomas, Paul; Rose, Stephen; Dowson, Nicholas

2017-12-01

Patient motion is an important consideration in modern PET image reconstruction. Advances in PET technology mean motion has an increasingly important influence on resulting image quality. Motion-induced artifacts can have adverse effects on clinical outcomes, including missed diagnoses and oversized radiotherapy treatment volumes. This review aims to summarize the wide variety of motion correction techniques available in PET and combined PET/CT and PET/MR, with a focus on the latter. A general framework for the motion correction of PET images is presented, consisting of acquisition, modeling, and correction stages. Methods for measuring, modeling, and correcting motion and associated artifacts, both in literature and commercially available, are presented, and their relative merits are contrasted. Identified limitations of current methods include modeling of aperiodic and/or unpredictable motion, attaining adequate temporal resolution for motion correction in dynamic kinetic modeling acquisitions, and maintaining availability of the MR in PET/MR scans for diagnostic acquisitions. Finally, avenues for future investigation are discussed, with a focus on improvements that could improve PET image quality, and that are practical in the clinical environment. © 2017 American Association of Physicists in Medicine.
OysterFutures: Integrating Stakeholder Objectives with Natural System Models to Promote Sustainable Natural Resource Policy

NASA Astrophysics Data System (ADS)

North, E. W.; Blair, J.; Cornwell, J. C.; Freitag, A. E.; Gawde, R. K.; Hartley, T. W.; Hood, R. R.; Jones, R. M.; Miller, T. J.; Thomas, J. E.; Wainger, L. A.; Wilberg, M. J.

2016-02-01

Achieving effective natural resource management is challenged by multiple and often competing objectives, a restricted set of policy options, and uncertainty in the performance of those options. Yet, managers need policies that allow continued use of natural resources while ensuring access for future generations and maintenance of ecosystem services. Formal approaches are needed that will assist managers and stakeholders in choosing policy options that have a high likelihood of achieving social, ecological, and economic goals. The goal of this project, OysterFutures, is to address this need by improving the use of predictive models to support sustainable natural resource policy and management. A stakeholder-centered process will be used to build an integrated model that combines estuarine physics, oyster life history, and the ecosystem services that oysters provide (e.g., harvest, water quality) to forecast outcomes under alternative management strategies. Through a series of facilitated meetings, stakeholders will participate in a science-based collaborative process which will allow them to project how well policies are expected to meet their objectives using the integrated model. This iterative process will ensure that the model will incorporate the complex human uses of the ecosystem as well as focus on the outcomes most important to the stakeholders. In addition, a study of the socioeconomic drivers of stakeholder involvement, information flow, use and influence, and policy formation will be undertaken to improve the process, enhance implementation success of recommended policies, and provide new ideas for integrating natural and social sciences, and scientists, in sustainable resource management. In this presentation, the strategy for integrating natural system models, stakeholder views, and sociological studies as well as methods for selecting stakeholders and facilitating stakeholder meetings will be described and discussed.
Synthesis and Assimilation Systems - Essential Adjuncts to the Global Ocean Observing System

NASA Technical Reports Server (NTRS)

Rienecker, Michele M.; Balmaseda, Magdalena; Awaji, Toshiyuki; Barnier, Bernard; Behringer, David; Bell, Mike; Bourassa, Mark; Brasseur, Pierre; Breivik, Lars-Anders; Carton, James;

2009-01-01

Ocean assimilation systems synthesize diverse in situ and satellite data streams into four-dimensional state estimates by combining the various observations with the model. Assimilation is particularly important for the ocean where subsurface observations, even today, are sparse and intermittent compared with the scales needed to represent ocean variability and where satellites only sense the surface. Developments in assimilation and in the observing system have advanced our understanding and prediction of ocean variations at mesoscale and climate scales. Use of these systems for assessing the observing system helps identify the strengths of each observation type. Results indicate that the ocean remains under-sampled and that further improvements in the observing system are needed. Prospects for future advances lie in improved models and better estimates of error statistics for both models and observations. Future developments will be increasingly towards consistent analyses across components of the Earth system. However, even today ocean synthesis and assimilation systems are providing products that are useful for many applications and should be considered an integral part of the global ocean observing and information system.

CMS Nonpayment Policy, Quality Improvement, and Hospital-Acquired Conditions: An Integrative Review.

PubMed

Bae, Sung-Heui

This integrative review synthesized evidence on the consequences of the Centers for Medicare & Medicaid Services (CMS) nonpayment policy on quality improvement initiatives and hospital-acquired conditions. Fourteen articles were included. This review presents strong evidence that the CMS policy has spurred quality improvement initiatives; however, the relationships between the CMS policy and hospital-acquired conditions are inconclusive. In future research, a comprehensive model of implementation of the CMS nonpayment policy would help us understand the effectiveness of this policy.
Effect of Bundled Payments and Health Care Reform as Alternative Payment Models in Total Joint Arthroplasty: A Clinical Review.

PubMed

Siddiqi, Ahmed; White, Peter B; Mistry, Jaydev B; Gwam, Chukwuweike U; Nace, James; Mont, Michael A; Delanois, Ronald E

2017-08-01

In an effort to control rising healthcare costs, healthcare reforms have developed initiatives to evaluate the efficacy of alternative payment models (APMs) for Medicare reimbursements. The Center for Medicare and Medicaid Services Innovation Center (CMMSIC) introduced the voluntary Bundled Payments for Care Improvement (BPCI) model experiment as a means to curtail Medicare cost by allotting a fixed payment for an episode of care. The purpose of this review is to (1) summarize the preliminary clinical results of the BPCI and (2) discuss how it has led to other healthcare reforms and alternative payment models. A literature search was performed using PubMed and the CMMSIC to explore different APMs and clinical results after implementation. All studies that were not in English or unrelated to the topic were excluded. Preliminary results of bundled payment models have shown reduced costs in total joint arthroplasty largely by reducing hospital length of stay, decreasing readmission rates, as well as reducing the number of patients sent to in-patient rehabilitation facilities. In order to refine episode of care bundles, CMMSIC has also developed other initiatives such as the Comprehensive Care for Joint Replacement (CJR) pathway and Surgical Hip and Femur Fracture (SHFFT). Despite the unknown future of the Affordable Care Act, BPCI, and CJR, preliminary results of alternative models have shown promise to reduce costs and improve quality of care. Moving into the future, surgeon control of the BPCI and CJR bundle should be investigated to further improve patient care and maximize financial compensation. Copyright © 2017 Elsevier Inc. All rights reserved.
Future of endemic flora of biodiversity hotspots in India.

PubMed

Chitale, Vishwas Sudhir; Behera, Mukund Dev; Roy, Partha Sarthi

2014-01-01

India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models.
Future of Endemic Flora of Biodiversity Hotspots in India

PubMed Central

Chitale, Vishwas Sudhir; Behera, Mukund Dev; Roy, Partha Sarthi

2014-01-01

India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models. PMID:25501852
Important technical parameters are not presented in reports of intraoral digital radiography in endodontic treatment: recommendations for future studies.

PubMed

Konishi, Masaru; Lindh, Christina; Nilsson, Mats; Tanimoto, Keiji; Rohlin, Madeleine

2012-08-01

The aims of this study were to review the literature on intraoral digital radiography in endodontic treatment with focus on technical parameters and to propose recommendations for improving the quality of reports in future publications. Two electronic databases were searched. Titles and abstracts were selected according to preestablished criteria. Data were extracted using a model of image acquisition and interpretation. The literature search yielded 233 titles and abstracts; 61 reports were read in full text. Recent reports presented technical parameters more thoroughly than older reports. Most reported important parameters for the x-ray unit, but for image interpretation only about one-half of the publications cited resolution of the display system and fewer than one-half bit depth of the graphics card. The methodologic quality of future publications must be improved to permit replication of studies and comparison of results between studies in dental digital radiography. Our recommendations can improve the quality of studies on diagnostic accuracy. Copyright © 2012 Mosby, Inc. All rights reserved.
Using Uncertainty Quantification to Guide Development and Improvements of a Regional-Scale Model of the Coastal Lowlands Aquifer System Spanning Texas, Louisiana, Mississippi, Alabama and Florida

NASA Astrophysics Data System (ADS)

Foster, L. K.; Clark, B. R.; Duncan, L. L.; Tebo, D. T.; White, J.

2017-12-01

Several historical groundwater models exist within the Coastal Lowlands Aquifer System (CLAS), which spans the Gulf Coastal Plain in Texas, Louisiana, Mississippi, Alabama, and Florida. The largest of these models, called the Gulf Coast Regional Aquifer System Analysis (RASA) model, has been brought into a new framework using the Newton formulation for MODFLOW-2005 (MODFLOW-NWT) and serves as the starting point of a new investigation underway by the U.S. Geological Survey to improve understanding of the CLAS and provide predictions of future groundwater availability within an uncertainty quantification (UQ) framework. The use of an UQ framework will not only provide estimates of water-level observation worth, hydraulic parameter uncertainty, boundary-condition uncertainty, and uncertainty of future potential predictions, but it will also guide the model development process. Traditionally, model development proceeds from dataset construction to the process of deterministic history matching, followed by deterministic predictions using the model. This investigation will combine the use of UQ with existing historical models of the study area to assess in a quantitative framework the effect model package and property improvements have on the ability to represent past-system states, as well as the effect on the model's ability to make certain predictions of water levels, water budgets, and base-flow estimates. Estimates of hydraulic property information and boundary conditions from the existing models and literature, forming the prior, will be used to make initial estimates of model forecasts and their corresponding uncertainty, along with an uncalibrated groundwater model run within an unconstrained Monte Carlo analysis. First-Order Second-Moment (FOSM) analysis will also be used to investigate parameter and predictive uncertainty, and guide next steps in model development prior to rigorous history matching by using PEST++ parameter estimation code.
Improved Range Estimation Model for Three-Dimensional (3D) Range Gated Reconstruction

PubMed Central

Chua, Sing Yee; Guo, Ningqun; Tan, Ching Seong; Wang, Xin

2017-01-01

Accuracy is an important measure of system performance and remains a challenge in 3D range gated reconstruction despite the advancement in laser and sensor technology. The weighted average model that is commonly used for range estimation is heavily influenced by the intensity variation due to various factors. Accuracy improvement in term of range estimation is therefore important to fully optimise the system performance. In this paper, a 3D range gated reconstruction model is derived based on the operating principles of range gated imaging and time slicing reconstruction, fundamental of radiant energy, Laser Detection And Ranging (LADAR), and Bidirectional Reflection Distribution Function (BRDF). Accordingly, a new range estimation model is proposed to alleviate the effects induced by distance, target reflection, and range distortion. From the experimental results, the proposed model outperforms the conventional weighted average model to improve the range estimation for better 3D reconstruction. The outcome demonstrated is of interest to various laser ranging applications and can be a reference for future works. PMID:28872589
Space Suit Thermal Dynamics

NASA Technical Reports Server (NTRS)

Campbell, Anthony B.; Nair, Satish S.; Miles, John B.; Iovine, John V.; Lin, Chin H.

1998-01-01

The present NASA space suit (the Shuttle EMU) is a self-contained environmental control system, providing life support, environmental protection, earth-like mobility, and communications. This study considers the thermal dynamics of the space suit as they relate to astronaut thermal comfort control. A detailed dynamic lumped capacitance thermal model of the present space suit is used to analyze the thermal dynamics of the suit with observations verified using experimental and flight data. Prior to using the model to define performance characteristics and limitations for the space suit, the model is first evaluated and improved. This evaluation includes determining the effect of various model parameters on model performance and quantifying various temperature prediction errors in terms of heat transfer and heat storage. The observations from this study are being utilized in two future design efforts, automatic thermal comfort control design for the present space suit and design of future space suit systems for Space Station, Lunar, and Martian missions.
Technosocial Modeling of IED Threat Scenarios and Attacks

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

Whitney, Paul D.; Brothers, Alan J.; Coles, Garill A.

2009-03-23

This paper describes an approach for integrating sociological and technical models to develop more complete threat assessment. Current approaches to analyzing and addressing threats tend to focus on the technical factors. This paper addresses development of predictive models that encompass behavioral as well as these technical factors. Using improvised explosive device (IED) attacks as motivation, this model supports identification of intervention activities 'left of boom' as well as prioritizing attack modalities. We show how Bayes nets integrate social factors associated with IED attacks into general threat model containing technical and organizational steps from planning through obtaining the IED to initiationmore » of the attack. The social models are computationally-based representations of relevant social science literature that describes human decision making and physical factors. When combined with technical models, the resulting model provides improved knowledge integration into threat assessment for monitoring. This paper discusses the construction of IED threat scenarios, integration of diverse factors into an analytical framework for threat assessment, indicator identification for future threats, and future research directions.« less
Projections of Temperature-Attributable Premature Deaths in 209 U.S. Cities Using a Cluster-Based Poisson Approach

NASA Technical Reports Server (NTRS)

Schwartz, Joel D.; Lee, Mihye; Kinney, Patrick L.; Yang, Suijia; Mills, David; Sarofim, Marcus C.; Jones, Russell; Streeter, Richard; St. Juliana, Alexis; Peers, Jennifer;

2015-01-01

Background: A warming climate will affect future temperature-attributable premature deaths. This analysis is the first to project these deaths at a near national scale for the United States using city and month-specific temperature-mortality relationships. Methods: We used Poisson regressions to model temperature-attributable premature mortality as a function of daily average temperature in 209 U.S. cities by month. We used climate data to group cities into clusters and applied an Empirical Bayes adjustment to improve model stability and calculate cluster-based month-specific temperature-mortality functions. Using data from two climate models, we calculated future daily average temperatures in each city under Representative Concentration Pathway 6.0. Holding population constant at 2010 levels, we combined the temperature data and cluster-based temperature-mortality functions to project city-specific temperature-attributable premature deaths for multiple future years which correspond to a single reporting year. Results within the reporting periods are then averaged to account for potential climate variability and reported as a change from a 1990 baseline in the future reporting years of 2030, 2050 and 2100. Results: We found temperature-mortality relationships that vary by location and time of year. In general, the largest mortality response during hotter months (April - September) was in July in cities with cooler average conditions. The largest mortality response during colder months (October-March) was at the beginning (October) and end (March) of the period. Using data from two global climate models, we projected a net increase in premature deaths, aggregated across all 209 cities, in all future periods compared to 1990. However, the magnitude and sign of the change varied by cluster and city. Conclusions: We found increasing future premature deaths across the 209 modeled U.S. cities using two climate model projections, based on constant temperature-mortality relationships from 1997 to 2006 without any future adaptation. However, results varied by location, with some locations showing net reductions in premature temperature-attributable deaths with climate change.

A Priori Calculations of Thermodynamic Functions

DTIC Science & Technology

1991-12-01

Ten closes this work with a brief summary and offers suggestions for improving the model and for future research. S CHAPTER TWO In this chapter, we...we must first define the theoretical model . The molecules studied in this work contain up to 10 non- hydrogen atoms and, in general, are not...is given by equation (2-31) for two different geometries or two different theoretical models . Equation (2-31) shows the error in the force constant has
An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)

NASA Astrophysics Data System (ADS)

Moulds, S.; Buytaert, W.; Mijic, A.

2015-04-01

Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment.
On the quantum-channel capacity for orbital angular momentum-based free-space optical communications.

PubMed

Zhang, Yequn; Djordjevic, Ivan B; Gao, Xin

2012-08-01

Inspired by recent demonstrations of orbital angular momentum-(OAM)-based single-photon communications, we propose two quantum-channel models: (i) the multidimensional quantum-key distribution model and (ii) the quantum teleportation model. Both models employ operator-sum representation for Kraus operators derived from OAM eigenkets transition probabilities. These models are highly important for future development of quantum-error correction schemes to extend the transmission distance and improve date rates of OAM quantum communications. By using these models, we calculate corresponding quantum-channel capacities in the presence of atmospheric turbulence.
Observation model and parameter partials for the JPL VLBI parameter estimation software MASTERFIT-1987

NASA Technical Reports Server (NTRS)

Sovers, O. J.; Fanselow, J. L.

1987-01-01

This report is a revision of the document of the same title (1986), dated August 1, which it supersedes. Model changes during 1986 and 1987 included corrections for antenna feed rotation, refraction in modelling antenna axis offsets, and an option to employ improved values of the semiannual and annual nutation amplitudes. Partial derivatives of the observables with respect to an additional parameter (surface temperature) are now available. New versions of two figures representing the geometric delay are incorporated. The expressions for the partial derivatives with respect to the nutation parameters have been corrected to include contributions from the dependence of UTI on nutation. The authors hope to publish revisions of this document in the future, as modeling improvements warrant.

Observation model and parameter partials for the JPL VLBI parameter estimation software MASTERFIT-1987

NASA Astrophysics Data System (ADS)

Sovers, O. J.; Fanselow, J. L.

1987-12-01

This report is a revision of the document of the same title (1986), dated August 1, which it supersedes. Model changes during 1986 and 1987 included corrections for antenna feed rotation, refraction in modelling antenna axis offsets, and an option to employ improved values of the semiannual and annual nutation amplitudes. Partial derivatives of the observables with respect to an additional parameter (surface temperature) are now available. New versions of two figures representing the geometric delay are incorporated. The expressions for the partial derivatives with respect to the nutation parameters have been corrected to include contributions from the dependence of UTI on nutation. The authors hope to publish revisions of this document in the future, as modeling improvements warrant.
An improved model for the combustion of AP composite propellants

NASA Technical Reports Server (NTRS)

Cohen, N. S.; Strand, L. D.

1981-01-01

This paper presents several improvements to the BDP model of steady-state burning of AP composite solid propellants. The Price-Boggs-Derr model of AP monopropellant burning is incorporated to represent the AP. A separate energy equation is written for the binder to permit a different surface temperature from the AP; this includes an analysis of the sharing of primary diffusion flame energy, and correction of a BDP model inconsistency in treating the binder regression rate. A method for assembling component contributions to calculate the burning rates of multimodal propellants is also presented. Results are shown in the form of representative burning rate curves, comparisons with data, and calculated internal details of interest. Ideas for future work are discussed in an Appendix.
A water balance model to estimate flow through the Old and Middle River corridor

USGS Publications Warehouse

Andrews, Stephen W.; Gross, Edward S.; Hutton, Paul H.

2016-01-01

We applied a water balance model to predict tidally averaged (subtidal) flows through the Old River and Middle River corridor in the Sacramento–San Joaquin Delta. We reviewed the dynamics that govern subtidal flows and water levels and adopted a simplified representation. In this water balance approach, we estimated ungaged flows as linear functions of known (or specified) flows. We assumed that subtidal storage within the control volume varies because of fortnightly variation in subtidal water level, Delta inflow, and barometric pressure. The water balance model effectively predicts subtidal flows and approaches the accuracy of a 1–D Delta hydrodynamic model. We explore the potential to improve the approach by representing more complex dynamics and identify possible future improvements.
Climate Modeling and Analysis with Decision Makers in Mind

NASA Astrophysics Data System (ADS)

Jones, A. D.; Jagannathan, K.; Calvin, K. V.; Lamarque, J. F.; Ullrich, P. A.

2016-12-01

There is a growing need for information about future climate conditions to support adaptation planning across a wide range of sectors and stakeholder communities. However, our principal tools for understanding future climate - global Earth system models - were not developed with these user needs in mind, nor have we developed transparent methods for evaluating and communicating the credibility of various climate information products with respect to the climate characteristics that matter most to decision-makers. Several recent community engagements have identified a need for "co-production" of knowledge among stakeholders and scientists. Here we highlight some of the barriers to communication and collaboration that must be overcome to improve the dialogue among researchers and climate adaptation practitioners in a meaningful way. Solutions to this challenge are two-fold: 1) new institutional arrangements and collaborative mechanisms designed to improve coordination and understanding among communities, and 2) a research agenda that explicitly incorporates stakeholder needs into model evaluation, development, and experimental design. We contrast the information content in global-scale model evaluation exercises with that required for in specific decision contexts, such as long-term agricultural management decisions. Finally, we present a vision for advancing the science of model evaluation in the context of predicting decision-relevant hydroclimate regime shifts in North America.
Improving automation standards via semantic modelling: Application to ISA88.

PubMed

Dombayci, Canan; Farreres, Javier; Rodríguez, Horacio; Espuña, Antonio; Graells, Moisès

2017-03-01

Standardization is essential for automation. Extensibility, scalability, and reusability are important features for automation software that rely in the efficient modelling of the addressed systems. The work presented here is from the ongoing development of a methodology for semi-automatic ontology construction methodology from technical documents. The main aim of this work is to systematically check the consistency of technical documents and support the improvement of technical document consistency. The formalization of conceptual models and the subsequent writing of technical standards are simultaneously analyzed, and guidelines proposed for application to future technical standards. Three paradigms are discussed for the development of domain ontologies from technical documents, starting from the current state of the art, continuing with the intermediate method presented and used in this paper, and ending with the suggested paradigm for the future. The ISA88 Standard is taken as a representative case study. Linguistic techniques from the semi-automatic ontology construction methodology is applied to the ISA88 Standard and different modelling and standardization aspects that are worth sharing with the automation community is addressed. This study discusses different paradigms for developing and sharing conceptual models for the subsequent development of automation software, along with presenting the systematic consistency checking method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Interactive Ozone and Methane Chemistry in GISS-E2 Historical and Future Climate Simulations

NASA Technical Reports Server (NTRS)

Shindell, D. T.; Pechony, O.; Voulgarakis, A.; Faluvegi, G.; Nazarenko. L.; Lamarque, J.-F.; Bowman, K.; Milly, G.; Kovari, B.; Ruedy, R.;

2013-01-01

The new generation GISS climate model includes fully interactive chemistry related to ozone in historical and future simulations, and interactive methane in future simulations. Evaluation of ozone, its tropospheric precursors, and methane shows that the model captures much of the largescale spatial structure seen in recent observations. While the model is much improved compared with the previous chemistry-climate model, especially for ozone seasonality in the stratosphere, there is still slightly too rapid stratospheric circulation, too little stratosphere-to-troposphere ozone flux in the Southern Hemisphere and an Antarctic ozone hole that is too large and persists too long. Quantitative metrics of spatial and temporal correlations with satellite datasets as well as spatial autocorrelation to examine transport and mixing are presented to document improvements in model skill and provide a benchmark for future evaluations. The difference in radiative forcing (RF) calculated using modeled tropospheric ozone versus tropospheric ozone observed by TES is only 0.016W/sq. m. Historical 20th Century simulations show a steady increase in whole atmosphere ozone RF through 1970 after which there is a decrease through 2000 due to stratospheric ozone depletion. Ozone forcing increases throughout the 21st century under RCP8.5 owing to a projected recovery of stratospheric ozone depletion and increases in methane, but decreases under RCP4.5 and 2.6 due to reductions in emissions of other ozone precursors. RF from methane is 0.05 to 0.18W/ sq. m higher in our model calculations than in the RCP RF estimates. The surface temperature response to ozone through 1970 follows the increase in forcing due to tropospheric ozone. After that time, surface temperatures decrease as ozone RF declines due to stratospheric depletion. The stratospheric ozone depletion also induces substantial changes in surface winds and the Southern Ocean circulation, which may play a role in a slightly stronger response per unit forcing during later decades. Tropical precipitation shifts south during boreal summer from 1850 to 1970, but then shifts northward from 1970 to 2000, following upper tropospheric temperature gradients more strongly than those at the surface.

Transition Models for Engineering Calculations

NASA Technical Reports Server (NTRS)

Fraser, C. J.

2007-01-01

While future theoretical and conceptual developments may promote a better understanding of the physical processes involved in the latter stages of boundary layer transition, the designers of rotodynamic machinery and other fluid dynamic devices need effective transition models now. This presentation will therefore center around the development of of some transition models which have been developed as design aids to improve the prediction codes used in the performance evaluation of gas turbine blading. All models are based on Narasimba's concentrated breakdown and spot growth.
VRML Industry: Microcosms in the Making.

ERIC Educational Resources Information Center

Brown, Eric

1998-01-01

Discusses VRML (Virtual Reality Modeling Language) technology and some of its possible applications, including creating three-dimensional images on the Web, advertising, and data visualization in computer-assisted design and computer-assisted manufacturing (CAD/CAM). Future improvements are discussed, including streaming, database support, and…
IMPROVE AND APPLY CHEMICAL MECHANISMS FOR DEVELOPING OZONE CONTROL STRATEGIES

EPA Science Inventory

Air quality models that realistically describe the formation of ozone, air toxics, and other pollutants are needed by EPA and state agencies to predict current and future concentrations of these pollutants and develop ways to decrease their concentrations below harmful levels. ...
Creativity and connections: the future of nursing education and practice: the Massachusetts Initiative.

PubMed

Sroczynski, Maureen; Gravlin, Gayle; Route, Paulette Seymour; Hoffart, Nancy; Creelman, Patricia

2011-01-01

Education and practice partnerships are key to effective academic program design and implementation in a time of decreasing supply and increasing demands on the nursing profession. An integrated education/practice competency model can positively impact patient safety, improve patient care, increase retention, and ensure a sufficient and competent nursing workforce, which is paramount to survival of the health care system. Through the contributions of nursing leaders from the broad spectrum of nursing and industry organizations within the state, the Massachusetts Nurse of the Future project developed a competency-based framework for the future design of nursing educational programs to meet current and future practice needs. The Massachusetts Nurse of the Future Nursing Core Competencies(©) expand on the Institute of Medicine's core competencies for all health care professionals and the Quality and Safety Education for Nurses competencies for quality and safety to define the expectations for all professional nurses of the future. The Massachusetts Nurse of the Future Nursing Core Competencies define the knowledge, attitude, and skills required as the minimal expectations for initial nursing practice following completion of a prelicensure professional nursing education program. These competencies are now being integrated into new models for seamless, coordinated nursing curriculum and transition into practice within the state and beyond. Copyright © 2011 Elsevier Inc. All rights reserved.
Improving Aerosol and Visibility Forecasting Capabilities Using Current and Future Generations of Satellite Observations

DTIC Science & Technology

2012-09-30

improving forecast performance over cloudy regions using the Ozone Monitoring Instrument (OMI) Aerosol Index; and 2) preparing for the post-MODIS...meteorological fields, the International Geosphere-Biosphere Programme (IGBP) SW and LW surface characteristics, and an ozone climatology are used as...The primary impact of CALIOP assimilation on the model is the redistribution of mass toward the boundary layer from the free troposphere . For high
Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach-A Case Study for the City of Wuhan in China.

PubMed

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-06-15

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.
Plant water potential improves prediction of empirical stomatal models.

PubMed

Anderegg, William R L; Wolf, Adam; Arango-Velez, Adriana; Choat, Brendan; Chmura, Daniel J; Jansen, Steven; Kolb, Thomas; Li, Shan; Meinzer, Frederick; Pita, Pilar; Resco de Dios, Víctor; Sperry, John S; Wolfe, Brett T; Pacala, Stephen

2017-01-01

Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes.
An economic model of the manufacturers' aircraft production and airline earnings potential, volume 3

NASA Technical Reports Server (NTRS)

Kneafsey, J. T.; Hill, R. M.

1978-01-01

A behavioral explanation of the process of technological change in the U. S. aircraft manufacturing and airline industries is presented. The model indicates the principal factors which influence the aircraft (airframe) manufacturers in researching, developing, constructing and promoting new aircraft technology; and the financial requirements which determine the delivery of new aircraft to the domestic trunk airlines. Following specification and calibration of the model, the types and numbers of new aircraft were estimated historically for each airline's fleet. Examples of possible applications of the model to forecasting an individual airline's future fleet also are provided. The functional form of the model is a composite which was derived from several preceding econometric models developed on the foundations of the economics of innovation, acquisition, and technological change and represents an important contribution to the improved understanding of the economic and financial requirements for aircraft selection and production. The model's primary application will be to forecast the future types and numbers of new aircraft required for each domestic airline's fleet.
Long short-term memory for speaker generalization in supervised speech separation

PubMed Central

Chen, Jitong; Wang, DeLiang

2017-01-01

Speech separation can be formulated as learning to estimate a time-frequency mask from acoustic features extracted from noisy speech. For supervised speech separation, generalization to unseen noises and unseen speakers is a critical issue. Although deep neural networks (DNNs) have been successful in noise-independent speech separation, DNNs are limited in modeling a large number of speakers. To improve speaker generalization, a separation model based on long short-term memory (LSTM) is proposed, which naturally accounts for temporal dynamics of speech. Systematic evaluation shows that the proposed model substantially outperforms a DNN-based model on unseen speakers and unseen noises in terms of objective speech intelligibility. Analyzing LSTM internal representations reveals that LSTM captures long-term speech contexts. It is also found that the LSTM model is more advantageous for low-latency speech separation and it, without future frames, performs better than the DNN model with future frames. The proposed model represents an effective approach for speaker- and noise-independent speech separation. PMID:28679261
Technical Review of the CENWP Computational Fluid Dynamics Model of the John Day Dam Forebay

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

Rakowski, Cynthia L.; Serkowski, John A.; Richmond, Marshall C.

The US Army Corps of Engineers Portland District (CENWP) has developed a computational fluid dynamics (CFD) model of the John Day forebay on the Columbia River to aid in the development and design of alternatives to improve juvenile salmon passage at the John Day Project. At the request of CENWP, Pacific Northwest National Laboratory (PNNL) Hydrology Group has conducted a technical review of CENWP's CFD model run in CFD solver software, STAR-CD. PNNL has extensive experience developing and applying 3D CFD models run in STAR-CD for Columbia River hydroelectric projects. The John Day forebay model developed by CENWP is adequatelymore » configured and validated. The model is ready for use simulating forebay hydraulics for structural and operational alternatives. The approach and method are sound, however CENWP has identified some improvements that need to be made for future models and for modifications to this existing model.« less
Modeling and analysis of the DSS-14 antenna control system

NASA Technical Reports Server (NTRS)

Gawronski, W.; Bartos, R.

1996-01-01

An improvement of pointing precision of the DSS-14 antenna is planned for the near future. In order to analyze the improvement limits and to design new controllers, a precise model of the antenna and the servo is developed, including a finite element model of the antenna structure and detailed models of the hydraulic drives and electronic parts. The DSS-14 antenna control system has two modes of operation: computer mode and precision mode. The principal goal of this investigation is to develop the model of the computer mode and to evaluate its performance. The DSS-14 antenna computer model consists of the antenna structure and drives in azimuth and elevation. For this model, the position servo loop is derived, and simulations of the closed-loop antenna dynamics are presented. The model is significantly different from that for the 34-m beam-waveguide antennas.
Time series analysis of malaria in Afghanistan: using ARIMA models to predict future trends in incidence.

PubMed

Anwar, Mohammad Y; Lewnard, Joseph A; Parikh, Sunil; Pitzer, Virginia E

2016-11-22

Malaria remains endemic in Afghanistan. National control and prevention strategies would be greatly enhanced through a better ability to forecast future trends in disease incidence. It is, therefore, of interest to develop a predictive tool for malaria patterns based on the current passive and affordable surveillance system in this resource-limited region. This study employs data from Ministry of Public Health monthly reports from January 2005 to September 2015. Malaria incidence in Afghanistan was forecasted using autoregressive integrated moving average (ARIMA) models in order to build a predictive tool for malaria surveillance. Environmental and climate data were incorporated to assess whether they improve predictive power of models. Two models were identified, each appropriate for different time horizons. For near-term forecasts, malaria incidence can be predicted based on the number of cases in the four previous months and 12 months prior (Model 1); for longer-term prediction, malaria incidence can be predicted using the rates 1 and 12 months prior (Model 2). Next, climate and environmental variables were incorporated to assess whether the predictive power of proposed models could be improved. Enhanced vegetation index was found to have increased the predictive accuracy of longer-term forecasts. Results indicate ARIMA models can be applied to forecast malaria patterns in Afghanistan, complementing current surveillance systems. The models provide a means to better understand malaria dynamics in a resource-limited context with minimal data input, yielding forecasts that can be used for public health planning at the national level.
Dynamic and Regression Modeling of Ocean Variability in the Tide-Gauge Record at Seasonal and Longer Periods

NASA Technical Reports Server (NTRS)

Hill, Emma M.; Ponte, Rui M.; Davis, James L.

2007-01-01

Comparison of monthly mean tide-gauge time series to corresponding model time series based on a static inverted barometer (IB) for pressure-driven fluctuations and a ocean general circulation model (OM) reveals that the combined model successfully reproduces seasonal and interannual changes in relative sea level at many stations. Removal of the OM and IB from the tide-gauge record produces residual time series with a mean global variance reduction of 53%. The OM is mis-scaled for certain regions, and 68% of the residual time series contain a significant seasonal variability after removal of the OM and IB from the tide-gauge data. Including OM admittance parameters and seasonal coefficients in a regression model for each station, with IB also removed, produces residual time series with mean global variance reduction of 71%. Examination of the regional improvement in variance caused by scaling the OM, including seasonal terms, or both, indicates weakness in the model at predicting sea-level variation for constricted ocean regions. The model is particularly effective at reproducing sea-level variation for stations in North America, Europe, and Japan. The RMS residual for many stations in these areas is 25-35 mm. The production of "cleaner" tide-gauge time series, with oceanographic variability removed, is important for future analysis of nonsecular and regionally differing sea-level variations. Understanding the ocean model's strengths and weaknesses will allow for future improvements of the model.
TORNADO-WARNING PERFORMANCE IN THE PAST AND FUTURE: A Perspective from Signal Detection Theory.

NASA Astrophysics Data System (ADS)

Brooks, Harold E.

2004-06-01

Changes over the years in tornado-warning performance in the United States can be modeled from the perspective of signal detection theory. From this view, it can be seen that there have been distinct periods of change in performance, most likely associated with deployment of radars, and changes in scientific understanding and training. The model also makes it clear that improvements in the false alarm ratio can only occur at the cost of large decreases in the probability of detection, or with large improvements in the overall quality of the warning system.

Predictions of LDEF radioactivity and comparison with measurements

NASA Technical Reports Server (NTRS)

Armstrong, T. W.; Colborn, B. L.; Harmon, B. A.; Laird, C. E.

1995-01-01

As part of the program to utilize LDEF data for evaluation and improvement of current ionizing radiation environmental models and related predictive methods for future LEO missions, calculations have been carried out to compare with the induced radioactivity measured in metal samples placed on LDEF. The predicted activation is about a factor of two lower than observed, which is attributed to deficiencies in the AP8 trapped proton model. It is shown that this finding based on activation sample data is consistent with comparisons made with other LDEF activation and dose data. Plans for confirming these results utilizing additional LDEF data sets, and plans for model modifications to improve the agreement with LDEF data, are discussed.
Using genetic algorithms to optimise current and future health planning--the example of ambulance locations.

PubMed

Sasaki, Satoshi; Comber, Alexis J; Suzuki, Hiroshi; Brunsdon, Chris

2010-01-28

Ambulance response time is a crucial factor in patient survival. The number of emergency cases (EMS cases) requiring an ambulance is increasing due to changes in population demographics. This is decreasing ambulance response times to the emergency scene. This paper predicts EMS cases for 5-year intervals from 2020, to 2050 by correlating current EMS cases with demographic factors at the level of the census area and predicted population changes. It then applies a modified grouping genetic algorithm to compare current and future optimal locations and numbers of ambulances. Sets of potential locations were evaluated in terms of the (current and predicted) EMS case distances to those locations. Future EMS demands were predicted to increase by 2030 using the model (R2 = 0.71). The optimal locations of ambulances based on future EMS cases were compared with current locations and with optimal locations modelled on current EMS case data. Optimising the location of ambulance stations locations reduced the average response times by 57 seconds. Current and predicted future EMS demand at modelled locations were calculated and compared. The reallocation of ambulances to optimal locations improved response times and could contribute to higher survival rates from life-threatening medical events. Modelling EMS case 'demand' over census areas allows the data to be correlated to population characteristics and optimal 'supply' locations to be identified. Comparing current and future optimal scenarios allows more nuanced planning decisions to be made. This is a generic methodology that could be used to provide evidence in support of public health planning and decision making.
Limitations in predicting the space radiation health risk for exploration astronauts.

PubMed

Chancellor, Jeffery C; Blue, Rebecca S; Cengel, Keith A; Auñón-Chancellor, Serena M; Rubins, Kathleen H; Katzgraber, Helmut G; Kennedy, Ann R

2018-01-01

Despite years of research, understanding of the space radiation environment and the risk it poses to long-duration astronauts remains limited. There is a disparity between research results and observed empirical effects seen in human astronaut crews, likely due to the numerous factors that limit terrestrial simulation of the complex space environment and extrapolation of human clinical consequences from varied animal models. Given the intended future of human spaceflight, with efforts now to rapidly expand capabilities for human missions to the moon and Mars, there is a pressing need to improve upon the understanding of the space radiation risk, predict likely clinical outcomes of interplanetary radiation exposure, and develop appropriate and effective mitigation strategies for future missions. To achieve this goal, the space radiation and aerospace community must recognize the historical limitations of radiation research and how such limitations could be addressed in future research endeavors. We have sought to highlight the numerous factors that limit understanding of the risk of space radiation for human crews and to identify ways in which these limitations could be addressed for improved understanding and appropriate risk posture regarding future human spaceflight.
Internal dosimetry monitoring equipment: Present and future

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

Selby, J.; Carbaugh, E.H.; Lynch, T.P.

1993-09-01

We have attempted to characterize the current and future status of in vivo and in vitro measurement programs coupled with the associated radioanalytical methods and workplace monitoring. Developments in these areas must be carefully integrated by internal dosimetrists, radiochemists and field health physicists. Their goal should be uniform improvement rather than to focus on one specific area (e.g., dose modeling) to the neglect of other areas where the measurement capabilities are substantially less sophisticated and, therefore, the potential source of error is greatest.
An investigation of the role of current and future remote sensing data systems in numerical meteorology

NASA Technical Reports Server (NTRS)

Diak, George R.; Smith, William L.

1992-01-01

A flexible system for performing observing system simulation experiments which made contributions to meteorology across all elements of the observing system simulation experiment (OSSE) components was developed. Future work will seek better understanding of the links between satellite-measured radiation and radiative transfer in the clear, cloudy and precipitating atmosphere and investigate how that understanding might be applied to improve the depiction of the initial state and the treatment of physical processes in forecast models of the atmosphere.
Engineering photorespiration: current state and future possibilities.

PubMed

Peterhansel, C; Krause, K; Braun, H-P; Espie, G S; Fernie, A R; Hanson, D T; Keech, O; Maurino, V G; Mielewczik, M; Sage, R F

2013-07-01

Reduction of flux through photorespiration has been viewed as a major way to improve crop carbon fixation and yield since the energy-consuming reactions associated with this pathway were discovered. This view has been supported by the biomasses increases observed in model species that expressed artificial bypass reactions to photorespiration. Here, we present an overview about the major current attempts to reduce photorespiratory losses in crop species and provide suggestions for future research priorities. © 2012 German Botanical Society and The Royal Botanical Society of the Netherlands.
Using Citizen Science Data to Model the Distributions of Common Songbirds of Turkey Under Different Global Climatic Change Scenarios

PubMed Central

Abolafya, Moris; Onmuş, Ortaç; Şekercioğlu, Çağan H.; Bilgin, Raşit

2013-01-01

In this study, we evaluated the potential impact of climate change on the distributions of Turkey’s songbirds in the 21st century by modelling future distributions of 20 resident and nine migratory species under two global climate change scenarios. We combined verified data from an ornithological citizen science initiative (www.kusbank.org) with maximum entropy modeling and eight bioclimatic variables to estimate species distributions and projections for future time periods. Model predictions for resident and migratory species showed high variability, with some species projected to lose and others projected to gain suitable habitat. Our study helps improve the understanding of the current and potential future distributions of Turkey’s songbirds and their responses to climate change, highlights effective strategies to maximize avian conservation efforts in the study region, and provides a model for using citizen science data for biodiversity research in a large developing country with few professional field biologists. Our results demonstrate that climate change will not affect every species equally in Turkey. Expected range reductions in some breeding species will increase the risk of local extinction, whereas others are likely to expand their ranges. PMID:23844151
Using citizen science data to model the distributions of common songbirds of Turkey under different global climatic change scenarios.

PubMed

Abolafya, Moris; Onmuş, Ortaç; Şekercioğlu, Çağan H; Bilgin, Raşit

2013-01-01

In this study, we evaluated the potential impact of climate change on the distributions of Turkey's songbirds in the 21st century by modelling future distributions of 20 resident and nine migratory species under two global climate change scenarios. We combined verified data from an ornithological citizen science initiative (www.kusbank.org) with maximum entropy modeling and eight bioclimatic variables to estimate species distributions and projections for future time periods. Model predictions for resident and migratory species showed high variability, with some species projected to lose and others projected to gain suitable habitat. Our study helps improve the understanding of the current and potential future distributions of Turkey's songbirds and their responses to climate change, highlights effective strategies to maximize avian conservation efforts in the study region, and provides a model for using citizen science data for biodiversity research in a large developing country with few professional field biologists. Our results demonstrate that climate change will not affect every species equally in Turkey. Expected range reductions in some breeding species will increase the risk of local extinction, whereas others are likely to expand their ranges.
Balancing the benefits and costs of antibiotic drugs: the TREAT model.

PubMed

Leibovici, L; Paul, M; Andreassen, S

2010-12-01

TREAT is a computerized decision support system aimed at improving empirical antibiotic treatment of inpatients with suspected bacterial infections. It contains a model that balances, for each antibiotic choice (including 'no antibiotics'), expected benefit and expected costs. The main benefit afforded by appropriate, empirical, early antibiotic treatment in moderate to severe infections is a better chance of survival. Each antibiotic drug was consigned three cost components: cost of the drug and administration; cost of side effects; and costs of future resistance. 'No treatment' incurs no costs. The model worked well for decision support. Its analysis showed, yet again, that for moderate to severe infections, a model that does not include costs of resistance to future patients will always return maximum antibiotic treatment. Two major moral decisions are hidden in the model: how to take into account the limited life-expectancy and limited quality of life of old or very sick patients; and how to assign a value for a life-year of a future, unnamed patient vs. the present, individual patient. © 2010 The Authors. Clinical Microbiology and Infection © 2010 European Society of Clinical Microbiology and Infectious Diseases.
Data Assimilation in the Solar Wind: Challenges and First Results

NASA Astrophysics Data System (ADS)

Lang, Matthew; Browne, Phil; van Leeuwen, Peter Jan; Owens, Matt

2017-04-01

Data assimilation (DA) is currently underused in the solar wind field to improve the modelled variables using observations. Data assimilation has been used in Numerical Weather Prediction (NWP) models with great success, and it can be seen that the improvement of DA methods in NWP modelling has led to improvements in forecasting skill over the past 20-30 years. The state of the art DA methods developed for NWP modelling have never been applied to space weather models, hence it is important to implement the improvements that can be gained from these methods to improve our understanding of the solar wind and how to model it. The ENLIL solar wind model has been coupled to the EMPIRE data assimilation library in order to apply these advanced data assimilation methods to a space weather model. This coupling allows multiple data assimilation methods to be applied to ENLIL with relative ease. I shall discuss twin experiments that have been undertaken, applying the LETKF to the ENLIL model when a CME occurs in the observation and when it does not. These experiments show that there is potential in the application of advanced data assimilation methods to the solar wind field, however, there is still a long way to go until it can be applied effectively. I shall discuss these issues and suggest potential avenues for future research in this area.
Soil carbon management in large-scale Earth system modelling: implications for crop yields and nitrogen leaching

NASA Astrophysics Data System (ADS)

Olin, S.; Lindeskog, M.; Pugh, T. A. M.; Schurgers, G.; Wårlind, D.; Mishurov, M.; Zaehle, S.; Stocker, B. D.; Smith, B.; Arneth, A.

2015-06-01

We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land use-enabled dynamic vegetation model LPJ-GUESS. Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. We explore trade-offs between important ecosystem services that can be provided from agricultural fields such as crop yields, retention of nitrogen and carbon storage. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till and cover-crops proposed in literature is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C-N interactions in agricultural ecosystems under future environmental change, and the effects these have on terrestrial biogeochemical cycles.
Current and anticipated uses of thermal-hydraulic codes in Germany

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

Teschendorff, V.; Sommer, F.; Depisch, F.

1997-07-01

In Germany, one third of the electrical power is generated by nuclear plants. ATHLET and S-RELAP5 are successfully applied for safety analyses of the existing PWR and BWR reactors and possible future reactors, e.g. EPR. Continuous development and assessment of thermal-hydraulic codes are necessary in order to meet present and future needs of licensing organizations, utilities, and vendors. Desired improvements include thermal-hydraulic models, multi-dimensional simulation, computational speed, interfaces to coupled codes, and code architecture. Real-time capability will be essential for application in full-scope simulators. Comprehensive code validation and quantification of uncertainties are prerequisites for future best-estimate analyses.
Approaches and possible improvements in the area of multibody dynamics modeling

NASA Technical Reports Server (NTRS)

Lips, K. W.; Singh, R.

1987-01-01

A wide ranging look is taken at issues involved in the dynamic modeling of complex, multibodied orbiting space systems. Capabilities and limitations of two major codes (DISCOS, TREETOPS) are assessed and possible extensions to the CONTOPS software are outlined. In addition, recommendations are made concerning the direction future development should take in order to achieve higher fidelity, more computationally efficient multibody software solutions.
The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review.

PubMed

Sanderson, Michael; Arbuthnott, Katherine; Kovats, Sari; Hajat, Shakoor; Falloon, Pete

2017-01-01

Heat related mortality is of great concern for public health, and estimates of future mortality under a warming climate are important for planning of resources and possible adaptation measures. Papers providing projections of future heat-related mortality were critically reviewed with a focus on the use of climate model data. Some best practice guidelines are proposed for future research. The electronic databases Web of Science and PubMed/Medline were searched for papers containing a quantitative estimate of future heat-related mortality. The search was limited to papers published in English in peer-reviewed journals up to the end of March 2017. Reference lists of relevant papers and the citing literature were also examined. The wide range of locations studied and climate data used prevented a meta-analysis. A total of 608 articles were identified after removal of duplicate entries, of which 63 were found to contain a quantitative estimate of future mortality from hot days or heat waves. A wide range of mortality models and climate model data have been used to estimate future mortality. Temperatures in the climate simulations used in these studies were projected to increase. Consequently, all the papers indicated that mortality from high temperatures would increase under a warming climate. The spread in projections of future climate by models adds substantial uncertainty to estimates of future heat-related mortality. However, many studies either did not consider this source of uncertainty, or only used results from a small number of climate models. Other studies showed that uncertainty from changes in populations and demographics, and the methods for adaptation to warmer temperatures were at least as important as climate model uncertainty. Some inconsistencies in the use of climate data (for example, using global mean temperature changes instead of changes for specific locations) and interpretation of the effects on mortality were apparent. Some factors which have not been considered when estimating future mortality are summarised. Most studies have used climate data generated using scenarios with medium and high emissions of greenhouse gases. More estimates of future mortality using climate information from the mitigation scenario RCP2.6 are needed, as this scenario is the only one under which the Paris Agreement to limit global warming to 2°C or less could be realised. Many of the methods used to combine modelled data with local climate observations are simplistic. Quantile-based methods might offer an improved approach, especially for temperatures at the ends of the distributions. The modelling of adaptation to warmer temperatures in mortality models is generally arbitrary and simplistic, and more research is needed to better quantify adaptation. Only a small number of studies included possible changes in population and demographics in their estimates of future mortality, meaning many estimates of mortality could be biased low. Uncertainty originating from establishing a mortality baseline, climate projections, adaptation and population changes is important and should be considered when estimating future mortality.
Expected Improvements in VLBI Measurements of the Earth's Orientation

NASA Technical Reports Server (NTRS)

Ma, Chopo

2003-01-01

Measurements of the Earth s orientation since the 1970s using space geodetic techniques have provided a continually expanding and improving data set for studies of the Earth s structure and the distribution of mass and angular momentum. The accuracy of current one-day measurements is better than 100 microarcsec for the motion of the pole with respect to the celestial and terrestrial reference frames and better than 3 microsec for the rotation around the pole. VLBI uniquely provides the three Earth orientation parameters (nutation and UTI) that relate the Earth to the extragalactic celestial reference frame. The accuracy and resolution of the VLBI Earth orientation time series can be expected to improve substantially in the near future because of refinements in the realization of the celestial reference frame, improved modeling of the troposphere and non-linear station motions, larger observing networks, optimized scheduling, deployment of disk-based Mark V recorders, full use of Mark IV capabilities, and e-VLBI. More radical future technical developments will be discussed.
Thermal and Environmental Barrier Coatings for Advanced Propulsion Engine Systems

NASA Technical Reports Server (NTRS)

Zhu, Dong-Ming; Miller, Robert A.

2004-01-01

Ceramic thermal and environmental barrier coatings (TEBCs) are used in gas turbine engines to protect engine hot-section components in the harsh combustion environments, and extend component lifetimes. For future high performance engines, the development of advanced ceramic barrier coating systems will allow these coatings to be used to simultaneously increase engine operating temperature and reduce cooling requirements, thereby leading to significant improvements in engine power density and efficiency. In order to meet future engine performance and reliability requirements, the coating systems must be designed with increased high temperature stability, lower thermal conductivity, and improved thermal stress and erosion resistance. In this paper, ceramic coating design and testing considerations will be described for high temperature and high-heat-flux engine applications in hot corrosion and oxidation, erosion, and combustion water vapor environments. Further coating performance and life improvements will be expected by utilizing advanced coating architecture design, composition optimization, and improved processing techniques, in conjunction with modeling and design tools.
Using a cloud to replenish parched groundwater modeling efforts.

PubMed

Hunt, Randall J; Luchette, Joseph; Schreuder, Willem A; Rumbaugh, James O; Doherty, John; Tonkin, Matthew J; Rumbaugh, Douglas B

2010-01-01

Groundwater models can be improved by introduction of additional parameter flexibility and simultaneous use of soft-knowledge. However, these sophisticated approaches have high computational requirements. Cloud computing provides unprecedented access to computing power via the Internet to facilitate the use of these techniques. A modeler can create, launch, and terminate "virtual" computers as needed, paying by the hour, and save machine images for future use. Such cost-effective and flexible computing power empowers groundwater modelers to routinely perform model calibration and uncertainty analysis in ways not previously possible.
Using a cloud to replenish parched groundwater modeling efforts

USGS Publications Warehouse

Hunt, Randall J.; Luchette, Joseph; Schreuder, Willem A.; Rumbaugh, James O.; Doherty, John; Tonkin, Matthew J.; Rumbaugh, Douglas B.

2010-01-01

Groundwater models can be improved by introduction of additional parameter flexibility and simultaneous use of soft-knowledge. However, these sophisticated approaches have high computational requirements. Cloud computing provides unprecedented access to computing power via the Internet to facilitate the use of these techniques. A modeler can create, launch, and terminate “virtual” computers as needed, paying by the hour, and save machine images for future use. Such cost-effective and flexible computing power empowers groundwater modelers to routinely perform model calibration and uncertainty analysis in ways not previously possible.
GenePRIMP: Improving Microbial Gene Prediction Quality

ScienceCinema

Pati, Amrita

2018-01-24

Amrita Pati of the DOE Joint Genome Institute's Genome Biology group talks about a computational pipeline that evaluates the accuracy of gene models in genomes and metagenomes at different stages of finishing at the "Sequencing, Finishing, Analysis in the Future" meeting in Santa Fe, NM.
Assessing the Needs of Adults for Continuing Education: A Model.

ERIC Educational Resources Information Center

Moore, Donald E., Jr.

1980-01-01

Reviews the needs assessment studies described in this journal issue. Concludes that (1) lessons from completed needs assessments can help continuing education practitioners plan and conduct future studies, and (2) a rational, need-reduction, decision-making approach can improve continuing education programs. (CT)

The Elusive Goal of World Literacy.

ERIC Educational Resources Information Center

Bhola, H. S.; And Others

1980-01-01

This issue is devoted to discussions of world literacy and national programs which comparative studies indicate may be used as models for future UNESCO international campaigns. Individual articles explore economic incentives for literacy motivation, radio learning projects, media programs in Jamaica, literacy improvement in Somalia, and a…
New Developments in Education for the Seventies.

ERIC Educational Resources Information Center

Spaulding, Seth

Theories relating to proposed improvements in education are discussed. Changes in curricula, contributions of fields such as psychology, and issues currently being debated are given consideration. Innovative models and approaches are proposed, and several interesting speculations are offered related to the future of education. Following the…
Integrating Human Factors into Space Vehicle Processing for Risk Management

NASA Technical Reports Server (NTRS)

Woodbury, Sarah; Richards, Kimberly J.

2008-01-01

This presentation will discuss the multiple projects performed in United Space Alliance's Human Engineering Modeling and Performance (HEMAP) Lab, improvements that resulted from analysis, and the future applications of the HEMAP Lab for risk assessment by evaluating human/machine interaction and ergonomic designs.
Unlocking Triticeae genomics to sustainably feed the future

PubMed Central

Mochida, Keiichi; Shinozaki, Kazuo

2013-01-01

The tribe Triticeae includes the major crops wheat and barley. Within the last few years, the whole genomes of four Triticeae species—barley, wheat, Tausch’s goatgrass (Aegilops tauschii) and wild einkorn wheat (Triticum urartu)—have been sequenced. The availability of these genomic resources for Triticeae plants and innovative analytical applications using next-generation sequencing technologies are helping to revitalize our approaches in genetic work and to accelerate improvement of the Triticeae crops. Comparative genomics and integration of genomic resources from Triticeae plants and the model grass Brachypodium distachyon are aiding the discovery of new genes and functional analyses of genes in Triticeae crops. Innovative approaches and tools such as analysis of next-generation populations, evolutionary genomics and systems approaches with mathematical modeling are new strategies that will help us discover alleles for adaptive traits to future agronomic environments. In this review, we provide an update on genomic tools for use with Triticeae plants and Brachypodium and describe emerging approaches toward crop improvements in Triticeae. PMID:24204022
Organic matter export to the seafloor in the Baltic Sea: Drivers of change and future projections.

PubMed

Tamelander, Tobias; Spilling, Kristian; Winder, Monica

2017-12-01

The impact of environmental change and anthropogenic stressors on coastal marine systems will strongly depend on changes in the magnitude and composition of organic matter exported from the water column to the seafloor. Knowledge of vertical export in the Baltic Sea is synthesised to illustrate how organic matter deposition will respond to climate warming, climate-related changes in freshwater runoff, and ocean acidification. Pelagic heterotrophic processes are suggested to become more important in a future warmer climate, with negative feedbacks to organic matter deposition to the seafloor. This is an important step towards improved oxygen conditions in the near-bottom layer that will reduce the release of inorganic nutrients from the sediment and hence counteract further eutrophication. The evaluation of these processes in ecosystem models, validated by field observations, will significantly advance the understanding of the system's response to environmental change and will improve the use of such models in management of coastal areas.
Towards a Future ICRF Realization

NASA Technical Reports Server (NTRS)

Ma, Chopo; Gordon, D.; MacMillan, D.; Petrov, L.; Smith, David E. (Technical Monitor)

2001-01-01

The data and analysis for the ICRF were completed in 1995 to define a frame to which the Hipparcos optical catalog could be fixed. Additional observations on most of the 608 sources in the overall ICRF catalog have been acquired using a small portion of geodetic observing time as well as astrometric sessions concentrating on the southern hemisphere. Positions of new sources have been determined, including approx.1200 from a VLBA phase calibrator survey. A future ICRF realization will require improved geophysical modeling, sophisticated treatment of position variations and/or source structure, optimized data selection and weighting, and reidentification of defining sources. The motivation for the next realization could be significant improvement in accuracy and density or preparation for optical extragalactic catalogs with microarcsecond precision.
Towards a Future ICRF Realization

NASA Technical Reports Server (NTRS)

Ma, Chopo; Gordon, David; MacMillan, Daniel; Petrov, Leonid

2002-01-01

The data and analysis for the ICRF were completed in 1995 to define a frame to which the Hipparcos optical catalog could be fixed. Additional observations on most of the 608 sources in the overall ICRF catalog have been acquired using a small portion of geodetic observing time as well as astrometric sessions concentrating on the Southern Hemisphere. Positions of new sources have been determined, including approximately 1200 from a VLBA phase calibrator survey. A future ICRF realization will require improved geophysical modeling, sophisticated treatment of position variations and/or source structure, optimized data selection and weighting, and re-identification of defining sources. The motivation for the next realization could be significant improvement in accuracy and density or preparation for optical extragalactic catalogs with microarcsecond precision.
Current trends and future prospects of biotechnological interventions through tissue culture in apple.

PubMed

Bhatti, Shammi; Jha, Gopaljee

2010-11-01

Apple (Malus domestica Borkh.), which is a widely cultivated, important economic fruit crop with nutritive and medicinal importance, has emerged as a model horticultural crop in this post-genomic era. Apple cultivation is heavily dependent on climatic condition and is susceptible to several diseases caused by fungi, bacteria, viruses, insects, etc. Extensive research work has been carried out to standardize tissue culture protocols and utilize them in apple improvement. We review the in vitro shoot multiplication, rooting, transformation and regeneration methodologies in apple and tabulate various such protocols for easy reference. The utility and limitation of transgenesis in apple improvement have also been summarized. The concepts of marker-free plants, use of non-antibiotic resistance selectable markers, and cisgenic and intragenic approaches are highlighted. Furthermore, the limitations, current trends and future prospects of tissue culture-mediated biotechnological interventions in apple improvement are discussed.
Modelling structural and plasma facing materials for fusion power plants: Recent advances and outstanding issues in the EURATOM fusion materials programme

NASA Astrophysics Data System (ADS)

Boutard, Jean-Louis; Dudarev, Sergei; Rieth, Michael

2011-10-01

EFDA Fusion Materials Topical Group was established at the end of 2007 to coordinate the EU effort on the development of structural and protection materials able to withstand the very demanding operating conditions of a future DEMO power plant. Focusing on a selection of well identified materials issues, including the behaviour of Reduced Activation Ferritic-Martensitic steels, and W-alloys under the foreseen operation conditions in a future DEMO, this paper describes recent advances in physical modelling and experimental validation, contributing to the definition of chemical composition and microstructure of materials with improved in-service stability at high temperature, high neutron flux and intense ion bombardment.
Accounting for downscaling and model uncertainty in fine-resolution seasonal climate projections over the Columbia River Basin

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Moradkhani, Hamid; Rana, Arun

2018-01-01

Climate change is expected to have severe impacts on natural systems as well as various socio-economic aspects of human life. This has urged scientific communities to improve the understanding of future climate and reduce the uncertainties associated with projections. In the present study, ten statistically downscaled CMIP5 GCMs at 1/16th deg. spatial resolution from two different downscaling procedures are utilized over the Columbia River Basin (CRB) to assess the changes in climate variables and characterize the associated uncertainties. Three climate variables, i.e. precipitation, maximum temperature, and minimum temperature, are studied for the historical period of 1970-2000 as well as future period of 2010-2099, simulated with representative concentration pathways of RCP4.5 and RCP8.5. Bayesian Model Averaging (BMA) is employed to reduce the model uncertainty and develop a probabilistic projection for each variable in each scenario. Historical comparison of long-term attributes of GCMs and observation suggests a more accurate representation for BMA than individual models. Furthermore, BMA projections are used to investigate future seasonal to annual changes of climate variables. Projections indicate significant increase in annual precipitation and temperature, with varied degree of change across different sub-basins of CRB. We then characterized uncertainty of future projections for each season over CRB. Results reveal that model uncertainty is the main source of uncertainty, among others. However, downscaling uncertainty considerably contributes to the total uncertainty of future projections, especially in summer. On the contrary, downscaling uncertainty appears to be higher than scenario uncertainty for precipitation.
Predicting Liver Transplant Capacity Using Discrete Event Simulation.

PubMed

Toro-Díaz, Hector; Mayorga, Maria E; Barritt, A Sidney; Orman, Eric S; Wheeler, Stephanie B

2015-08-01

The number of liver transplants (LTs) performed in the US increased until 2006 but has since declined despite an ongoing increase in demand. This decline may be due in part to decreased donor liver quality and increasing discard of poor-quality livers. We constructed a discrete event simulation (DES) model informed by current donor characteristics to predict future LT trends through the year 2030. The data source for our model is the United Network for Organ Sharing database, which contains patient-level information on all organ transplants performed in the US. Previous analysis showed that liver discard is increasing and that discarded organs are more often from donors who are older, are obese, have diabetes, and donated after cardiac death. Given that the prevalence of these factors is increasing, the DES model quantifies the reduction in the number of LTs performed through 2030. In addition, the model estimatesthe total number of future donors needed to maintain the current volume of LTs and the effect of a hypothetical scenario of improved reperfusion technology.We also forecast the number of patients on the waiting list and compare this with the estimated number of LTs to illustrate the impact that decreased LTs will have on patients needing transplants. By altering assumptions about the future donor pool, this model can be used to develop policy interventions to prevent a further decline in this lifesaving therapy. To our knowledge, there are no similar predictive models of future LT use based on epidemiological trends. © The Author(s) 2014.
Predicting Liver Transplant Capacity Using Discrete Event Simulation

PubMed Central

Diaz, Hector Toro; Mayorga, Maria; Barritt, A. Sidney; Orman, Eric S.; Wheeler, Stephanie B.

2014-01-01

The number of liver transplants (LTs) performed in the US increased until 2006, but has since declined despite an ongoing increase in demand. This decline may be due in part to decreased donor liver quality and increasing discard of poor quality livers. We constructed a Discrete Event Simulation (DES) model informed by current donor characteristics to predict future LT trends through the year 2030. The data source for our model is the United Network for Organ Sharing database, which contains patient level information on all organ transplants performed in the US. Previous analysis showed that liver discard is increasing and that discarded organs are more often from donors who are older, obese, have diabetes, and donated after cardiac death. Given that the prevalence of these factors is increasing, the DES model quantifies the reduction in the number of LTs performed through 2030. In addition, the model estimates the total number of future donors needed to maintain the current volume of LTs, and the effect of a hypothetical scenario of improved reperfusion technology. We also forecast the number of patients on the waiting list and compare this to the estimated number of LTs to illustrate the impact that decreased LTs will have on patients needing transplants. By altering assumptions about the future donor pool, this model can be used to develop policy interventions to prevent a further decline in this life saving therapy. To our knowledge, there are no similar predictive models of future LT use based on epidemiologic trends. PMID:25391681
XSIM Final Report: Modelling the Past and Future of Identity Management for Scientific Collaborations

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

Cowles, Robert; Jackson, Craig; Welch, Von

The eXtreme Science Identity Management (XSIM1) research project: collected and analyzed real world data on virtual organization (VO) identity management (IdM) representing the last 15+ years of collaborative DOE science; constructed a descriptive VO IdM model based on that data; used the model and existing trends to project the direction for IdM in the 2020 timeframe; and provided guidance to scientific collaborations and resource providers that are implementing or seeking to improve IdM functionality. XSIM conducted over 20 semistructured interviews of representatives from scientific collaborations and resource providers, both in the US and Europe; the interviewees supported diverse set ofmore » scientific collaborations and disciplines. We developed a definition of “trust,” a key concept in IdM, to understand how varying trust models affect where IdM functions are performed. The model identifies how key IdM data elements are utilized in collaborative scientific workflows, and it has the flexibility to describe past, present and future trust relationships and IdM implementations. During the funding period, we gave more than two dozen presentations to socialize our work, encourage feedback, and improve the model; we also published four refereed papers. Additionally, we developed, presented, and received favorable feedback on three white papers providing practical advice to collaborations and/or resource providers.« less
Using aircraft and satellite observations to improve regulatory air quality models

NASA Astrophysics Data System (ADS)

Canty, T. P.; Vinciguerra, T.; Anderson, D. C.; Carpenter, S. F.; Goldberg, D. L.; Hembeck, L.; Montgomery, L.; Liu, X.; Salawitch, R. J.; Dickerson, R. R.

2014-12-01

Federal and state agencies rely on EPA approved models to develop attainment strategies that will bring states into compliance with the National Ambient Air Quality Standards (NAAQS). We will describe modifications to the Community Multi-Scale Air Quality (CMAQ) model and Comprehensive Air Quality Model with Extensions (CAMx) frameworks motivated by analysis of NASA satellite and aircraft measurements. Observations of tropospheric column NO2 from OMI have already led to the identification of an important deficiency in the chemical mechanisms used by models; data collected during the DISCOVER-AQ field campaign has been instrumental in devising an improved representation of the chemistry of nitrogen species. Our recent work has focused on the use of: OMI observations of tropospheric O3 to assess and improve the representation of boundary conditions used by AQ models, OMI NO2 to derive a top down NOx emission inventory from commercial shipping vessels that affect air quality in the Eastern U.S., and OMI HCHO to assess the C5H8 emission inventories provided by bioegenic emissions models. We will describe how these OMI-driven model improvements are being incorporated into the State Implementation Plans (SIPs) being prepared for submission to EPA in summer 2015 and how future modeling efforts may be impacted by our findings.
Neural signatures of experience-based improvements in deterministic decision-making.

PubMed

Tremel, Joshua J; Laurent, Patryk A; Wolk, David A; Wheeler, Mark E; Fiez, Julie A

2016-12-15

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. Copyright © 2016 Elsevier B.V. All rights reserved.
Neural signatures of experience-based improvements in deterministic decision-making

PubMed Central

Tremel, Joshua J.; Laurent, Patryk A.; Wolk, David A.; Wheeler, Mark E.; Fiez, Julie A.

2016-01-01

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. PMID:27523644
Clouds enhance Greenland ice sheet mass loss

NASA Astrophysics Data System (ADS)

Van Tricht, Kristof; Gorodetskaya, Irina V.; L'Ecuyer, Tristan; Lenaerts, Jan T. M.; Lhermitte, Stef; Noel, Brice; Turner, David D.; van den Broeke, Michiel R.; van Lipzig, Nicole P. M.

2015-04-01

Clouds have a profound influence on both the Arctic and global climate, while they still represent one of the key uncertainties in climate models, limiting the fidelity of future climate projections. The potentially important role of thin liquid-containing clouds over Greenland in enhancing ice sheet melt has recently gained interest, yet current research is spatially and temporally limited, focusing on particular events, and their large scale impact on the surface mass balance remains unknown. We used a combination of satellite remote sensing (CloudSat - CALIPSO), ground-based observations and climate model (RACMO) data to show that liquid-containing clouds warm the Greenland ice sheet 94% of the time. High surface reflectivity (albedo) for shortwave radiation reduces the cloud shortwave cooling effect on the absorbed fluxes, while not influencing the absorption of longwave radiation. Cloud warming over the ice sheet therefore dominates year-round. Only when albedo values drop below ~0.6 in the coastal areas during summer, the cooling effect starts to overcome the warming effect. The year-round excess of energy due to the presence of liquid-containing clouds has an extensive influence on the mass balance of the ice sheet. Simulations using the SNOWPACK snow model showed not only a strong influence of these liquid-containing clouds on melt increase, but also on the increased sublimation mass loss. Simulations with the Community Earth System Climate Model for the end of the 21st century (2080-2099) show that Greenland clouds contain more liquid water path and less ice water path. This implies that cloud radiative forcing will be further enhanced in the future. Our results therefore urge the need for improving cloud microphysics in climate models, to improve future projections of ice sheet mass balance and global sea level rise.
Mechanics of airflow in the human nasal airways.

PubMed

Doorly, D J; Taylor, D J; Schroter, R C

2008-11-30

The mechanics of airflow in the human nasal airways is reviewed, drawing on the findings of experimental and computational model studies. Modelling inevitably requires simplifications and assumptions, particularly given the complexity of the nasal airways. The processes entailed in modelling the nasal airways (from defining the model, to its production and, finally, validating the results) is critically examined, both for physical models and for computational simulations. Uncertainty still surrounds the appropriateness of the various assumptions made in modelling, particularly with regard to the nature of flow. New results are presented in which high-speed particle image velocimetry (PIV) and direct numerical simulation are applied to investigate the development of flow instability in the nasal cavity. These illustrate some of the improved capabilities afforded by technological developments for future model studies. The need for further improvements in characterising airway geometry and flow together with promising new methods are briefly discussed.
What’s Needed from Climate Modeling to Advance Actionable Science for Water Utilities?

NASA Astrophysics Data System (ADS)

Barsugli, J. J.; Anderson, C. J.; Smith, J. B.; Vogel, J. M.

2009-12-01

“…perfect information on climate change is neither available today nor likely to be available in the future, but … over time, as the threats climate change poses to our systems grow more real, predicting those effects with greater certainty is non-discretionary. We’re not yet at a level at which climate change projections can drive climate change adaptation.” (Testimony of WUCA Staff Chair David Behar to the House Committee on Science and Technology, May 5, 2009) To respond to this challenge, the Water Utility Climate Alliance (WUCA) has sponsored a white paper titled “Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change. ” This report concerns how investments in the science of climate change, and in particular climate modeling and downscaling, can best be directed to help make climate projections more actionable. The meaning of “model improvement” can be very different depending on whether one is talking to a climate model developer or to a water manager trying to incorporate climate projections in to planning. We first surveyed the WUCA members on present and potential uses of climate model projections and on climate inputs to their various system models. Based on those surveys and on subsequent discussions, we identified four dimensions along which improvement in modeling would make the science more “actionable”: improved model agreement on change in key parameters; narrowing the range of model projections; providing projections at spatial and temporal scales that match water utilities system models; providing projections that water utility planning horizons. With these goals in mind we developed four options for improving global-scale climate modeling and three options for improving downscaling that will be discussed. However, there does not seem to be a single investment - the proverbial “magic bullet” -- which will substantially reduce the range of model projections at the scales at which utility planning is conducted. In the near term we feel strongly that water utilities and climate scientists should work together to leverage the upcoming Coupled Model Intercomparison Project, Phase 5 (CMIP5; a coordinated set climate model experiments that will be used to support the upcoming IPCC Fifth Assessment) to better benefit water utilities. In the longer term, even with model and downscaling improvements, it is very likely that substantial uncertainty about future climate change at the desired spatial and temporal scales will remain. Nonetheless, there is no doubt the climate is changing, and the challenge is to work with what we have, or what we can reasonably expect to have in the coming years to make the best decisions we can.
Effects of emotion on prospection during decision-making.

PubMed

Worthy, Darrell A; Byrne, Kaileigh A; Fields, Sherecce

2014-01-01

In two experiments we examined the role of emotion, specifically worry, anxiety, and mood, on prospection during decision-making. Worry is a particularly relevant emotion to study in the context of prospection because high levels of worry may make individuals more aversive toward the uncertainty associated with the prospect of obtaining future improvements in rewards or states. Thus, high levels of worry might lead to reduced prospection during decision-making and enhance preference for immediate over delayed rewards. In Experiment 1 participants performed a two-choice dynamic decision-making task where they were required to choose between one option (the decreasing option) which provided larger immediate rewards but declines in future states, and another option (the increasing option) which provided smaller immediate rewards but improvements in future states, making it the optimal choice. High levels of worry were associated with poorer performance in the task. Additionally, fits of a sophisticated reinforcement-learning model that incorporated both reward-based and state-based information suggested that individuals reporting high levels of worry gave greater weight to the immediate rewards they would receive on each trial than to the degree to which each action would lead to improvements in their future state. In Experiment 2 we found that high levels of worry were associated with greater delay discounting using a standard delay discounting task. Combined, the results suggest that high levels of worry are associated with reduced prospection during decision-making. We attribute these results to high worriers' aversion toward the greater uncertainty associated with attempting to improve future rewards than to maximize immediate reward. These results have implications for researchers interested in the effects of emotion on cognition, and suggest that emotion strongly affects the focus on temporal outcomes during decision-making.

A Bayesian network based framework for real-time crash prediction on the basic freeway segments of urban expressways.

PubMed

Hossain, Moinul; Muromachi, Yasunori

2012-03-01

The concept of measuring the crash risk for a very short time window in near future is gaining more practicality due to the recent advancements in the fields of information systems and traffic sensor technology. Although some real-time crash prediction models have already been proposed, they are still primitive in nature and require substantial improvements to be implemented in real-life. This manuscript investigates the major shortcomings of the existing models and offers solutions to overcome them with an improved framework and modeling method. It employs random multinomial logit model to identify the most important predictors as well as the most suitable detector locations to acquire data to build such a model. Afterwards, it applies Bayesian belief net (BBN) to build the real-time crash prediction model. The model has been constructed using high resolution detector data collected from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited, Japan. It has been specifically built for the basic freeway segments and it predicts the chance of formation of a hazardous traffic condition within the next 4-9 min for a particular 250 meter long road section. The performance evaluation results reflect that at an average threshold value the model is able to successful classify 66% of the future crashes with a false alarm rate less than 20%. Copyright © 2011 Elsevier Ltd. All rights reserved.
Co-streaming classes: a follow-up study in improving the user experience to better reach users.

PubMed

Hayes, Barrie E; Handler, Lara J; Main, Lindsey R

2011-01-01

Co-streaming classes have enabled library staff to extend open classes to distance education students and other users. Student evaluations showed that the model could be improved. Two areas required attention: audio problems experienced by online participants and staff teaching methods. Staff tested equipment and adjusted software configuration to improve user experience. Staff training increased familiarity with specialized teaching techniques and troubleshooting procedures. Technology testing and staff training were completed, and best practices were developed and applied. Class evaluations indicate improvements in classroom experience. Future plans include expanding co-streaming to more classes and on-going data collection, evaluation, and improvement of classes.
Survey of possibility for volcanic energy development

NASA Astrophysics Data System (ADS)

1990-03-01

Volcanic areas, clarification of heat source structure, evaluation of resources and problems on utilization techniques were arranged to search the possibility of future volcanic heat source. It is necessary to improve the exploration accuracy by combining geophysical exploration with geological and geochemical surveys in order to explorate a magma reservoir. Especially, seismic exploration is effective. The surveying procedure is as follows: confirmation of magma existence and grasping the whole image, evaluation of resources, clarification of three-dimensional distribution of magma in a promising area, and heat structure survey by heat flow measurement and others to construct more accurate model for resources. This model is verified finally by practical drilling. Promising areas which are worthy of development, are active volcanic areas in Kyushu, Hakkoda nad Hokkaido. It is desirable to make drilling to the depth of 3 km or magma reservoir to develop the future heat source. It is also required to improve the thermal resistance and corrosion resistance of materials to be used. Heat extraction by a single well is most realistic and the closed coaxial double pipe heat exchanger or open heat exchanger in the well will be used to improve the extraction.
Adapting wheat in Europe for climate change.

PubMed

Semenov, M A; Stratonovitch, P; Alghabari, F; Gooding, M J

2014-05-01

Increasing cereal yield is needed to meet the projected increased demand for world food supply of about 70% by 2050. Sirius, a process-based model for wheat, was used to estimate yield potential for wheat ideotypes optimized for future climatic projections for ten wheat growing areas of Europe. It was predicted that the detrimental effect of drought stress on yield would be decreased due to enhanced tailoring of phenology to future weather patterns, and due to genetic improvements in the response of photosynthesis and green leaf duration to water shortage. Yield advances could be made through extending maturation and thereby improve resource capture and partitioning. However the model predicted an increase in frequency of heat stress at meiosis and anthesis. Controlled environment experiments quantify the effects of heat and drought at booting and flowering on grain numbers and potential grain size. A current adaptation of wheat to areas of Europe with hotter and drier summers is a quicker maturation which helps to escape from excessive stress, but results in lower yields. To increase yield potential and to respond to climate change, increased tolerance to heat and drought stress should remain priorities for the genetic improvement of wheat.
Personal Health Record Use in the United States: Forecasting Future Adoption Levels

PubMed Central

Huerta, Timothy R

2016-01-01

Background Personal health records (PHRs) offer a tremendous opportunity to generate consumer support in pursing the triple aim of reducing costs, increasing access, and improving care quality. Moreover, surveys in the United States indicate that consumers want Web-based access to their medical records. However, concerns that consumers’ low health information literacy levels and physicians’ resistance to sharing notes will limit PHRs’ utility to a relatively small portion of the population have reduced both the product innovation and policy imperatives. Objective The purpose of our study was 3-fold: first, to report on US consumers’ current level of PHR activity; second, to describe the roles of imitation and innovation influence factors in determining PHR adoption rates; and third, to forecast future PHR diffusion uptake among US consumers under 3 scenarios. Methods We used secondary data from the Health Information National Trends Survey (HINTS) of US citizens for the survey years 2008, 2011, and 2013. Applying technology diffusion theory and Bass modeling, we evaluated 3 future PHR adoption scenarios by varying the introduction dates. Results All models displayed the characteristic diffusion S-curve indicating that the PHR technology is likely to achieve significant market penetration ahead of meaningful use goals. The best-performing model indicates that PHR adoption will exceed 75% by 2020. Therefore, the meaningful use program targets for PHR adoption are below the rates likely to occur without an intervention. Conclusions The promise of improved care quality and cost savings through better consumer engagement prompted the US Institute of Medicine to call for universal PHR adoption in 1999. The PHR products available as of 2014 are likely to meet and exceed meaningful use stage 3 targets before 2020 without any incentive. Therefore, more ambitious uptake and functionality availability should be incorporated into future goals. PMID:27030105
Integrated assessment of future potential global change scenarios and their hydrological impacts in coastal aquifers - a new tool to analyse management alternatives in the Plana Oropesa-Torreblanca aquifer

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, David; Renau-Pruñonosa, Arianna; Llopis-Albert, Carlos; Morell, Ignacio; Collados-Lara, Antonio-Juan; Senent-Aparicio, Javier; Baena-Ruiz, Leticia

2018-05-01

Any change in the components of the water balance in a coastal aquifer, whether natural or anthropogenic, can alter the freshwater-salt water equilibrium. In this sense climate change (CC) and land use and land cover (LULC) change might significantly influence the availability of groundwater resources in the future. These coastal systems demand an integrated analysis of quantity and quality issues to obtain an appropriate assessment of hydrological impacts using density-dependent flow solutions. The aim of this work is to perform an integrated analysis of future potential global change (GC) scenarios and their hydrological impacts in a coastal aquifer, the Plana Oropesa-Torreblanca aquifer. It is a Mediterranean aquifer that extends over 75 km2 in which important historical LULC changes have been produced and are planned for the future. Future CC scenarios will be defined by using an equi-feasible and non-feasible ensemble of projections based on the results of a multi-criteria analysis of the series generated from several regional climatic models with different downscaling approaches. The hydrological impacts of these CC scenarios combined with future LULC scenarios will be assessed with a chain of models defined by a sequential coupling of rainfall-recharge models, crop irrigation requirements and irrigation return models (for the aquifer and its neighbours that feed it), and a density-dependent aquifer approach. This chain of models, calibrated using the available historical data, allow testing of the conceptual approximation of the aquifer behaviour. They are also fed with series representatives of potential global change scenarios in order to perform a sensitivity analysis regarding future scenarios of rainfall recharge, lateral flows coming from the hydraulically connected neighbouring aquifer, agricultural recharge (taking into account expected future LULC changes) and sea level rise (SLR). The proposed analysis is valuable for improving our knowledge about the aquifer, and so comprises a tool to design sustainable adaptation management strategies taking into account the uncertainty in future GC conditions and their impacts. The results show that GC scenarios produce significant increases in the variability of flow budget components and in the salinity.
Constraining primordial non-Gaussianity with bispectrum and power spectrum from upcoming optical and radio surveys

NASA Astrophysics Data System (ADS)

Karagiannis, Dionysios; Lazanu, Andrei; Liguori, Michele; Raccanelli, Alvise; Bartolo, Nicola; Verde, Licia

2018-07-01

We forecast constraints on primordial non-Gaussianity (PNG) and bias parameters from measurements of galaxy power spectrum and bispectrum in future radio continuum and optical surveys. In the galaxy bispectrum, we consider a comprehensive list of effects, including the bias expansion for non-Gaussian initial conditions up to second order, redshift space distortions, redshift uncertainties and theoretical errors. These effects are all combined in a single PNG forecast for the first time. Moreover, we improve the bispectrum modelling over previous forecasts, by accounting for trispectrum contributions. All effects have an impact on final predicted bounds, which varies with the type of survey. We find that the bispectrum can lead to improvements up to a factor ˜5 over bounds based on the power spectrum alone, leading to significantly better constraints for local-type PNG, with respect to current limits from Planck. Future radio and photometric surveys could obtain a measurement error of σ (f_{NL}^{loc}) ≈ 0.2. In the case of equilateral PNG, galaxy bispectrum can improve upon present bounds only if significant improvements in the redshift determinations of future, large volume, photometric or radio surveys could be achieved. For orthogonal non-Gaussianity, expected constraints are generally comparable to current ones.
Constraining Primordial non-Gaussianity with Bispectrum and Power Spectum from Upcoming Optical and Radio Surveys

NASA Astrophysics Data System (ADS)

Karagiannis, Dionysios; Lazanu, Andrei; Liguori, Michele; Raccanelli, Alvise; Bartolo, Nicola; Verde, Licia

2018-04-01

We forecast constraints on primordial non-Gaussianity (PNG) and bias parameters from measurements of galaxy power spectrum and bispectrum in future radio continuum and optical surveys. In the galaxy bispectrum, we consider a comprehensive list of effects, including the bias expansion for non-Gaussian initial conditions up to second order, redshift space distortions, redshift uncertainties and theoretical errors. These effects are all combined in a single PNG forecast for the first time. Moreover, we improve the bispectrum modelling over previous forecasts, by accounting for trispectrum contributions. All effects have an impact on final predicted bounds, which varies with the type of survey. We find that the bispectrum can lead to improvements up to a factor ˜5 over bounds based on the power spectrum alone, leading to significantly better constraints for local-type PNG, with respect to current limits from Planck. Future radio and photometric surveys could obtain a measurement error of σ (f_{NL}^{loc}) ≈ 0.2. In the case of equilateral PNG, galaxy bispectrum can improve upon present bounds only if significant improvements in the redshift determinations of future, large volume, photometric or radio surveys could be achieved. For orthogonal non-Gaussianity, expected constraints are generally comparable to current ones.
The future of nearshore processes research

USGS Publications Warehouse

Elko, Nicole A.; Feddersen, Falk; Foster, Diane; Hapke, Cheryl J.; McNinch, Jesse E.; Mulligan, Ryan P.; Tuba Ӧzkan-Haller, H.; Plant, Nathaniel G.; Raubenheimer, Britt

2014-01-01

The nearshore is the transition region between land and the continental shelf including (from onshore to offshore) coastal plains, wetlands, estuaries, coastal cliffs, dunes, beaches, surf zones (regions of wave breaking), and the inner shelf (Figure ES-1). Nearshore regions are vital to the national economy, security, commerce, and recreation. The nearshore is dynamically evolving, is often densely populated, and is under increasing threat from sea level rise, long-term erosion, extreme storms, and anthropogenic influences. Worldwide, almost one billion people live at elevations within 10 m of present sea level. Long-term erosion threatens communities, infrastructure, ecosystems, and habitat. Extreme storms can cause billions of dollars of damage. Degraded water quality impacts ecosystem and human health. Nearshore processes, the complex interactions between water, sediment, biota, and humans, must be understood and predicted to manage this often highly developed yet vulnerable nearshore environment. Over the past three decades, the understanding of nearshore processes has improved. However, societal needs are growing with increased coastal urbanization and threats of future climate change, and significant scientific challenges remain. To address these challenges, members of academia, industry, and federal agencies (USGS, USACE, NPS, NOAA, FEMA, ONR) met at the “The Past and Future of Nearshore Processes Research: Reflections on the Sallenger Years and a New Vision for the Future” workshop to develop a nearshore processes research vision where societal needs and science challenges intersect. The resulting vision is comprised of three broad research themes: Long-term coastal evolution due to natural and anthropogenic processes: As global climate change alters the rates of sea level rise and potentially storm patterns and coastal urbanization increases over the coming decades, an understanding of coastal evolution is critical. Improved knowledge of long-term morphological, ecological, and societal processes and their interactions will result in an improved ability to simulate coastal change. This will enable proactive solutions for resilient coasts and better guidance for reducing coastal vulnerability.Extreme Events: Flooding, erosion, and the subsequent recovery: Hurricane Sandy caused flooding and erosion along hundreds of miles of shoreline, flooded New York City, and impacted communities and infrastructure. Overall U.S. coastal extreme event related economic losses have increased substantially. Furthermore, climate change may cause an increase in coastal extreme events and rising sea levels could increase the occurrence of extreme events. Addressing this research theme will result in an improved understanding of the physical processes during extreme events, leading to improved models of flooding, erosion, and recovery. The resulting societal benefit will be more resilient coastal communities.The physical, biological and chemical processes impacting human and ecosystem health: Nearshore regions are used for recreation, tourism, and human habitation, and provide habitat and valuable ecosystem services. These areas must be sustained for future generations, however overall coastal water quality is declining due to microbial pathogens, fertilizers, pesticides, and heavy metal contamination, threatening ecosystem and human health. To ensure sustainable nearshore regions, predictive real-time water- and sediment-based based pollutant modeling capabilities must be developed, which requires expanding our knowledge of the physics, chemistry, and biology of the nearshore. The resulting societal benefits will include better beach safety, healthier ecosystems, and improved mitigation and regulatory policies.The scientists and engineers of the U.S. nearshore community are poised to make significant progress on these research themes, which have significant societal impact. The U.S. nearshore community, including academic, government, and industry colleagues, recommends multi-agency investment into a coordinated development of observational and modeling research infrastructure to address these themes, as discussed in the whitepaper. The observational infrastructure should include development of new sensors and methods, focused observational programs, and expanded nearshore observing systems. The modeling infrastructure should include improved process representation, better model coupling, incorporation of data assimilation techniques, and testing of real-time models. The observations will provide test beds to compare and improve models.
PICUS v1.6 - enhancing the water cycle within a hybrid ecosystem model to assess the provision of drinking water in a changing climate

NASA Astrophysics Data System (ADS)

Schimmel, A.; Rammer, W.; Lexer, M. J.

2012-04-01

The PICUS model is a hybrid ecosystem model which is based on a 3D patch model and a physiological stand level production model. The model includes, among others, a submodel of bark beetle disturbances in Norway spruce and a management module allowing any silvicultural treatment to be mimicked realistically. It has been tested intensively for its ability to realistically reproduce tree growth and stand dynamics in complex structured mixed and mono-species temperate forest ecosystems. In several applications the models capacity to generate relevant forest related attributes which were subsequently fed into indicator systems to assess sustainable forest management under current and future climatic conditions has been proven. However, the relatively coarse monthly temporal resolution of the driving climate data as well as the process resolution of the major water relations within the simulated ecosystem hampered the inclusion of more detailed physiologically based assessments of drought conditions and water provisioning ecosystem services. In this contribution we present the improved model version PICUS v1.6 focusing on the newly implemented logic for the water cycle calculations. Transpiration, evaporation from leave surfaces and the forest floor, snow cover and snow melt as well as soil water dynamics in several soil horizons are covered. In enhancing the model overarching goal was to retain the large-scale applicability by keeping the input requirements to a minimum while improving the physiological foundation of water related ecosystem processes. The new model version is tested against empirical time series data. Future model applications are outlined.
Modeling returns volatility: Realized GARCH incorporating realized risk measure

NASA Astrophysics Data System (ADS)

Jiang, Wei; Ruan, Qingsong; Li, Jianfeng; Li, Ye

2018-06-01

This study applies realized GARCH models by introducing several risk measures of intraday returns into the measurement equation, to model the daily volatility of E-mini S&P 500 index futures returns. Besides using the conventional realized measures, realized volatility and realized kernel as our benchmarks, we also use generalized realized risk measures, realized absolute deviation, and two realized tail risk measures, realized value-at-risk and realized expected shortfall. The empirical results show that realized GARCH models using the generalized realized risk measures provide better volatility estimation for the in-sample and substantial improvement in volatility forecasting for the out-of-sample. In particular, the realized expected shortfall performs best for all of the alternative realized measures. Our empirical results reveal that future volatility may be more attributable to present losses (risk measures). The results are robust to different sample estimation windows.
Transient Mathematical Modeling for Liquid Rocket Engine Systems: Methods, Capabilities, and Experience

NASA Technical Reports Server (NTRS)

Seymour, David C.; Martin, Michael A.; Nguyen, Huy H.; Greene, William D.

2005-01-01

The subject of mathematical modeling of the transient operation of liquid rocket engines is presented in overview form from the perspective of engineers working at the NASA Marshall Space Flight Center. The necessity of creating and utilizing accurate mathematical models as part of liquid rocket engine development process has become well established and is likely to increase in importance in the future. The issues of design considerations for transient operation, development testing, and failure scenario simulation are discussed. An overview of the derivation of the basic governing equations is presented along with a discussion of computational and numerical issues associated with the implementation of these equations in computer codes. Also, work in the field of generating usable fluid property tables is presented along with an overview of efforts to be undertaken in the future to improve the tools use for the mathematical modeling process.
Transient Mathematical Modeling for Liquid Rocket Engine Systems: Methods, Capabilities, and Experience

NASA Technical Reports Server (NTRS)

Martin, Michael A.; Nguyen, Huy H.; Greene, William D.; Seymout, David C.

2003-01-01

The subject of mathematical modeling of the transient operation of liquid rocket engines is presented in overview form from the perspective of engineers working at the NASA Marshall Space Flight Center. The necessity of creating and utilizing accurate mathematical models as part of liquid rocket engine development process has become well established and is likely to increase in importance in the future. The issues of design considerations for transient operation, development testing, and failure scenario simulation are discussed. An overview of the derivation of the basic governing equations is presented along with a discussion of computational and numerical issues associated with the implementation of these equations in computer codes. Also, work in the field of generating usable fluid property tables is presented along with an overview of efforts to be undertaken in the future to improve the tools use for the mathematical modeling process.
Assessing and forecasting population health: integrating knowledge and beliefs in a comprehensive framework.

PubMed

Van Meijgaard, Jeroen; Fielding, Jonathan E; Kominski, Gerald F

2009-01-01

A comprehensive population health-forecasting model has the potential to interject new and valuable information about the future health status of the population based on current conditions, socioeconomic and demographic trends, and potential changes in policies and programs. Our Health Forecasting Model uses a continuous-time microsimulation framework to simulate individuals' lifetime histories by using birth, risk exposures, disease incidence, and death rates to mark changes in the state of the individual. The model generates a reference forecast of future health in California, including details on physical activity, obesity, coronary heart disease, all-cause mortality, and medical expenditures. We use the model to answer specific research questions, inform debate on important policy issues in public health, support community advocacy, and provide analysis on the long-term impact of proposed changes in policies and programs, thus informing stakeholders at all levels and supporting decisions that can improve the health of populations.
Enhancing metaproteomics-The value of models and defined environmental microbial systems

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

Herbst, Florian-Alexander; Lünsmann, Vanessa; Kjeldal, Henrik

Metaproteomicsthe large-scale characterization of the entire protein complement of environmental microbiota at a given point in timehas provided new features to study complex microbial communities in order to unravel these black boxes. Some new technical challenges arose that were not an issue for classical proteome analytics before that could be tackled by the application of different model systems. Here, we review different current and future model systems for metaproteome analysis. We introduce model systems for clinical and biotechnological research questions including acid mine drainage, anaerobic digesters, and activated sludge, following a short introduction to microbial communities and metaproteomics. Model systemsmore » are useful to evaluate the challenges encountered within (but not limited to) metaproteomics, including species complexity and coverage, biomass availability, or reliable protein extraction. Moreover, the implementation of model systems can be considered as a step forward to better understand microbial community responses and ecological functions of single member organisms. In the future, improvements are necessary to fully explore complex environmental systems by metaproteomics.« less
Enhancing metaproteomics-The value of models and defined environmental microbial systems

DOE PAGES

Herbst, Florian-Alexander; Lünsmann, Vanessa; Kjeldal, Henrik; ...

2016-01-21

Metaproteomicsthe large-scale characterization of the entire protein complement of environmental microbiota at a given point in timehas provided new features to study complex microbial communities in order to unravel these black boxes. Some new technical challenges arose that were not an issue for classical proteome analytics before that could be tackled by the application of different model systems. Here, we review different current and future model systems for metaproteome analysis. We introduce model systems for clinical and biotechnological research questions including acid mine drainage, anaerobic digesters, and activated sludge, following a short introduction to microbial communities and metaproteomics. Model systemsmore » are useful to evaluate the challenges encountered within (but not limited to) metaproteomics, including species complexity and coverage, biomass availability, or reliable protein extraction. Moreover, the implementation of model systems can be considered as a step forward to better understand microbial community responses and ecological functions of single member organisms. In the future, improvements are necessary to fully explore complex environmental systems by metaproteomics.« less
CFE-2 Experiment Run

NASA Image and Video Library

2013-11-11

ISS038-E-000269 (11 Nov. 2013) --- NASA astronaut Michael Hopkins, Expedition 38 flight engineer, conducts a session with the Capillary Flow Experiment (CFE) in the Harmony node of the International Space Station. CFE is a suite of fluid physics experiments that investigate how fluids move up surfaces in microgravity. The results aim to improve current computer models that are used by designers of low gravity fluid systems and may improve fluid transfer systems for water on future spacecraft.
CFE-2 Experiment Run

NASA Image and Video Library

2013-11-11

ISS038-E-000263 (11 Nov. 2013) --- NASA astronaut Michael Hopkins, Expedition 38 flight engineer, conducts a session with the Capillary Flow Experiment (CFE) in the Harmony node of the International Space Station. CFE is a suite of fluid physics experiments that investigate how fluids move up surfaces in microgravity. The results aim to improve current computer models that are used by designers of low gravity fluid systems and may improve fluid transfer systems for water on future spacecraft.
Swanson conducts CFE session

NASA Image and Video Library

2014-07-03

ISS040-E-032827 (3 July 2014) --- NASA astronaut Steve Swanson, Expedition 40 commander, conducts a session with the Capillary Flow Experiment (CFE) in the Harmony node of the International Space Station. CFE is a suite of fluid physics experiments that investigate how fluids move up surfaces in microgravity. The results aim to improve current computer models that are used by designers of low gravity fluid systems and may improve fluid transfer systems for water on future spacecraft.
Swanson conducts CFE session

NASA Image and Video Library

2014-07-03

ISS040-E-032825 (3 July 2014) --- NASA astronaut Steve Swanson, Expedition 40 commander, conducts a session with the Capillary Flow Experiment (CFE) in the Harmony node of the International Space Station. CFE is a suite of fluid physics experiments that investigate how fluids move up surfaces in microgravity. The results aim to improve current computer models that are used by designers of low gravity fluid systems and may improve fluid transfer systems for water on future spacecraft.

Swanson conducts CFE session

NASA Image and Video Library

2014-07-03

ISS040-E-032820 (3 July 2014) --- NASA astronaut Steve Swanson, Expedition 40 commander, conducts a session with the Capillary Flow Experiment (CFE) in the Harmony node of the International Space Station. CFE is a suite of fluid physics experiments that investigate how fluids move up surfaces in microgravity. The results aim to improve current computer models that are used by designers of low gravity fluid systems and may improve fluid transfer systems for water on future spacecraft.
Improving Offensive Performance through Opponent Modeling

DTIC Science & Technology

2009-01-01

of of- fensive players , we improve on the yardage gained. Introduction By accessing the play history of your opponent, it is pos- sible to glean...review a video play history of the player taking a penalty kick; iden- tifying the player’s tendency to kick to the left allowed the goalkeeper to...recognition and 3) off-line review. In online track- ing, immediate future actions of individual players (passes, feints) are predicted, whereas in online
Improvements on GPS Location Cluster Analysis for the Prediction of Large Carnivore Feeding Activities: Ground-Truth Detection Probability and Inclusion of Activity Sensor Measures

PubMed Central

Blecha, Kevin A.; Alldredge, Mat W.

2015-01-01

Animal space use studies using GPS collar technology are increasingly incorporating behavior based analysis of spatio-temporal data in order to expand inferences of resource use. GPS location cluster analysis is one such technique applied to large carnivores to identify the timing and location of feeding events. For logistical and financial reasons, researchers often implement predictive models for identifying these events. We present two separate improvements for predictive models that future practitioners can implement. Thus far, feeding prediction models have incorporated a small range of covariates, usually limited to spatio-temporal characteristics of the GPS data. Using GPS collared cougar (Puma concolor) we include activity sensor data as an additional covariate to increase prediction performance of feeding presence/absence. Integral to the predictive modeling of feeding events is a ground-truthing component, in which GPS location clusters are visited by human observers to confirm the presence or absence of feeding remains. Failing to account for sources of ground-truthing false-absences can bias the number of predicted feeding events to be low. Thus we account for some ground-truthing error sources directly in the model with covariates and when applying model predictions. Accounting for these errors resulted in a 10% increase in the number of clusters predicted to be feeding events. Using a double-observer design, we show that the ground-truthing false-absence rate is relatively low (4%) using a search delay of 2–60 days. Overall, we provide two separate improvements to the GPS cluster analysis techniques that can be expanded upon and implemented in future studies interested in identifying feeding behaviors of large carnivores. PMID:26398546
Multi-scale predictions of coniferous forest mortality in the northern hemisphere

NASA Astrophysics Data System (ADS)

McDowell, N. G.

2015-12-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our incomplete understanding of the fundamental physiological thresholds of vegetation mortality during drought limits our ability to accurately simulate future vegetation distributions and associated climate feedbacks. Here we integrate experimental evidence with models to show potential widespread loss of needleleaf evergreen trees (NET; ~ conifers) within the Southwest USA by 2100; with rising temperature being the primary cause of mortality. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ypd) thresholds (April-August mean) beyond which photosynthesis, stomatal and hydraulic conductance, and carbohydrate availability approached zero. Empirical and mechanistic models accurately predicted NET Ypd, and 91% of predictions (10/11) exceeded mortality thresholds within the 21st century due to temperature rise. Completely independent global models predicted >50% loss of northern hemisphere NET by 2100, consistent with the findings for Southwest USA. The global models disagreed with the ecosystem process models in regards to future mortality in Southwest USA, however, highlighting the potential underestimates of future NET mortality as simulated by the global models and signifying the importance of improving regional predictions. Taken together, these results from the validated regional predictions and the global simulations predict global-scale conifer loss in coming decades under projected global warming.
Likelihood of achieving air quality targets under model uncertainties.

PubMed

Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

2011-01-01

Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.
Using a full annual cycle model to evaluate long-term population viability of the conservation-reliant Kirtland's warbler after successful recovery

USGS Publications Warehouse

Brown, Donald J.; Ribic, Christine; Donner, Deahn M.; Nelson, Mark D.; Bocetti, Carol I.; Deloria-Sheffield, Christie M.

2017-01-01

Long-term management planning for conservation-reliant migratory songbirds is particularly challenging because habitat quality in different stages and geographic locations of the annual cycle can have direct and carry-over effects that influence the population dynamics. The Neotropical migratory songbird Kirtland's warbler Setophaga kirtlandii (Baird 1852) is listed as endangered under the U.S. Endangered Species Act and Near Threatened under the IUCN Red List. This conservation-reliant species is being considered for U.S. federal delisting because the species has surpassed the designated 1000 breeding pairs recovery threshold since 2001.To help inform the delisting decision and long-term management efforts, we developed a population simulation model for the Kirtland's warbler that incorporated both breeding and wintering grounds habitat dynamics, and projected population viability based on current environmental conditions and potential future management scenarios. Future management scenarios included the continuation of current management conditions, reduced productivity and carrying capacity due to the changes in habitat suitability from the creation of experimental jack pine Pinus banksiana (Lamb.) plantations, and reduced productivity from alteration of the brown-headed cowbird Molothrus ater (Boddaert 1783) removal programme.Linking wintering grounds precipitation to productivity improved the accuracy of the model for replicating past observed population dynamics. Our future simulations indicate that the Kirtland's warbler population is stable under two potential future management scenarios: (i) continuation of current management practices and (ii) spatially restricting cowbird removal to the core breeding area, assuming that cowbirds reduce productivity in the remaining patches by ≤41%. The additional future management scenarios we assessed resulted in population declines.Synthesis and applications. Our study indicates that the Kirtland's warbler population is stable under current management conditions and that the jack pine plantation and cowbird removal programmes continue to be necessary for the long-term persistence of the species. This study represents one of the first attempts to incorporate full annual cycle dynamics into a population viability analysis for a migratory bird, and our results indicate that incorporating wintering grounds dynamics improved the model performance.
Upstream factors affecting Tualatin River algae—Tracking the 2008 Anabaena algae bloom to Wapato Lake, Oregon

USGS Publications Warehouse

Rounds, Stewart A.; Carpenter, Kurt D.; Fesler, Kristel J.; Dorsey, Jessica L.

2015-12-17

The results and insights derived from this study can be used to enhance future monitoring and data collection strategies designed to improve water quality and plankton models and better predict dissolved-oxygen concentrations in the lower Tualatin River.
Detecting in-field variation in photosynthetic capacity of trangenically modifed plants with hyperspectral imaging.

NASA Astrophysics Data System (ADS)

Meacham, K.; Montes, C.; Pederson, T.; Wu, J.; Guan, K.; Bernacchi, C.

2017-12-01

Improved photosynthetic rates have been shown to increase crop biomass, making improved photosynthesis a focus for driving future grain yield increases. Improving the photosynthetic pathway offers opportunity to meet food demand, but requires high throughput measurement techniques to detect photosynthetic variation in natural accessions and transgenically modified plants. Gas exchange measurements are the most widely used method of measuring photosynthesis in field trials but this process is laborious and slow, and requires further modeling to estimate meaningful parameters and to upscale to the plot or canopy level. In field trials of tobacco with modifications made to the photosynthetic pathway, we infer the maximum carboxylation rate of Rubisco (Vcmax) and maximum electron transport rate (Jmax) and detect photosynthetic variation from hyperspectral imaging with a partial least squares regression technique. Ground-truth measurements from photosynthetic gas exchange, a full-range (400-2500nm) handheld spectroadiometer with leaf clip, hyperspectral indices, and extractions of leaf pigments support the model. The results from a range of wild-type cultivars and from genetically modified germplasm suggest that the opportunity for rapid selection of top performing genotypes from among thousands of plots. This research creates the opportunity to extend agroecosystem models from simplified "one-cultivar" generic parameterization to better represent a full suite of current and future crop cultivars for a wider range of environmental conditions.
Using the Whole School, Whole Community, Whole Child Model: Implications for Practice

PubMed Central

Rooney, Laura E; Videto, Donna M; Birch, David A

2015-01-01

BACKGROUND Schools, school districts, and communities seeking to implement the Whole School, Whole Community, Whole Child (WSCC) model should carefully and deliberately select planning, implementation, and evaluation strategies. METHODS In this article, we identify strategies, steps, and resources within each phase that can be integrated into existing processes that help improve health outcomes and academic achievement. Implementation practices may vary across districts depending upon available resources and time commitments. RESULTS Obtaining and maintaining administrative support at the beginning of the planning phase is imperative for identifying and implementing strategies and sustaining efforts to improve student health and academic outcomes. Strategy selection hinges on priority needs, community assets, and resources identified through the planning process. Determining the results of implementing the WSCC is based upon a comprehensive evaluation that begins during the planning phase. Evaluation guides success in attaining goals and objectives, assesses strengths and weaknesses, provides direction for program adjustment, revision, and future planning, and informs stakeholders of the effect of WSCC, including the effect on academic indicators. CONCLUSIONS With careful planning, implementation, and evaluation efforts, use of the WSCC model has the potential of focusing family, community, and school education and health resources to increase the likelihood of better health and academic success for students and improve school and community life in the present and in the future. PMID:26440824
International quality improvement initiatives.

PubMed

Hickey, Patricia A; Connor, Jean A; Cherian, Kotturathu M; Jenkins, Kathy; Doherty, Kaitlin; Zhang, Haibo; Gaies, Michael; Pasquali, Sara; Tabbutt, Sarah; St Louis, James D; Sarris, George E; Kurosawa, Hiromi; Jonas, Richard A; Sandoval, Nestor; Tchervenkov, Christo I; Jacobs, Jeffery P; Stellin, Giovanni; Kirklin, James K; Garg, Rajnish; Vener, David F

2017-12-01

Across the globe, the implementation of quality improvement science and collaborative learning has positively affected the care and outcomes for children born with CHD. These efforts have advanced the collective expertise and performance of inter-professional healthcare teams. In this review, we highlight selected quality improvement initiatives and strategies impacting the field of cardiovascular care and describe implications for future practice and research. The continued leveraging of technology, commitment to data transparency, focus on team-based practice, and recognition of cultural norms and preferences ensure the success of sustainable models of global collaboration.
Integrating ecosystem services analysis into scenario planning practice: accounting for street tree benefits with i-Tree valuation in Central Texas.

PubMed

Hilde, Thomas; Paterson, Robert

2014-12-15

Scenario planning continues to gain momentum in the United States as an effective process for building consensus on long-range community plans and creating regional visions for the future. However, efforts to integrate more sophisticated information into the analytical framework to help identify important ecosystem services have lagged in practice. This is problematic because understanding the tradeoffs of land consumption patterns on ecological integrity is central to mitigating the environmental degradation caused by land use change and new development. In this paper we describe how an ecosystem services valuation model, i-Tree, was integrated into a mainstream scenario planning software tool, Envision Tomorrow, to assess the benefits of public street trees for alternative future development scenarios. The tool is then applied to development scenarios from the City of Hutto, TX, a Central Texas Sustainable Places Project demonstration community. The integrated tool represents a methodological improvement for scenario planning practice, offers a way to incorporate ecosystem services analysis into mainstream planning processes, and serves as an example of how open source software tools can expand the range of issues available for community and regional planning consideration, even in cases where community resources are limited. The tool also offers room for future improvements; feasible options include canopy analysis of various future land use typologies, as well as a generalized street tree model for broader U.S. application. Copyright © 2014 Elsevier Ltd. All rights reserved.
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.
Modeling future scenarios of light attenuation and potential seagrass success in a eutrophic estuary

USGS Publications Warehouse

del Barrio, Pilar; Ganju, Neil K.; Aretxabaleta, Alfredo L.; Hayn, Melanie; García, Andrés; Howarth, Robert W.

2014-01-01

Estuarine eutrophication has led to numerous ecological changes, including loss of seagrass beds. One potential cause of these losses is a reduction in light availability due to increased attenuation by phytoplankton. Future sea level rise will also tend to reduce light penetration and modify seagrass habitat. In the present study, we integrate a spectral irradiance model into a biogeochemical model coupled to the Regional Ocean Model System (ROMS). It is linked to a bio-optical seagrass model to assess potential seagrass habitat in a eutrophic estuary under future nitrate loading and sea-level rise scenarios. The model was applied to West Falmouth Harbor, a shallow estuary located on Cape Cod (Massachusetts) where nitrate from groundwater has led to eutrophication and seagrass loss in landward portions of the estuary. Measurements of chlorophyll, turbidity, light attenuation, and seagrass coverage were used to assess the model accuracy. Mean chlorophyll based on uncalibrated in-situ fluorometry varied from 28 μg L−1 at the landward-most site to 6.5 μg L−1 at the seaward site, while light attenuation ranged from 0.86 to 0.45 m-1. The model reproduced the spatial variability in chlorophyll and light attenuation with RMS errors of 3.72 μg L−1 and 0.07 m-1 respectively. Scenarios of future nitrate reduction and sea-level rise suggest an improvement in light climate in the landward basin with a 75% reduction in nitrate loading. This coupled model may be useful to assess habitat availability changes due to eutrophication and sediment resuspension and fully considers spatial variability on the tidal timescale.
Designing ecological climate change impact assessments to reflect key climatic drivers

USGS Publications Warehouse

Sofaer, Helen R.; Barsugli, Joseph J.; Jarnevich, Catherine S.; Abatzoglou, John T.; Talbert, Marian; Miller, Brian W.; Morisette, Jeffrey T.

2017-01-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.
Designing ecological climate change impact assessments to reflect key climatic drivers.

PubMed

Sofaer, Helen R; Barsugli, Joseph J; Jarnevich, Catherine S; Abatzoglou, John T; Talbert, Marian K; Miller, Brian W; Morisette, Jeffrey T

2017-07-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive - such as means or extremes - can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the 'model space' approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling. © 2017 John Wiley & Sons Ltd.
Analyzing long-term spatial variability of blue and green water footprints in a semi-arid mountainous basin with MIROC-ESM model (case study: Kashafrood River Basin, Iran)

NASA Astrophysics Data System (ADS)

Aghakhani Afshar, A.; Hassanzadeh, Y.; Pourreza-Bilondi, M.; Ahmadi, A.

2017-11-01

The river basin hydrology cycles and the available water resources (including blue and green water) are greatly influenced by the climate change and rainfall patterns in regions with arid and semi-arid climates. In this study, the impacts of climate change on the parameters of virtual water is evaluated in the Kashafrood River (KR), as a large-scale basin which is located in the northeast of Iran, by means of SWAT model (Soil and Water Assessment Tool) along with SUFI-2 (Sequential Uncertainty Fitting Program version 2). In addition, sensitivity and uncertainty analyses are taken into account at five runoff stations for calibrating and validating the model. Based on the changes in blue water (BW), green water flow (GWF), and green water storage (GWS), the water availability was analyzed using MIROC-ESM model in series of the Coupled Model Intercomparison Project Phase 5 (CMIP5) and was compared with two Representative Concentration Pathways (RCPs) of new emission scenarios (RCP2.6 and RCP8.5). These emission scenarios were downscaled based on the observed data under three future periods: near future (2014-2042), intermediate future (2043-2071), and far future (2072-2100) in relation to a historical period (1992-2013). Calibration and validation at multi-site (five stations) showed a proper performance of the SWAT model in modeling hydrological processes. Results of investigating climate change impacts on the blue and green water components (BW and GW) showed that in the historical period, the basin was not in an appropriate climate condition for accessing the water resources. Also, in future times, considerable spatial variations in different hydrological components were observed. On the other hand, under both RCPs and in all three future periods in relative to historical period, the BW contents will increase about 46-74%, while GWF will decrease about 2-15%. Regarding the historical period, it was revealed that the condition of the basin will be improved. In addition, the GWS tended to rise about 11-18% or decrease about 6-60% in the future. The BW and GWS will decrease, and GWS will increase by changing from the near future to the intermediate future. On the other hand, by changing from the intermediate to the far future, BW and GWF will increase under RCP2.6 and will decrease under RCP8.5, respectively. Also, GWS will decrease under both RCPs.
Power accounting of plasma discharges in the linear device Proto-MPEX

NASA Astrophysics Data System (ADS)

Showers, M.; Piotrowicz, P. A.; Beers, C. J.; Biewer, T. M.; Caneses, J.; Canik, J.; Caughman, J. B. O.; Donovan, D. C.; Goulding, R. H.; Lumsdaine, A.; Kafle, N.; Owen, L. W.; Rapp, J.; Ray, H.

2018-06-01

Plasma material interaction (PMI) studies are crucial to the successful development of future fusion reactors. Prototype Material Plasma Exposure eXperiment (Proto-MPEX) is a prototype design for the MPEX, a steady-state linear device being developed to study PMI. The primary purpose of Proto-MPEX is developing the plasma heating source concepts for MPEX. A power accounting study of Proto-MPEX works to identify machine operating parameters that could improve its performance, thereby increasing its PMI research capabilities, potentially impacting the MPEX design concept. To build a comprehensive power balance, an analysis of the helicon region has been performed implementing a diagnostic suite and software modeling to identify mechanisms and locations of heat loss from the main plasma. Of the 106.3 kW of input power, up to 90.5% of the power has been accounted for in the helicon region. When the analysis was extended to encompass the device to its end plates, 49.2% of the input power was accounted for and verified diagnostically. Areas requiring further diagnostic analysis are identified. The required improvements will be implemented in future work. The data acquisition and analysis processes will be streamlined to form a working model for future power balance studies of Proto-MPEX. ).
The role of the physics department in the preparation of future pre-college teachers: A summary from the international conference on physics education

NASA Astrophysics Data System (ADS)

Lopez, Ramon E.

1997-03-01

This paper summarizes the conference presentations that specifically dealt with the role of the physics department in education of teachers, both before they begin teaching (pre-service) and during their careers (in-service). These presentations in general reflected a consensus that, as in the case of other students, instruction in pre-service and in-service courses should employ more active engagement techniques, both to improve student understanding and to model effective instruction, and that the appropriate use of technology can be a powerful aid to that end. Improvements made in standard introductory physics courses will impact most future secondary science teachers who, by and large, will have science degrees or take a significant amount of science courses. However, pre-service elementary teachers take few science courses and are often science phobic. This population represents the vast bulk of teachers who, if they have a good understanding of basic science, can engage children at the ages when they are most curious. Physics departments can play a valuable role in stimulating and sustaining reform of pre-college science teaching by being more involved in providing effective and appropriate instruction and models for inquiry to current and future elementary and secondary teachers.
Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

NASA Astrophysics Data System (ADS)

Bennett, Katrina E.; Urrego Blanco, Jorge R.; Jonko, Alexandra; Bohn, Theodore J.; Atchley, Adam L.; Urban, Nathan M.; Middleton, Richard S.

2018-01-01

The Colorado River Basin is a fundamentally important river for society, ecology, and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent, and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. We combine global sensitivity analysis with a space-filling Latin Hypercube Sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach. We find that snow-dominated regions are much more sensitive to uncertainties in VIC parameters. Although baseflow and runoff changes respond to parameters used in previous sensitivity studies, we discover new key parameter sensitivities. For instance, changes in runoff and evapotranspiration are sensitive to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI) in the VIC model. It is critical for improved modeling to narrow uncertainty in these parameters through improved observations and field studies. This is important because LAI and albedo are anticipated to change under future climate and narrowing uncertainty is paramount to advance our application of models such as VIC for water resource management.
Calibration to improve forward model simulation of microwave emissivity at GPM frequencies over the U.S. Southern Great Plains

PubMed Central

Harrison, Kenneth W.; Tian, Yudong; Peters-Lidard, Christa D.; Ringerud, Sarah; Kumar, Sujay V.

2018-01-01

Better estimation of land surface microwave emissivity promises to improve over-land precipitation retrievals in the GPM era. Forward models of land microwave emissivity are available but have suffered from poor parameter specification and limited testing. Here, forward models are calibrated and the accompanying change in predictive power is evaluated. With inputs (e.g., soil moisture) from the Noah land surface model and applying MODIS LAI data, two microwave emissivity models are tested, the Community Radiative Transfer Model (CRTM) and Community Microwave Emission Model (CMEM). The calibration is conducted with the NASA Land Information System (LIS) parameter estimation subsystem using AMSR-E based emissivity retrievals for the calibration dataset. The extent of agreement between the modeled and retrieved estimates is evaluated using the AMSR-E retrievals for a separate 7-year validation period. Results indicate that calibration can significantly improve the agreement, simulating emissivity with an across-channel average root-mean-square-difference (RMSD) of about 0.013, or about 20% lower than if relying on daily estimates based on climatology. The results also indicate that calibration of the microwave emissivity model alone, as was done in prior studies, results in as much as 12% higher across-channel average RMSD, as compared to joint calibration of the land surface and microwave emissivity models. It remains as future work to assess the extent to which the improvements in emissivity estimation translate into improvements in precipitation retrieval accuracy. PMID:29795962

Improving Translation from Preclinical Studies to Clinical Trials in Acute Kidney Injury.

PubMed

Fiorentino, Marco; Kellum, John A

2018-05-23

Several cellular and molecular targets and mechanisms have been investigated in preclinical studies of acute kidney injury (AKI), but translation in successful clinical studies has failed to date. This article reviews many issues that have limited this and the potential future perspectives in AKI prevention and treatment. Preclinical models of AKI should closely mimic the complexity of human AKI, considering the importance of several comorbidities in determining the clinical course and outcomes in the human disease. Moreover, studies should test novel interventions in models where AKI is already established, instead of focusing only at primary prevention. AKI definitions and endpoints in animal studies should be similar to those applied in clinical studies; in particular, AKI biomarkers should be implemented to guide patient selection for clinical trials and monitor intervention efficacy. In this scenario, cell-cycle arrest biomarkers have been widely investigated as AKI predictors in both preclinical and clinical studies and they serve as useful tools for future interventional studies. A better understanding of human AKI through a large collection of biological samples and kidney biopsies and omics applications, and an iterative relationship between preclinical and clinical studies are critical steps to improve future preclinical models and clinical trials. Finally, given the great variability in clinical manifestation of AKI, a strong collaboration between research centers and industry is recommended. Key messages: Several methodological issues have hampered the translation of basic research findings in clinical studies, and overcoming these obstacles is necessary to achieve success. © 2018 S. Karger AG, Basel.
The Chrysler-Weldtech Approach to Retraining Displaced Workers. A Model Project to Develop Specialized Welding Skills Required for Modern Auto Assembly Operations. Final Technical Report.

ERIC Educational Resources Information Center

Lyons, Thomas M.; Knight, Glen A.

A model project was conducted to demonstrate how Chrysler, in partnership with the education community and the government, could provide technical training to enable displaced workers to contribute to the "H-Body" car launch, to improve their job skills, and to enhance their future employability. The training was conducted on a pilot…
Analysis of Utility and Use of a Web-Based Tool for Digital Signal Processing Teaching by Means of a Technological Acceptance Model

ERIC Educational Resources Information Center

Toral, S. L.; Barrero, F.; Martinez-Torres, M. R.

2007-01-01

This paper presents an exploratory study about the development of a structural and measurement model for the technological acceptance (TAM) of a web-based educational tool. The aim consists of measuring not only the use of this tool, but also the external variables with a significant influence in its use for planning future improvements. The tool,…
The 2008 U.S. Geological Survey national seismic hazard models and maps for the central and eastern United States

USGS Publications Warehouse

Petersen, Mark D.; Frankel, Arthur D.; Harmsen, Stephen C.; Mueller, Charles S.; Boyd, Oliver S.; Luco, Nicolas; Wheeler, Russell L.; Rukstales, Kenneth S.; Haller, Kathleen M.

2012-01-01

In this paper, we describe the scientific basis for the source and ground-motion models applied in the 2008 National Seismic Hazard Maps, the development of new products that are used for building design and risk analyses, relationships between the hazard maps and design maps used in building codes, and potential future improvements to the hazard maps.
Testing the responses of four wheat crop models to heat stress at anthesis and grain filling.

PubMed

Liu, Bing; Asseng, Senthold; Liu, Leilei; Tang, Liang; Cao, Weixing; Zhu, Yan

2016-05-01

Higher temperatures caused by future climate change will bring more frequent heat stress events and pose an increasing risk to global wheat production. Crop models have been widely used to simulate future crop productivity but are rarely tested with observed heat stress experimental datasets. Four wheat models (DSSAT-CERES-Wheat, DSSAT-Nwheat, APSIM-Wheat, and WheatGrow) were evaluated with 4 years of environment-controlled phytotron experimental datasets with two wheat cultivars under heat stress at anthesis and grain filling stages. Heat stress at anthesis reduced observed grain numbers per unit area and individual grain size, while heat stress during grain filling mainly decreased the size of the individual grains. The observed impact of heat stress on grain filling duration, total aboveground biomass, grain yield, and grain protein concentration (GPC) varied depending on cultivar and accumulated heat stress. For every unit increase of heat degree days (HDD, degree days over 30 °C), grain filling duration was reduced by 0.30-0.60%, total aboveground biomass was reduced by 0.37-0.43%, and grain yield was reduced by 1.0-1.6%, but GPC was increased by 0.50% for cv Yangmai16 and 0.80% for cv Xumai30. The tested crop simulation models could reproduce some of the observed reductions in grain filling duration, final total aboveground biomass, and grain yield, as well as the observed increase in GPC due to heat stress. Most of the crop models tended to reproduce heat stress impacts better during grain filling than at anthesis. Some of the tested models require improvements in the response to heat stress during grain filling, but all models need improvements in simulating heat stress effects on grain set during anthesis. The observed significant genetic variability in the response of wheat to heat stress needs to be considered through cultivar parameters in future simulation studies. © 2016 John Wiley & Sons Ltd.
Learning clinically useful information from images: Past, present and future.

PubMed

Rueckert, Daniel; Glocker, Ben; Kainz, Bernhard

2016-10-01

Over the last decade, research in medical imaging has made significant progress in addressing challenging tasks such as image registration and image segmentation. In particular, the use of model-based approaches has been key in numerous, successful advances in methodology. The advantage of model-based approaches is that they allow the incorporation of prior knowledge acting as a regularisation that favours plausible solutions over implausible ones. More recently, medical imaging has moved away from hand-crafted, and often explicitly designed models towards data-driven, implicit models that are constructed using machine learning techniques. This has led to major improvements in all stages of the medical imaging pipeline, from acquisition and reconstruction to analysis and interpretation. As more and more imaging data is becoming available, e.g., from large population studies, this trend is likely to continue and accelerate. At the same time new developments in machine learning, e.g., deep learning, as well as significant improvements in computing power, e.g., parallelisation on graphics hardware, offer new potential for data-driven, semantic and intelligent medical imaging. This article outlines the work of the BioMedIA group in this area and highlights some of the challenges and opportunities for future work. Copyright © 2016 Elsevier B.V. All rights reserved.
Summary of papers on current and anticipated uses of thermal-hydraulic codes

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

Caruso, R.

1997-07-01

The author reviews a range of recent papers which discuss possible uses and future development needs for thermal/hydraulic codes in the nuclear industry. From this review, eight common recommendations are extracted. They are: improve the user interface so that more people can use the code, so that models are easier and less expensive to prepare and maintain, and so that the results are scrutable; design the code so that it can easily be coupled to other codes, such as core physics, containment, fission product behaviour during severe accidents; improve the numerical methods to make the code more robust and especiallymore » faster running, particularly for low pressure transients; ensure that future code development includes assessment of code uncertainties as integral part of code verification and validation; provide extensive user guidelines or structure the code so that the `user effect` is minimized; include the capability to model multiple fluids (gas and liquid phase); design the code in a modular fashion so that new models can be added easily; provide the ability to include detailed or simplified component models; build on work previously done with other codes (RETRAN, RELAP, TRAC, CATHARE) and other code validation efforts (CSAU, CSNI SET and IET matrices).« less
The ODD protocol: A review and first update

USGS Publications Warehouse

Grimm, Volker; Berger, Uta; DeAngelis, Donald L.; Polhill, J. Gary; Giske, Jarl; Railsback, Steve F.

2010-01-01

The 'ODD' (Overview, Design concepts, and Details) protocol was published in 2006 to standardize the published descriptions of individual-based and agent-based models (ABMs). The primary objectives of ODD are to make model descriptions more understandable and complete, thereby making ABMs less subject to criticism for being irreproducible. We have systematically evaluated existing uses of the ODD protocol and identified, as expected, parts of ODD needing improvement and clarification. Accordingly, we revise the definition of ODD to clarify aspects of the original version and thereby facilitate future standardization of ABM descriptions. We discuss frequently raised critiques in ODD but also two emerging, and unanticipated, benefits: ODD improves the rigorous formulation of models and helps make the theoretical foundations of large models more visible. Although the protocol was designed for ABMs, it can help with documenting any large, complex model, alleviating some general objections against such models.
Improving Global Health Education: Development of a Global Health Competency Model

PubMed Central

Ablah, Elizabeth; Biberman, Dorothy A.; Weist, Elizabeth M.; Buekens, Pierre; Bentley, Margaret E.; Burke, Donald; Finnegan, John R.; Flahault, Antoine; Frenk, Julio; Gotsch, Audrey R.; Klag, Michael J.; Lopez, Mario Henry Rodriguez; Nasca, Philip; Shortell, Stephen; Spencer, Harrison C.

2014-01-01

Although global health is a recommended content area for the future of education in public health, no standardized global health competency model existed for master-level public health students. Without such a competency model, academic institutions are challenged to ensure that students are able to demonstrate the knowledge, skills, and attitudes (KSAs) needed for successful performance in today's global health workforce. The Association of Schools of Public Health (ASPH) sought to address this need by facilitating the development of a global health competency model through a multistage modified-Delphi process. Practitioners and academic global health experts provided leadership and guidance throughout the competency development process. The resulting product, the Global Health Competency Model 1.1, includes seven domains and 36 competencies. The Global Health Competency Model 1.1 provides a platform for engaging educators, students, and global health employers in discussion of the KSAs needed to improve human health on a global scale. PMID:24445206
Mammographic density, breast cancer risk and risk prediction

PubMed Central

Vachon, Celine M; van Gils, Carla H; Sellers, Thomas A; Ghosh, Karthik; Pruthi, Sandhya; Brandt, Kathleen R; Pankratz, V Shane

2007-01-01

In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individual's probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models. PMID:18190724
Improving evaluation of climate change impacts on the water cycle by remote sensing ET-retrieval

NASA Astrophysics Data System (ADS)

García Galiano, S. G.; Olmos Giménez, P.; Ángel Martínez Pérez, J.; Diego Giraldo Osorio, J.

2015-05-01

Population growth and intense consumptive water uses are generating pressures on water resources in the southeast of Spain. Improving the knowledge of the climate change impacts on water cycle processes at the basin scale is a step to building adaptive capacity. In this work, regional climate model (RCM) ensembles are considered as an input to the hydrological model, for improving the reliability of hydroclimatic projections. To build the RCMs ensembles, the work focuses on probability density function (PDF)-based evaluation of the ability of RCMs to simulate of rainfall and temperature at the basin scale. To improve the spatial calibration of the continuous hydrological model used, an algorithm for remote sensing actual evapotranspiration (AET) retrieval was applied. From the results, a clear decrease in runoff is expected for 2050 in the headwater basin studied. The plausible future scenario of water shortage will produce negative impacts on the regional economy, where the main activity is irrigated agriculture.
Improving Care for Depression & Suicide Risk in Adolescents: Innovative Strategies for Bringing Treatments to Community Settings

PubMed Central

Asarnow, Joan Rosenbaum; Miranda, Jeanne

2015-01-01

This article reviews the literature on interventions and services for depression and suicide prevention among adolescents, with the goals of placing this science within the context of current changing health care environments and highlighting innovative models for improving health and mental health. We examine the: challenges and opportunities offered by new initiatives and legislation designed to transform the U.S. health and mental healthcare systems; summarize knowledge regarding the treatment of depression and suicidality/self-harm in adolescents; and describe innovative models for partnering with health systems and communities. This review demonstrates that treatment models and service delivery strategies are currently available for increasing evidence-based care, particularly for depression, and concludes with recommendations for future research and quality improvement initiatives aimed at inspiring additional efforts to put science to work, bridge science and community practice, and develop strategies for partnering with communities to improve care, mental health, and well-being among adolescents. PMID:24437432
Fire and Smoke Model Evaluation Experiment: Coordination of a study to improve smoke modeling for fire operations within the United States

NASA Astrophysics Data System (ADS)

French, N. H. F.; Ottmar, R. D.; Brown, T. J.; Larkin, N. K.

2017-12-01

The Fire and Smoke Model Evaluation Experiment (FASMEE) is an integrative research effort to identify and collect critical measurements to improve operational wildland fire and smoke prediction systems. FASMEE has two active phases and one suggested phase. Phase 1 is the analysis and planning process to assess the current state of fire-plume-smoke modeling and to determine the critical measurements required to evaluate and improve these operational fire and smoke models. As the major deliverable for Phase 1, a study plan has been completed that describes the measurement needs, field campaigns, and command, safety and air space de-confliction plans necessary to complete the FASMEE project. Phase 2 is a set of field campaigns to collect data during 2019-2022. Future Improvements would be a set of analyses and model improvements based on the data collected within Phase 2 that is dependent on identifying future funding sources. In this presentation, we will review the FASMEE Study Plan and detailed measurements and conditions expected for the four to five proposed research burns. The recommended measurements during Phase 2 span the four interrelated disciplines of FASMEE: fuels and consumption, fire behavior and energy, plume dynamics and meteorology, and smoke emissions, chemistry, and transport. Fuel type, condition, and consumption during wildland fire relates to several fire impacts including radiative heating, which provides the energy that drives fire dynamics. Local-scale meteorology is an important factor which relates to atmospheric chemistry, dispersion, and transport. Plume dynamics provide the connection between fire behavior and far-field smoke dispersion, because it determines the vertical distribution of the emissions. Guided by the data needs and science questions generated during Phase 1, three wildland fire campaigns were selected. These included the western wildfire campaign (rapid deployment aimed at western wildfires supporting NOAA, NASA, and NSF smoke flights), southwestern campaign (targeting high intensity prescribed fires), and southeastern campaign (targeting large and higher than average fuel loadings with important smoke management relevancy).
Modelling exploration of non-stationary hydrological system

NASA Astrophysics Data System (ADS)

Kim, Kue Bum; Kwon, Hyun-Han; Han, Dawei

2015-04-01

Traditional hydrological modelling assumes that the catchment does not change with time (i.e., stationary conditions) which means the model calibrated for the historical period is valid for the future period. However, in reality, due to change of climate and catchment conditions this stationarity assumption may not be valid in the future. It is a challenge to make the hydrological model adaptive to the future climate and catchment conditions that are not observable at the present time. In this study a lumped conceptual rainfall-runoff model called IHACRES was applied to a catchment in southwest England. Long observation data from 1961 to 2008 were used and seasonal calibration (in this study only summer period is further explored because it is more sensitive to climate and land cover change than the other three seasons) has been done since there are significant seasonal rainfall patterns. We expect that the model performance can be improved by calibrating the model based on individual seasons. The data is split into calibration and validation periods with the intention of using the validation period to represent the future unobserved situations. The success of the non-stationary model will depend not only on good performance during the calibration period but also the validation period. Initially, the calibration is based on changing the model parameters with time. Methodology is proposed to adapt the parameters using the step forward and backward selection schemes. However, in the validation both the forward and backward multiple parameter changing models failed. One problem is that the regression with time is not reliable since the trend may not be in a monotonic linear relationship with time. The second issue is that changing multiple parameters makes the selection process very complex which is time consuming and not effective in the validation period. As a result, two new concepts are explored. First, only one parameter is selected for adjustment while the other parameters are set as constant. Secondly, regression is made against climate condition instead of against time. It has been found that such a new approach is very effective and this non-stationary model worked very well both in the calibration and validation period. Although the catchment is specific in southwest England and the data are for only the summer period, the methodology proposed in this study is general and applicable to other catchments. We hope this study will stimulate the hydrological community to explore a variety of sites so that valuable experiences and knowledge could be gained to improve our understanding of such a complex modelling issue in climate change impact assessment.
Estimating indices of range shifts in birds using dynamic models when detection is imperfect

USGS Publications Warehouse

Clement, Matthew J.; Hines, James E.; Nichols, James D.; Pardieck, Keith L.; Ziolkowski, David J.

2016-01-01

There is intense interest in basic and applied ecology about the effect of global change on current and future species distributions. Projections based on widely used static modeling methods implicitly assume that species are in equilibrium with the environment and that detection during surveys is perfect. We used multiseason correlated detection occupancy models, which avoid these assumptions, to relate climate data to distributional shifts of Louisiana Waterthrush in the North American Breeding Bird Survey (BBS) data. We summarized these shifts with indices of range size and position and compared them to the same indices obtained using more basic modeling approaches. Detection rates during point counts in BBS surveys were low, and models that ignored imperfect detection severely underestimated the proportion of area occupied and slightly overestimated mean latitude. Static models indicated Louisiana Waterthrush distribution was most closely associated with moderate temperatures, while dynamic occupancy models indicated that initial occupancy was associated with diurnal temperature ranges and colonization of sites was associated with moderate precipitation. Overall, the proportion of area occupied and mean latitude changed little during the 1997–2013 study period. Near-term forecasts of species distribution generated by dynamic models were more similar to subsequently observed distributions than forecasts from static models. Occupancy models incorporating a finite mixture model on detection – a new extension to correlated detection occupancy models – were better supported and may reduce bias associated with detection heterogeneity. We argue that replacing phenomenological static models with more mechanistic dynamic models can improve projections of future species distributions. In turn, better projections can improve biodiversity forecasts, management decisions, and understanding of global change biology.
Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model.

PubMed

Fernandes, Jose A; Cheung, William W L; Jennings, Simon; Butenschön, Momme; de Mora, Lee; Frölicher, Thomas L; Barange, Manuel; Grant, Alastair

2013-08-01

Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment. © 2013 John Wiley & Sons Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Cort, Katherine A.; Hostick, Donna J.; Belzer, David B.

The purpose of this report is to compile information and conclusions gathered as part of three separate tasks undertaken as part of the overall project, “Modeling EERE Deployment Programs,” sponsored by the Planning, Analysis, and Evaluation office within the Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE). The purpose of the project was to identify and characterize the modeling of deployment programs within the EERE Technology Development (TD) programs, address improvements to modeling in the near term, and note gaps in knowledge where future research is needed.
Public Health Analysis Transport Optimization Model v. 1.0

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

Beyeler, Walt; Finley, Patrick; Walser, Alex

PHANTOM models logistic functions of national public health systems. The system enables public health officials to visualize and coordinate options for public health surveillance, diagnosis, response and administration in an integrated analytical environment. Users may simulate and analyze system performance applying scenarios that represent current conditions or future contingencies what-if analyses of potential systemic improvements. Public health networks are visualized as interactive maps, with graphical displays of relevant system performance metrics as calculated by the simulation modeling components.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Peeler, D.; Edwards, T.

High-level waste (HLW) throughput (i.e., the amount of waste processed per unit of time) is primarily a function of two critical parameters: waste loading (WL) and melt rate. For the Defense Waste Processing Facility (DWPF), increasing HLW throughput would significantly reduce the overall mission life cycle costs for the Department of Energy (DOE). Significant increases in waste throughput have been achieved at DWPF since initial radioactive operations began in 1996. Key technical and operational initiatives that supported increased waste throughput included improvements in facility attainment, the Chemical Processing Cell (CPC) flowsheet, process control models and frit formulations. As a resultmore » of these key initiatives, DWPF increased WLs from a nominal 28% for Sludge Batch 2 (SB2) to {approx}34 to 38% for SB3 through SB6 while maintaining or slightly improving canister fill times. Although considerable improvements in waste throughput have been obtained, future contractual waste loading targets are nominally 40%, while canister production rates are also expected to increase (to a rate of 325 to 400 canisters per year). Although implementation of bubblers have made a positive impact on increasing melt rate for recent sludge batches targeting WLs in the mid30s, higher WLs will ultimately make the feeds to DWPF more challenging to process. Savannah River Remediation (SRR) recently requested the Savannah River National Laboratory (SRNL) to perform a paper study assessment using future sludge projections to evaluate whether the current Process Composition Control System (PCCS) algorithms would provide projected operating windows to allow future contractual WL targets to be met. More specifically, the objective of this study was to evaluate future sludge batch projections (based on Revision 16 of the HLW Systems Plan) with respect to projected operating windows using current PCCS models and associated constraints. Based on the assessments, the waste loading interval over which a glass system (i.e., a projected sludge composition with a candidate frit) is predicted to be acceptable can be defined (i.e., the projected operating window) which will provide insight into the ability to meet future contractual WL obligations. In this study, future contractual WL obligations are assumed to be 40%, which is the goal after all flowsheet enhancements have been implemented to support DWPF operations. For a system to be considered acceptable, candidate frits must be identified that provide access to at least 40% WL while accounting for potential variation in the sludge resulting from differences in batch-to-batch transfers into the Sludge Receipt and Adjustment Tank (SRAT) and/or analytical uncertainties. In more general terms, this study will assess whether or not the current glass formulation strategy (based on the use of the Nominal and Variation Stage assessments) and current PCCS models will allow access to compositional regions required to targeted higher WLs for future operations. Some of the key questions to be considered in this study include: (1) If higher WLs are attainable with current process control models, are the models valid in these compositional regions? If the higher WL glass regions are outside current model development or validation ranges, is there existing data that could be used to demonstrate model applicability (or lack thereof)? If not, experimental data may be required to revise current models or serve as validation data with the existing models. (2) Are there compositional trends in frit space that are required by the PCCS models to obtain access to these higher WLs? If so, are there potential issues with the compositions of the associated frits (e.g., limitations on the B{sub 2}O{sub 3} and/or Li{sub 2}O concentrations) as they are compared to model development/validation ranges or to the term 'borosilicate' glass? If limitations on the frit compositional range are realized, what is the impact of these restrictions on other glass properties such as the ability to suppress nepheline formation or influence melt rate? The model based assessments being performed make the assumption that the process control models are applicable over the glass compositional regions being evaluated. Although the glass compositional region of interest is ultimately defined by the specific frit, sludge, and WL interval used, there is no prescreening of these compositional regions with respect to the model development or validation ranges which is consistent with current DWPF operations.« less
Sometimes it hurts when supervisors don't listen: the antecedents and consequences of safety voice among young workers.

PubMed

Tucker, Sean; Turner, Nick

2015-01-01

We examined the relationship among having ideas about how to improve occupational safety, speaking up about them (safety voice), and future work-related injuries. One hundred fifty-five employed teenagers completed 3 surveys with a 1-month lag between each survey. We found that participants who were more likely to have ideas about how to improve occupational safety and had high affective commitment to the organization reported the highest level of safety voice. In turn, supervisor openness to voice moderated the relationship between safety voice and future work-related injuries. Specifically, future work-related injuries were most frequent when high levels of safety voice were combined with low supervisor openness to voice. The tested model clarifies the conditions under which workers share safety-related ideas with a supervisor and the real consequences of speaking up about them. We discuss the implications of these findings for safety management. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Assessing the impacts of climate change in Mediterranean catchments under conditions of data scarcity

NASA Astrophysics Data System (ADS)

Meyer, Swen; Ludwig, Ralf

2013-04-01

According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. While there is scientific consensus that climate induced changes on the hydrology of Mediterranean regions are presently occurring and are projected to amplify in the future, very little knowledge is available about the quantification of these changes, which is hampered by a lack of suitable and cost effective hydrological monitoring and modeling systems. The European FP7-project CLIMB is aiming to analyze climate induced changes on the hydrology of the Mediterranean Basins by investigating 7 test sites located in the countries Italy, France, Turkey, Tunisia, Gaza and Egypt. CLIMB employs a combination of novel geophysical field monitoring concepts, remote sensing techniques and integrated hydrologic modeling to improve process descriptions and understanding and to quantify existing uncertainties in climate change impact analysis. The Rio Mannu Basin, located in Sardinia; Italy, is one test site of the CLIMB project. The catchment has a size of 472.5 km2, it ranges from 62 to 946 meters in elevation, at mean annual temperatures of 16°C and precipitation of about 700 mm, the annual runoff volume is about 200 mm. The physically based Water Simulation Model WaSiM Vers. 2 (Schulla & Jasper (1999)) was setup to model current and projected future hydrological conditions. The availability of measured meteorological and hydrological data is poor as common to many Mediterranean catchments. The lack of available measured input data hampers the calibration of the model setup and the validation of model outputs. State of the art remote sensing techniques and field measuring techniques were applied to improve the quality of hydrological input parameters. In a field campaign about 250 soil samples were collected and lab-analyzed. Different geostatistical regionalization methods were tested to improve the model setup. The soil parameterization of the model was tested against publically available soil data. Results show a significant improvement of modeled soil moisture outputs. To validate WaSiMs evapotranspiration (ETact) outputs, Landsat TM images were used to calculate the actual monthly mean ETact rates using the triangle method (Jiang and Islam, 1999). Simulated spatial ETact patterns and those derived from remote sensing show a good fit especially for the growing season. WaSiM was driven with the meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. Output results were analyzed for climate induced changes on selected hydrological variables. While the climate projections reveal increased precipitation rates in the spring season, first simulation results show an earlier onset and an increased duration of the dry season, imposing an increased irrigation demand and higher vulnerability of agricultural productivity.
Assessing Animal Welfare Impacts in the Management of European Rabbits (Oryctolagus cuniculus), European Moles (Talpa europaea) and Carrion Crows (Corvus corone)

PubMed Central

Baker, Sandra E.; Sharp, Trudy M.; Macdonald, David W.

2016-01-01

Human-wildlife conflict is a global issue. Attempts to manage this conflict impact upon wild animal welfare, an issue receiving little attention until relatively recently. Where human activities harm animal welfare these effects should be minimised where possible. However, little is known about the welfare impacts of different wildlife management interventions, and opinions on impacts vary widely. Welfare impacts therefore need to be assessed objectively. Our objectives were to: 1) establish whether an existing welfare assessment model could differentiate and rank the impacts of different wildlife management interventions (for decision-making purposes); 2) identify and evaluate any additional benefits of making formal welfare assessments; and 3) illustrate issues raised by application of the model. We applied the welfare assessment model to interventions commonly used with rabbits (Oryctolagus cuniculus), moles (Talpa europaea) and crows (Corvus corone) in the UK. The model ranked interventions for rabbits (least impact first: fencing, head shot, chest shot) and crows (shooting, scaring, live trapping with cervical dislocation). For moles, managing molehills and tunnels scored least impact. Both spring trapping, and live trapping followed by translocation, scored greater impacts, but these could not be compared directly as they scored on different axes of the model. Some rankings appeared counter-intuitive, highlighting the need for objective formal welfare assessments. As well as ranking the humaneness of interventions, the model highlighted future research needs and how Standard Operating Procedures might be improved. The model is a milestone in assessing wildlife management welfare impacts, but our research revealed some limitations of the model and we discuss likely challenges in resolving these. In future, the model might be developed to improve its utility, e.g. by refining the time-scales. It might also be used to reach consensus among stakeholders about relative welfare impacts or to identify ways of improving wildlife management practice in the field. PMID:26726808
Assessing Animal Welfare Impacts in the Management of European Rabbits (Oryctolagus cuniculus), European Moles (Talpa europaea) and Carrion Crows (Corvus corone).

PubMed

Baker, Sandra E; Sharp, Trudy M; Macdonald, David W

2016-01-01

Human-wildlife conflict is a global issue. Attempts to manage this conflict impact upon wild animal welfare, an issue receiving little attention until relatively recently. Where human activities harm animal welfare these effects should be minimised where possible. However, little is known about the welfare impacts of different wildlife management interventions, and opinions on impacts vary widely. Welfare impacts therefore need to be assessed objectively. Our objectives were to: 1) establish whether an existing welfare assessment model could differentiate and rank the impacts of different wildlife management interventions (for decision-making purposes); 2) identify and evaluate any additional benefits of making formal welfare assessments; and 3) illustrate issues raised by application of the model. We applied the welfare assessment model to interventions commonly used with rabbits (Oryctolagus cuniculus), moles (Talpa europaea) and crows (Corvus corone) in the UK. The model ranked interventions for rabbits (least impact first: fencing, head shot, chest shot) and crows (shooting, scaring, live trapping with cervical dislocation). For moles, managing molehills and tunnels scored least impact. Both spring trapping, and live trapping followed by translocation, scored greater impacts, but these could not be compared directly as they scored on different axes of the model. Some rankings appeared counter-intuitive, highlighting the need for objective formal welfare assessments. As well as ranking the humaneness of interventions, the model highlighted future research needs and how Standard Operating Procedures might be improved. The model is a milestone in assessing wildlife management welfare impacts, but our research revealed some limitations of the model and we discuss likely challenges in resolving these. In future, the model might be developed to improve its utility, e.g. by refining the time-scales. It might also be used to reach consensus among stakeholders about relative welfare impacts or to identify ways of improving wildlife management practice in the field.
Soil Carbon Residence Time in the Arctic - Potential Drivers of Past and Future Change

NASA Astrophysics Data System (ADS)

Huntzinger, D. N.; Fisher, J.; Schwalm, C. R.; Hayes, D. J.; Stofferahn, E.; Hantson, W.; Schaefer, K. M.; Fang, Y.; Michalak, A. M.; Wei, Y.

2017-12-01

Carbon residence time is one of the most important factors controlling carbon cycling in ecosystems. Residence time depends on carbon allocation and conversion among various carbon pools and the rate of organic matter decomposition; all of which rely on environmental conditions, primarily temperature and soil moisture. As a result, residence time is an emergent property of models and a strong determinant of terrestrial carbon storage capacity. However, residence time is poorly constrained in process-based models due, in part, to the lack of data with which to benchmark global-scale models in order to guide model improvements and, ultimately, reduce uncertainty in model projections. Here we focus on improving the understanding of the drivers to observed and simulated carbon residence time in the Arctic-Boreal region (ABR). Carbon-cycling in the ABR represents one of the largest sources of uncertainty in historical and future projections of land-atmosphere carbon dynamics. This uncertainty is depicted in the large spread of terrestrial biospheric model (TBM) estimates of carbon flux and ecosystem carbon pool size in this region. Recent efforts, such as the Arctic-Boreal Vulnerability Experiment (ABoVE), have increased the availability of spatially explicit in-situ and remotely sensed carbon and ecosystem focused data products in the ABR. Together with simulations from Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we use these observations to evaluate the ability of models to capture soil carbon stocks and changes in the ABR. Specifically, we compare simulated versus observed soil carbon residence times in order to evaluate the functional response and sensitivity of modeled soil carbon stocks to changes in key environmental drivers. Understanding how simulated carbon residence time compares with observations and what drives these differences is critical for improving projections of changing carbon dynamics in the ABR and globally.
HEP Software Foundation Community White Paper Working Group - Detector Simulation

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

Apostolakis, J.

A working group on detector simulation was formed as part of the high-energy physics (HEP) Software Foundation's initiative to prepare a Community White Paper that describes the main software challenges and opportunities to be faced in the HEP field over the next decade. The working group met over a period of several months in order to review the current status of the Full and Fast simulation applications of HEP experiments and the improvements that will need to be made in order to meet the goals of future HEP experimental programmes. The scope of the topics covered includes the main componentsmore » of a HEP simulation application, such as MC truth handling, geometry modeling, particle propagation in materials and fields, physics modeling of the interactions of particles with matter, the treatment of pileup and other backgrounds, as well as signal processing and digitisation. The resulting work programme described in this document focuses on the need to improve both the software performance and the physics of detector simulation. The goals are to increase the accuracy of the physics models and expand their applicability to future physics programmes, while achieving large factors in computing performance gains consistent with projections on available computing resources.« less
Reinventing The Design Process: Teams and Models

NASA Technical Reports Server (NTRS)

Wall, Stephen D.

1999-01-01

The future of space mission designing will be dramatically different from the past. Formerly, performance-driven paradigms emphasized data return with cost and schedule being secondary issues. Now and in the future, costs are capped and schedules fixed-these two variables must be treated as independent in the design process. Accordingly, JPL has redesigned its design process. At the conceptual level, design times have been reduced by properly defining the required design depth, improving the linkages between tools, and managing team dynamics. In implementation-phase design, system requirements will be held in crosscutting models, linked to subsystem design tools through a central database that captures the design and supplies needed configuration management and control. Mission goals will then be captured in timelining software that drives the models, testing their capability to execute the goals. Metrics are used to measure and control both processes and to ensure that design parameters converge through the design process within schedule constraints. This methodology manages margins controlled by acceptable risk levels. Thus, teams can evolve risk tolerance (and cost) as they would any engineering parameter. This new approach allows more design freedom for a longer time, which tends to encourage revolutionary and unexpected improvements in design.
Paths to future growth in photovoltaics manufacturing

DOE PAGES

Basore, Paul A.

2016-03-01

The past decade has seen rapid growth in the photovoltaics industry, followed in the past few years by a period of much slower growth. A simple model that is consistent with this historical record can be used to predict the future evolution of the industry. Two key parameters are identified that determine the outcome. One is the annual global investment in manufacturing capacity normalized to the manufacturing capacity for the previous year (capacity-normalized capital investment rate, CapIR, units dollar/W). The other is how much capital investment is required for each watt of annual manufacturing capacity, normalized to the service lifemore » of the assets (capacity-normalized capital demand rate, CapDR, units dollar/W). If these two parameters remain unchanged from the values they have held for the past few years, global manufacturing capacity will peak in the next few years and then decline. However, it only takes a modest improvement in CapIR to ensure future growth in photovoltaics. Here, several approaches are presented that can enable the required improvement in CapIR. If, in addition, there is an accompanying improvement in CapDR, the rate of growth can be substantially accelerated.« less
The infant incubator in the neonatal intensive care unit: unresolved issues and future developments.

PubMed

Antonucci, Roberto; Porcella, Annalisa; Fanos, Vassilios

2009-01-01

Since the 19th century, devices termed incubators were developed to maintain thermal stability in low birth weight (LBW) and sick newborns, thus improving their chances of survival. Remarkable progress has been made in the production of infant incubators, which are currently highly technological devices. However, they still need to be improved in many aspects. Regarding the temperature and humidity control, future incubators should minimize heat loss from the neonate and eddies around him/her. An unresolved issue is exposure to high noise levels in the Neonatal Intensive Care Unit (NICU). Strategies aimed at modifying the behavior of NICU personnel, along with structural improvements in incubator design, are required to reduce noise exposure. Light environment should be taken into consideration in designing new models of incubators. In fact, ambient NICU illumination may cause visual pathway sequelae or possibly retinopathy of prematurity (ROP), while premature exposure to continuous lighting may adversely affect the rest-activity patterns of the newborn. Accordingly, both the use of incubator covers and circadian lighting in the NICU might attenuate these effects. The impact of electromagnetic fields (EMFs) on infant health is still unclear. However, future incubators should be designed to minimize the EMF exposure of the newborn.
Effect of the science teaching advancement through modeling physical science professional development workshop on teachers' attitudes, beliefs and content knowledge and students' content knowledge

NASA Astrophysics Data System (ADS)

Dietz, Laura

The Science Teaching Advancement through Modeling Physical Science (STAMPS) professional development workshop was evaluated for effectiveness in improving teachers' and students' content knowledge. Previous research has shown modeling to be an effective method of instruction for improving student and teacher content knowledge, evidenced by assessment scores. Data includes teacher scores on the Force Concept Inventory (FCI; Hestenes, Wells, & Swackhamer, 1992) and the Chemistry Concept Inventory (CCI; Jenkins, Birk, Bauer, Krause, & Pavelich, 2004), as well as student scores on a physics and chemistry assessment. Quantitative data is supported by teacher responses to a post workshop survey and classroom observations. Evaluation of the data shows that the STAMPS professional development workshop was successful in improving both student and teacher content knowledge. Conclusions and suggestions for future study are also included.
Using Neural Networks to Improve the Performance of Radiative Transfer Modeling Used for Geometry Dependent LER Calculations

NASA Astrophysics Data System (ADS)

Fasnacht, Z.; Qin, W.; Haffner, D. P.; Loyola, D. G.; Joiner, J.; Krotkov, N. A.; Vasilkov, A. P.; Spurr, R. J. D.

2017-12-01

In order to estimate surface reflectance used in trace gas retrieval algorithms, radiative transfer models (RTM) such as the Vector Linearized Discrete Ordinate Radiative Transfer Model (VLIDORT) can be used to simulate the top of the atmosphere (TOA) radiances with advanced models of surface properties. With large volumes of satellite data, these model simulations can become computationally expensive. Look up table interpolation can improve the computational cost of the calculations, but the non-linear nature of the radiances requires a dense node structure if interpolation errors are to be minimized. In order to reduce our computational effort and improve the performance of look-up tables, neural networks can be trained to predict these radiances. We investigate the impact of using look-up table interpolation versus a neural network trained using the smart sampling technique, and show that neural networks can speed up calculations and reduce errors while using significantly less memory and RTM calls. In future work we will implement a neural network in operational processing to meet growing demands for reflectance modeling in support of high spatial resolution satellite missions.
The Value of GRACE Data in Improving, Assessing and Evaluating Land Surface and Climate Models

NASA Astrophysics Data System (ADS)

Yang, Z.

2011-12-01

I will review how the Gravity Recovery and Climate Experiment (GRACE) satellite measurements have improved land surface models that are developed for weather, climate, and hydrological studies. GRACE-derived terrestrial water storage (TWS) changes have been successfully used to assess and evaluate the improved representations of land-surface hydrological processes such as groundwater-soil moisture interaction, frozen soil and infiltration, and the topographic control on runoff production, as evident in the simulations from the latest Noah-MP, the Community Land Model, and the Community Climate System Model. GRACE data sets have made it possible to estimate key terrestrial water storage components (snow mass, surface water, groundwater or water table depth), biomass, and surface water fluxes (evapotranspiration, solid precipitation, melt of snow/ice). Many of the examples will draw from my Land, Environment and Atmosphere Dynamics group's work on land surface model developments, snow mass retrieval, and multi-sensor snow data assimilation using the ensemble Karman filter and the ensemble Karman smoother. Finally, I will briefly outline some future directions in using GRACE in land surface modeling.
A physics department's role in preparing physics teachers: The Colorado learning assistant model

NASA Astrophysics Data System (ADS)

Otero, Valerie; Pollock, Steven; Finkelstein, Noah

2010-11-01

In response to substantial evidence that many U.S. students are inadequately prepared in science and mathematics, we have developed an effective and adaptable model that improves the education of all students in introductory physics and increases the numbers of talented physics majors becoming certified to teach physics. We report on the Colorado Learning Assistant model and discuss its effectiveness at a large research university. Since its inception in 2003, we have increased the pool of well-qualified K-12 physics teachers by a factor of approximately three, engaged scientists significantly in the recruiting and preparation of future teachers, and improved the introductory physics sequence so that students' learning gains are typically double the traditional average.
Capital planning for operating theatres based on projecting future theatre requirements.

PubMed

Sheehan, Jennifer A; Tyler, Peter; Jayasinha, Hirani; Meleady, Kathleen T; Jones, Neill

2011-05-01

During 2006, NSW and ACT Health Departments jointly engaged KPMG to develop an Operating Theatre Requirements' Projection Model and an accompanying planning guideline. A research scan was carried out to identify drivers of surgical demand, theatre capacity and theatre performance, as well as locating existing approaches to modelling operating theatre requirements for planning purposes. The project delivered a Microsoft Excel-based model for projecting future operating theatre requirements, together with an accompanying guideline for use of the model and interpretation of its outputs. It provides a valuable addition to the suite of tools available to Health staff for service and capital planning. The model operates with several limitations, largely due to being data dependent, and the state and completeness of available theatre activity data. However, the operational flexibility built into the model allows users to compensate for these limitations, on a case by case basis, when the user has access to suitable, local data. The design flexibility of the model means that updating the model as improved data become available is not difficult; resulting in revisions being able to be made quickly, and disseminated to users rapidly.
Rodent models in Down syndrome research: impact and future opportunities

PubMed Central

2017-01-01

ABSTRACT Down syndrome is caused by trisomy of chromosome 21. To date, a multiplicity of mouse models with Down-syndrome-related features has been developed to understand this complex human chromosomal disorder. These mouse models have been important for determining genotype-phenotype relationships and identification of dosage-sensitive genes involved in the pathophysiology of the condition, and in exploring the impact of the additional chromosome on the whole genome. Mouse models of Down syndrome have also been used to test therapeutic strategies. Here, we provide an overview of research in the last 15 years dedicated to the development and application of rodent models for Down syndrome. We also speculate on possible and probable future directions of research in this fast-moving field. As our understanding of the syndrome improves and genome engineering technologies evolve, it is necessary to coordinate efforts to make all Down syndrome models available to the community, to test therapeutics in models that replicate the whole trisomy and design new animal models to promote further discovery of potential therapeutic targets. PMID:28993310
Rodent models in Down syndrome research: impact and future opportunities.

PubMed

Herault, Yann; Delabar, Jean M; Fisher, Elizabeth M C; Tybulewicz, Victor L J; Yu, Eugene; Brault, Veronique

2017-10-01

Down syndrome is caused by trisomy of chromosome 21. To date, a multiplicity of mouse models with Down-syndrome-related features has been developed to understand this complex human chromosomal disorder. These mouse models have been important for determining genotype-phenotype relationships and identification of dosage-sensitive genes involved in the pathophysiology of the condition, and in exploring the impact of the additional chromosome on the whole genome. Mouse models of Down syndrome have also been used to test therapeutic strategies. Here, we provide an overview of research in the last 15 years dedicated to the development and application of rodent models for Down syndrome. We also speculate on possible and probable future directions of research in this fast-moving field. As our understanding of the syndrome improves and genome engineering technologies evolve, it is necessary to coordinate efforts to make all Down syndrome models available to the community, to test therapeutics in models that replicate the whole trisomy and design new animal models to promote further discovery of potential therapeutic targets. © 2017. Published by The Company of Biologists Ltd.
Strategic Planning in an Educational Development Centre: Motivation, Management, and Messiness

ERIC Educational Resources Information Center

Albon, Simon P.; Iqbal, Isabeau; Pearson, Marion L.

2016-01-01

Strategic planning in universities is frequently positioned as vital for clarifying future directions, providing a coherent basis for decision-making, establishing priorities, and improving organizational performance. Models for successful strategic planning abound and often present the process as linear and straightforward. In this essay, we…
A PRELIMINARY EVALUATION OF MODELS-3 CMAQ USING PARTICULATE MATTER DATA FROM THE IMPROVE NETWORK

EPA Science Inventory

The Clean Air Act and its Amendments require the United States Environmental Protection Agency (EPA) to establish National Ambient Air Quality Standards for Particulate Matter (PM) and to assess current and future air quality regulations designed to protect human health and wel...
Observations on Leadership, Problem Solving, and Preferred Futures of Universities

ERIC Educational Resources Information Center

Puncochar, Judith

2013-01-01

A focus on enrollments, rankings, uncertain budgets, and branding efforts to operate universities could have serious implications for discussions of sustainable solutions to complex problems and the decision-making processes of leaders. The Authentic Leadership Model for framing ill-defined problems in higher education is posited to improve the…
The Future Starts Now

ERIC Educational Resources Information Center

Panza, Carol M.

2012-01-01

The fishbone diagram developed by Mariano Bernardez (2009a, 2009b) in the introductory article to this issue of "Performance Improvement Quarterly" depicts the origins and interrelationships of the models and approaches of many fields and researchers that have contributed to human performance technology (HPT) as it is used today. We can…
Foreword to the Special Issue on Remote Sensing and Modeling of Surface Properties

USDA-ARS?s Scientific Manuscript database

CURRENTLY, the Numerical Weather Prediction (NWP) community is striving for better ways to extract information on the lower layer using current and future satellite systems to improve short-term to medium-range forecasts. The surface emissivity is highly variable and may cause biases in the forward ...

Educational Drama: A Model Used in a Business School

ERIC Educational Resources Information Center

de Villiers, Rouxelle; Botes, Vida L.

2014-01-01

This article considers the advantages, benefits, disadvantages and weaknesses of experiential learning through the use of educational drama (ED) to assist business students and academics to improve competencies required for their future roles in business. A review of the literature was undertaken. Simulated interaction (SI) and role-play (RP) are…
Hanging Together To Avoid Hanging Separately: Opportunities for Academic Libraries and Consortia.

ERIC Educational Resources Information Center

Allen, Barbara McFadden; Hirshon, Arnold

1998-01-01

Discusses academic library consortia, examines types of consortia, and presents three case histories (OhioLINK, PALCI and CIC). Highlights include economic competition; changes in information access and delivery; growth of information technology; quality improvement; and future strategies, including pricing models for electronic information,…
Modeling green infrastructure land use changes on future air quality in Kansas City

EPA Science Inventory

Green infrastructure can be a cost-effective approach for reducing stormwater runoff and improving water quality as a result, but it could also bring co-benefits for air quality: less impervious surfaces and more vegetation can decrease the urban heat island effect, and also resu...
Comparison of process-based models to quantify nutrient flows and greenhouse gas emissions of milk production

USDA-ARS?s Scientific Manuscript database

Assessing and improving the sustainability of dairy production systems is essential to secure future food production. This requires a holistic approach that reveals trade-offs between emissions of the different greenhouse gases (GHG) and nutrient-based pollutants and ensures that interactions betwee...
Genetic interactions for heat stress and production level: predicting foreign from domestic data

USDA-ARS?s Scientific Manuscript database

Genetic by environmental interactions were estimated from U.S. national data by separately adding random regressions for heat stress (HS) and herd production level (HL) to the all-breed animal model to improve predictions of future records and rankings in other climate and production situations. Yie...
The New Literacies of Online Reading Comprehension: Future Directions

ERIC Educational Resources Information Center

Coiro, Julie

2012-01-01

Research in four areas has the potential to dramatically improve how practitioners address the challenges of integrating digital texts and tasks into their literacy curriculum. Advances in defining and measuring key components of online reading comprehension are rapidly emerging. In addition, instructional models, such as Internet reciprocal…
Predictor Combination in Binary Decision-Making Situations

ERIC Educational Resources Information Center

McGrath, Robert E.

2008-01-01

Professional psychologists are often confronted with the task of making binary decisions about individuals, such as predictions about future behavior or employee selection. Test users familiar with linear models and Bayes's theorem are likely to assume that the accuracy of decisions is consistently improved by combination of outcomes across valid…
Using high-resolution future climate scenarios to forecast Bromus tectorum invasion in Rocky Mountain National Park.

PubMed

West, Amanda M; Kumar, Sunil; Wakie, Tewodros; Brown, Cynthia S; Stohlgren, Thomas J; Laituri, Melinda; Bromberg, Jim

2015-01-01

National Parks are hallmarks of ecosystem preservation in the United States. The introduction of alien invasive plant species threatens protection of these areas. Bromus tectorum L. (commonly called downy brome or cheatgrass), which is found in Rocky Mountain National Park (hereafter, the Park), Colorado, USA, has been implicated in early spring competition with native grasses, decreased soil nitrogen, altered nutrient and hydrologic regimes, and increased fire intensity. We estimated the potential distribution of B. tectorum in the Park based on occurrence records (n = 211), current and future climate, and distance to roads and trails. An ensemble of six future climate scenarios indicated the habitable area of B. tectorum may increase from approximately 5.5% currently to 20.4% of the Park by the year 2050. Using ordination methods we evaluated the climatic space occupied by B. tectorum in the Park and how this space may shift given future climate change. Modeling climate change at a small extent (1,076 km2) and at a fine spatial resolution (90 m) is a novel approach in species distribution modeling, and may provide inference for microclimates not captured in coarse-scale models. Maps from our models serve as high-resolution hypotheses that can be improved over time by land managers to set priorities for surveys and removal of invasive species such as B. tectorum.
Using High-Resolution Future Climate Scenarios to Forecast Bromus tectorum Invasion in Rocky Mountain National Park

PubMed Central

West, Amanda M.; Kumar, Sunil; Wakie, Tewodros; Brown, Cynthia S.; Stohlgren, Thomas J.; Laituri, Melinda; Bromberg, Jim

2015-01-01

National Parks are hallmarks of ecosystem preservation in the United States. The introduction of alien invasive plant species threatens protection of these areas. Bromus tectorum L. (commonly called downy brome or cheatgrass), which is found in Rocky Mountain National Park (hereafter, the Park), Colorado, USA, has been implicated in early spring competition with native grasses, decreased soil nitrogen, altered nutrient and hydrologic regimes, and increased fire intensity. We estimated the potential distribution of B. tectorum in the Park based on occurrence records (n = 211), current and future climate, and distance to roads and trails. An ensemble of six future climate scenarios indicated the habitable area of B. tectorum may increase from approximately 5.5% currently to 20.4% of the Park by the year 2050. Using ordination methods we evaluated the climatic space occupied by B. tectorum in the Park and how this space may shift given future climate change. Modeling climate change at a small extent (1,076 km2) and at a fine spatial resolution (90 m) is a novel approach in species distribution modeling, and may provide inference for microclimates not captured in coarse-scale models. Maps from our models serve as high-resolution hypotheses that can be improved over time by land managers to set priorities for surveys and removal of invasive species such as B. tectorum. PMID:25695255
An evaluation of Dynamic TOPMODEL for low flow simulation

NASA Astrophysics Data System (ADS)

Coxon, G.; Freer, J. E.; Quinn, N.; Woods, R. A.; Wagener, T.; Howden, N. J. K.

2015-12-01

Hydrological models are essential tools for drought risk management, often providing input to water resource system models, aiding our understanding of low flow processes within catchments and providing low flow predictions. However, simulating low flows and droughts is challenging as hydrological systems often demonstrate threshold effects in connectivity, non-linear groundwater contributions and a greater influence of water resource system elements during low flow periods. These dynamic processes are typically not well represented in commonly used hydrological models due to data and model limitations. Furthermore, calibrated or behavioural models may not be effectively evaluated during more extreme drought periods. A better understanding of the processes that occur during low flows and how these are represented within models is thus required if we want to be able to provide robust and reliable predictions of future drought events. In this study, we assess the performance of dynamic TOPMODEL for low flow simulation. Dynamic TOPMODEL was applied to a number of UK catchments in the Thames region using time series of observed rainfall and potential evapotranspiration data that captured multiple historic droughts over a period of several years. The model performance was assessed against the observed discharge time series using a limits of acceptability framework, which included uncertainty in the discharge time series. We evaluate the models against multiple signatures of catchment low-flow behaviour and investigate differences in model performance between catchments, model diagnostics and for different low flow periods. We also considered the impact of surface water and groundwater abstractions and discharges on the observed discharge time series and how this affected the model evaluation. From analysing the model performance, we suggest future improvements to Dynamic TOPMODEL to improve the representation of low flow processes within the model structure.
Cluster-void degeneracy breaking: Modified gravity in the balance

NASA Astrophysics Data System (ADS)

Sahlén, Martin; Silk, Joseph

2018-05-01

Combining galaxy cluster and void abundances is a novel, powerful way to constrain deviations from general relativity and the Λ CDM model. For a flat w CDM model with growth of large-scale structure parametrized by the redshift-dependent growth index γ (z )=γ0+γ1z /(1 +z ) of linear matter perturbations, combining void and cluster abundances in future surveys with Euclid and the four-meter multiobject spectroscopic telescope could improve the figure of merit for (w ,γ0,γ1) by a factor of 20 compared to individual abundances. In an ideal case, improvement on current cosmological data is a figure of merit factor 600 or more.
Helicopter rotor dynamics and aeroelasticity - Some key ideas and insights

NASA Technical Reports Server (NTRS)

Friedmann, Peretz P.

1990-01-01

Four important current topics in helicopter rotor dynamics and aeroelasticity are discussed: (1) the role of geometric nonlinearities in rotary-wing aeroelasticity; (2) structural modeling, free vibration, and aeroelastic analysis of composite rotor blades; (3) modeling of coupled rotor/fuselage areomechanical problems and their active control; and (4) use of higher-harmonic control for vibration reduction in helicopter rotors in forward flight. The discussion attempts to provide an improved fundamental understanding of the current state of the art. In this way, future research can be focused on problems which remain to be solved instead of producing marginal improvements on problems which are already understood.
Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China

PubMed Central

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-01-01

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan. PMID:28617348
The Future of Wind Energy in California: Future Projections in Variable-Resolution CESM

NASA Astrophysics Data System (ADS)

Wang, M.; Ullrich, P. A.; Millstein, D.; Collier, C.

2017-12-01

This study focuses on the wind energy characterization and future projection at five primary wind turbine sites in California. Historical (1980-2000) and mid-century (2030-2050) simulations were produced using the Variable-Resolution Community Earth System Model (VR-CESM) to analyze the trends and variations in wind energy under climate change. Datasets from Det Norske Veritas Germanischer Llyod (DNV GL), MERRA-2, CFSR, NARR, as well as surface observational data were used for model validation and comparison. Significant seasonal wind speed changes under RCP8.5 were detected from several wind farm sites. Large-scale patterns were then investigated to analyze the synoptic-scale impact on localized wind change. The agglomerative clustering method was applied to analyze and group different wind patterns. The associated meteorological background of each cluster was investigated to analyze the drivers of different wind patterns. This study improves the characterization of uncertainty around the magnitude and variability in space and time of California's wind resources in the near future, and also enhances understanding of the physical mechanisms related to the trends in wind resource variability.
Shaping the Future of Research: a perspective from junior scientists

PubMed Central

MacKellar, Drew C.; Mazzilli, Sarah A.; Pai, Vaibhav P.; Goodwin, Patricia R.; Walsh, Erica M.; Robinson-Mosher, Avi; Bowman, Thomas A.; Kraemer, James; Erb, Marcella L.; Schoenfeld, Eldi; Shokri, Leila; Jackson, Jonathan D.; Islam, Ayesha; Mattozzi, Matthew D.; Krukenberg, Kristin A.; Polka, Jessica K.

2015-01-01

The landscape of scientific research and funding is in flux as a result of tight budgets, evolving models of both publishing and evaluation, and questions about training and workforce stability. As future leaders, junior scientists are uniquely poised to shape the culture and practice of science in response to these challenges. A group of postdocs in the Boston area who are invested in improving the scientific endeavor, planned a symposium held on October 2 nd and 3 rd, 2014, as a way to join the discussion about the future of US biomedical research. Here we present a report of the proceedings of participant-driven workshops and the organizers’ synthesis of the outcomes. PMID:25653845
Collaborative Multi-Scale 3d City and Infrastructure Modeling and Simulation

NASA Astrophysics Data System (ADS)

Breunig, M.; Borrmann, A.; Rank, E.; Hinz, S.; Kolbe, T.; Schilcher, M.; Mundani, R.-P.; Jubierre, J. R.; Flurl, M.; Thomsen, A.; Donaubauer, A.; Ji, Y.; Urban, S.; Laun, S.; Vilgertshofer, S.; Willenborg, B.; Menninghaus, M.; Steuer, H.; Wursthorn, S.; Leitloff, J.; Al-Doori, M.; Mazroobsemnani, N.

2017-09-01

Computer-aided collaborative and multi-scale 3D planning are challenges for complex railway and subway track infrastructure projects in the built environment. Many legal, economic, environmental, and structural requirements have to be taken into account. The stringent use of 3D models in the different phases of the planning process facilitates communication and collaboration between the stake holders such as civil engineers, geological engineers, and decision makers. This paper presents concepts, developments, and experiences gained by an interdisciplinary research group coming from civil engineering informatics and geo-informatics banding together skills of both, the Building Information Modeling and the 3D GIS world. New approaches including the development of a collaborative platform and 3D multi-scale modelling are proposed for collaborative planning and simulation to improve the digital 3D planning of subway tracks and other infrastructures. Experiences during this research and lessons learned are presented as well as an outlook on future research focusing on Building Information Modeling and 3D GIS applications for cities of the future.
Probing particle and nuclear physics models of neutrinoless double beta decay with different nuclei

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

Fogli, G. L.; Rotunno, A. M.; Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Via Orabona 4, 70126 Bari

2009-07-01

Half-life estimates for neutrinoless double beta decay depend on particle physics models for lepton-flavor violation, as well as on nuclear physics models for the structure and transitions of candidate nuclei. Different models considered in the literature can be contrasted - via prospective data - with a 'standard' scenario characterized by light Majorana neutrino exchange and by the quasiparticle random phase approximation, for which the theoretical covariance matrix has been recently estimated. We show that, assuming future half-life data in four promising nuclei ({sup 76}Ge, {sup 82}Se, {sup 130}Te, and {sup 136}Xe), the standard scenario can be distinguished from a fewmore » nonstandard physics models, while being compatible with alternative state-of-the-art nuclear calculations (at 95% C.L.). Future signals in different nuclei may thus help to discriminate at least some decay mechanisms, without being spoiled by current nuclear uncertainties. Prospects for possible improvements are also discussed.« less
The technology acceptance model: its past and its future in health care.

PubMed

Holden, Richard J; Karsh, Ben-Tzion

2010-02-01

Increasing interest in end users' reactions to health information technology (IT) has elevated the importance of theories that predict and explain health IT acceptance and use. This paper reviews the application of one such theory, the Technology Acceptance Model (TAM), to health care. We reviewed 16 data sets analyzed in over 20 studies of clinicians using health IT for patient care. Studies differed greatly in samples and settings, health ITs studied, research models, relationships tested, and construct operationalization. Certain TAM relationships were consistently found to be significant, whereas others were inconsistent. Several key relationships were infrequently assessed. Findings show that TAM predicts a substantial portion of the use or acceptance of health IT, but that the theory may benefit from several additions and modifications. Aside from improved study quality, standardization, and theoretically motivated additions to the model, an important future direction for TAM is to adapt the model specifically to the health care context, using beliefs elicitation methods.
THE TECHNOLOGY ACCEPTANCE MODEL: ITS PAST AND ITS FUTURE IN HEALTH CARE

PubMed Central

HOLDEN, RICHARD J.; KARSH, BEN-TZION

2009-01-01

Increasing interest in end users’ reactions to health information technology (IT) has elevated the importance of theories that predict and explain health IT acceptance and use. This paper reviews the application of one such theory, the Technology Acceptance Model (TAM), to health care. We reviewed 16 data sets analyzed in over 20 studies of clinicians using health IT for patient care. Studies differed greatly in samples and settings, health ITs studied, research models, relationships tested, and construct operationalization. Certain TAM relationships were consistently found to be significant, whereas others were inconsistent. Several key relationships were infrequently assessed. Findings show that TAM predicts a substantial portion of the use or acceptance of health IT, but that the theory may benefit from several additions and modifications. Aside from improved study quality, standardization, and theoretically motivated additions to the model, an important future direction for TAM is to adapt the model specifically to the health care context, using beliefs elicitation methods. PMID:19615467
Scale dependency of regional climate modeling of current and future climate extremes in Germany

NASA Astrophysics Data System (ADS)

Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

2017-11-01

A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

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.
Integrated decision-making about housing, energy and wellbeing: a qualitative system dynamics model.

PubMed

Macmillan, Alexandra; Davies, Michael; Shrubsole, Clive; Luxford, Naomi; May, Neil; Chiu, Lai Fong; Trutnevyte, Evelina; Bobrova, Yekatherina; Chalabi, Zaid

2016-03-08

The UK government has an ambitious goal to reduce carbon emissions from the housing stock through energy efficiency improvements. This single policy goal is a strong driver for change in the housing system, but comes with positive and negative "unintended consequences" across a broad range of outcomes for health, equity and environmental sustainability. The resulting policies are also already experiencing under-performance through a failure to consider housing as a complex system. This research aimed to move from considering disparate objectives of housing policies in isolation to mapping the links between environmental, economic, social and health outcomes as a complex system. We aimed to support a broad range of housing policy stakeholders to improve their understanding of housing as a complex system through a collaborative learning process. We used participatory system dynamics modelling to develop a qualitative causal theory linking housing, energy and wellbeing. Qualitative interviews were followed by two interactive workshops to develop the model, involving representatives from national and local government, housing industries, non-government organisations, communities and academia. More than 50 stakeholders from 37 organisations participated. The process resulted in a shared understanding of wellbeing as it relates to housing; an agreed set of criteria against which to assess to future policy options; and a comprehensive set of causal loop diagrams describing the housing, energy and wellbeing system. The causal loop diagrams cover seven interconnected themes: community connection and quality of neighbourhoods; energy efficiency and climate change; fuel poverty and indoor temperature; household crowding; housing affordability; land ownership, value and development patterns; and ventilation and indoor air pollution. The collaborative learning process and the model have been useful for shifting the thinking of a wide range of housing stakeholders towards a more integrated approach to housing. The qualitative model has begun to improve the assessment of future policy options across a broad range of outcomes. Future work is needed to validate the model and increase its utility through computer simulation incorporating best quality data and evidence. Combining system dynamics modelling with other methods for weighing up policy options, as well as methods to support shifts in the conceptual frameworks underpinning policy, will be necessary to achieve shared housing goals across physical, mental, environmental, economic and social wellbeing.
Theory of constraints for publicly funded health systems.

PubMed

Sadat, Somayeh; Carter, Michael W; Golden, Brian

2013-03-01

Originally developed in the context of publicly traded for-profit companies, theory of constraints (TOC) improves system performance through leveraging the constraint(s). While the theory seems to be a natural fit for resource-constrained publicly funded health systems, there is a lack of literature addressing the modifications required to adopt TOC and define the goal and performance measures. This paper develops a system dynamics representation of the classical TOC's system-wide goal and performance measures for publicly traded for-profit companies, which forms the basis for developing a similar model for publicly funded health systems. The model is then expanded to include some of the factors that affect system performance, providing a framework to apply TOC's process of ongoing improvement in publicly funded health systems. Future research is required to more accurately define the factors affecting system performance and populate the model with evidence-based estimates for various parameters in order to use the model to guide TOC's process of ongoing improvement.
The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review

PubMed Central

Arbuthnott, Katherine; Kovats, Sari; Hajat, Shakoor; Falloon, Pete

2017-01-01

Background and objectives Heat related mortality is of great concern for public health, and estimates of future mortality under a warming climate are important for planning of resources and possible adaptation measures. Papers providing projections of future heat-related mortality were critically reviewed with a focus on the use of climate model data. Some best practice guidelines are proposed for future research. Methods The electronic databases Web of Science and PubMed/Medline were searched for papers containing a quantitative estimate of future heat-related mortality. The search was limited to papers published in English in peer-reviewed journals up to the end of March 2017. Reference lists of relevant papers and the citing literature were also examined. The wide range of locations studied and climate data used prevented a meta-analysis. Results A total of 608 articles were identified after removal of duplicate entries, of which 63 were found to contain a quantitative estimate of future mortality from hot days or heat waves. A wide range of mortality models and climate model data have been used to estimate future mortality. Temperatures in the climate simulations used in these studies were projected to increase. Consequently, all the papers indicated that mortality from high temperatures would increase under a warming climate. The spread in projections of future climate by models adds substantial uncertainty to estimates of future heat-related mortality. However, many studies either did not consider this source of uncertainty, or only used results from a small number of climate models. Other studies showed that uncertainty from changes in populations and demographics, and the methods for adaptation to warmer temperatures were at least as important as climate model uncertainty. Some inconsistencies in the use of climate data (for example, using global mean temperature changes instead of changes for specific locations) and interpretation of the effects on mortality were apparent. Some factors which have not been considered when estimating future mortality are summarised. Conclusions Most studies have used climate data generated using scenarios with medium and high emissions of greenhouse gases. More estimates of future mortality using climate information from the mitigation scenario RCP2.6 are needed, as this scenario is the only one under which the Paris Agreement to limit global warming to 2°C or less could be realised. Many of the methods used to combine modelled data with local climate observations are simplistic. Quantile-based methods might offer an improved approach, especially for temperatures at the ends of the distributions. The modelling of adaptation to warmer temperatures in mortality models is generally arbitrary and simplistic, and more research is needed to better quantify adaptation. Only a small number of studies included possible changes in population and demographics in their estimates of future mortality, meaning many estimates of mortality could be biased low. Uncertainty originating from establishing a mortality baseline, climate projections, adaptation and population changes is important and should be considered when estimating future mortality. PMID:28686743
High-Performance Computer Modeling of the Cosmos-Iridium Collision

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

Olivier, S; Cook, K; Fasenfest, B

2009-08-28

This paper describes the application of a new, integrated modeling and simulation framework, encompassing the space situational awareness (SSA) enterprise, to the recent Cosmos-Iridium collision. This framework is based on a flexible, scalable architecture to enable efficient simulation of the current SSA enterprise, and to accommodate future advancements in SSA systems. In particular, the code is designed to take advantage of massively parallel, high-performance computer systems available, for example, at Lawrence Livermore National Laboratory. We will describe the application of this framework to the recent collision of the Cosmos and Iridium satellites, including (1) detailed hydrodynamic modeling of the satellitemore » collision and resulting debris generation, (2) orbital propagation of the simulated debris and analysis of the increased risk to other satellites (3) calculation of the radar and optical signatures of the simulated debris and modeling of debris detection with space surveillance radar and optical systems (4) determination of simulated debris orbits from modeled space surveillance observations and analysis of the resulting orbital accuracy, (5) comparison of these modeling and simulation results with Space Surveillance Network observations. We will also discuss the use of this integrated modeling and simulation framework to analyze the risks and consequences of future satellite collisions and to assess strategies for mitigating or avoiding future incidents, including the addition of new sensor systems, used in conjunction with the Space Surveillance Network, for improving space situational awareness.« less
Fontan Surgical Planning: Previous Accomplishments, Current Challenges, and Future Directions.

PubMed

Trusty, Phillip M; Slesnick, Timothy C; Wei, Zhenglun Alan; Rossignac, Jarek; Kanter, Kirk R; Fogel, Mark A; Yoganathan, Ajit P

2018-04-01

The ultimate goal of Fontan surgical planning is to provide additional insights into the clinical decision-making process. In its current state, surgical planning offers an accurate hemodynamic assessment of the pre-operative condition, provides anatomical constraints for potential surgical options, and produces decent post-operative predictions if boundary conditions are similar enough between the pre-operative and post-operative states. Moving forward, validation with post-operative data is a necessary step in order to assess the accuracy of surgical planning and determine which methodological improvements are needed. Future efforts to automate the surgical planning process will reduce the individual expertise needed and encourage use in the clinic by clinicians. As post-operative physiologic predictions improve, Fontan surgical planning will become an more effective tool to accurately model patient-specific hemodynamics.
Cost/benefit trade-offs for reducing the energy consumption of commercial air transportation (RECAT)

NASA Technical Reports Server (NTRS)

Gobetz, F. W.; Leshane, A. A.

1976-01-01

The RECAT study evaluated the opportunities for reducing the energy requirements of the U.S. domestic air passenger transport system through improved operational techniques, modified in-service aircraft, derivatives of current production models, or new aircraft using either current or advanced technology. Each of these fuel-conserving alternatives was investigated individually to test its potential for fuel conservation relative to a hypothetical baseline case in which current, in-production aircraft types are assumed to operate, without modification and with current operational techniques, into the future out to the year 2000. Consequently, while the RECAT results lend insight into the directions in which technology can best be pursued for improved air transport fuel economy, no single option studied in the RECAT program is indicative of a realistic future scenario.
Projecting technology change to improve space technology planning and systems management

NASA Astrophysics Data System (ADS)

Walk, Steven Robert

2011-04-01

Projecting technology performance evolution has been improving over the years. Reliable quantitative forecasting methods have been developed that project the growth, diffusion, and performance of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These forecasts can be applied at the early stages of space technology planning to better predict available future technology performance, assure the successful selection of technology, and improve technology systems management strategy. Often what is published as a technology forecast is simply scenario planning, usually made by extrapolating current trends into the future, with perhaps some subjective insight added. Typically, the accuracy of such predictions falls rapidly with distance in time. Quantitative technology forecasting (QTF), on the other hand, includes the study of historic data to identify one of or a combination of several recognized universal technology diffusion or substitution patterns. In the same manner that quantitative models of physical phenomena provide excellent predictions of system behavior, so do QTF models provide reliable technological performance trajectories. In practice, a quantitative technology forecast is completed to ascertain with confidence when the projected performance of a technology or system of technologies will occur. Such projections provide reliable time-referenced information when considering cost and performance trade-offs in maintaining, replacing, or migrating a technology, component, or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical application in space technology and technology systems management.
Simulated Impacts of Climate Change on Water Use and Yield of Irrigated Sugarcane in South Africa

NASA Technical Reports Server (NTRS)

Jones, M.R; Singels, A.; Ruane, A. C.

2015-01-01

Reliable predictions of climate change impacts on water use, irrigation requirements and yields of irrigated sugarcane in South Africa (a water-scarce country) are necessary to plan adaptation strategies. Although previous work has been done in this regard, methodologies and results vary considerably. The objectives were (1) to estimate likely impacts of climate change on sugarcane yields, water use and irrigation demand at three irrigated sugarcane production sites in South Africa (Malelane, Pongola and La Mercy) for current (1980-2010) and future (2070-2100) climate scenarios, using an approach based on the Agricultural Model Inter-comparison and Improvement Project (AgMIP) protocols; and (2) to assess the suitability of this methodology for investigating climate change impacts on sugarcane production. Future climate datasets were generated using the Delta downscaling method and three Global Circulation Models (GCMs) assuming atmospheric CO2 concentration [CO2] of 734 ppm(A2 emissions scenario). Yield and water use were simulated using the DSSAT-Canegro v4.5 model. Irrigated cane yields are expected to increase at all three sites (between 11 and 14%), primarily due to increased interception of radiation as a result of accelerated canopy development. Evapotranspiration and irrigation requirements increased by 11% due to increased canopy cover and evaporative demand. Sucrose yields are expected to decline because of increased consumption of photo-assimilate for structural growth and maintenance respiration. Crop responses in canopy development and yield formation differed markedly between the crop cycles investigated. Possible agronomic implications of these results include reduced weed control costs due to shortened periods of partial canopy, a need for improved efficiency of irrigation to counter increased demands, and adjustments to ripening and harvest practices to counter decreased cane quality and optimize productivity. Although the Delta climate data downscaling method is considered robust, accurate and easily-understood, it does not change the future number of rain-days per month. The impacts of this and other climate data simplifications ought to be explored in future work. Shortcomings of the DSSAT-Canegro model include the simulated responses of phenological development, photosynthesis and respiration processes to high temperatures, and the disconnect between simulated biomass accumulation and expansive growth. Proposed methodology refinements should improve the reliability of predicted climate change impacts on sugarcane yield.
IRI-2016: Description and Introduction

NASA Astrophysics Data System (ADS)

Bilitza, Dieter; Watanabe, Shigeto; Truhlik, Vladimir; Altadill, David

2016-07-01

The International Reference Ionosphere (IRI) is recognized as the official standard for the ionosphere (COSPAR, URSI, ISO) and is widely used for a multitude of different applications as evidenced by the many papers in science and engineering journals that acknowledge the use of IRI (e.g., about 11% of all Radio Science papers each year and citations in 21 different journals in 2015). The improvement process of the model is continuing as new data become fully available and new modeling techniques provide a more optimal representation of the observed variation patterns. We will introduce and present the latest version of the IRI model (IRI-2016) and discuss the impact of the various improvements and new additions. Most importantly, two new models will be introduced for the F2 peak height, hmF2, that were developed based on ionosonde measurements and COSMIC radio occultation data, respectively. In addition IRI-2016 includes an improved representation of the ionosphere during the very low solar activities that were reached during the last solar minimum in 2008/2009. A number of other improvements and corrections were implemented in the model and will be discussed in this presentation. We will also report about recent IRI workshops and their findings and plans for the future.
Effects of 4D-Var data assimilation using remote sensing precipitation products in a WRF over the complex Heihe River Basin

NASA Astrophysics Data System (ADS)

Pan, Xiaoduo; Li, Xin; Cheng, Guodong

2017-04-01

Traditionally, ground-based, in situ observations, remote sensing, and regional climate modeling, individually, cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrain. Data assimilation techniques are often used to assimilate ground observations and remote sensing products into models for dynamic downscaling. In this study, the Weather Research and Forecasting (WRF) model was used to assimilate two satellite precipitation products (TRMM 3B42 and FY-2D) using the 4D-Var data assimilation method. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly for short-term weather forecasting. Future work is proposed to assimilate a suite of remote sensing data, e.g., the combination of precipitation and soil moisture data, into a WRF model to improve 7-8 day forecasts of precipitation and other atmospheric variables.
A protocol for the intercomparison of marine fishery and ecosystem models: Fish-MIP v1.0

NASA Astrophysics Data System (ADS)

Tittensor, Derek P.; Eddy, Tyler D.; Lotze, Heike K.; Galbraith, Eric D.; Cheung, William; Barange, Manuel; Blanchard, Julia L.; Bopp, Laurent; Bryndum-Buchholz, Andrea; Büchner, Matthias; Bulman, Catherine; Carozza, David A.; Christensen, Villy; Coll, Marta; Dunne, John P.; Fernandes, Jose A.; Fulton, Elizabeth A.; Hobday, Alistair J.; Huber, Veronika; Jennings, Simon; Jones, Miranda; Lehodey, Patrick; Link, Jason S.; Mackinson, Steve; Maury, Olivier; Niiranen, Susa; Oliveros-Ramos, Ricardo; Roy, Tilla; Schewe, Jacob; Shin, Yunne-Jai; Silva, Tiago; Stock, Charles A.; Steenbeek, Jeroen; Underwood, Philip J.; Volkholz, Jan; Watson, James R.; Walker, Nicola D.

2018-04-01

Model intercomparison studies in the climate and Earth sciences communities have been crucial to building credibility and coherence for future projections. They have quantified variability among models, spurred model development, contrasted within- and among-model uncertainty, assessed model fits to historical data, and provided ensemble projections of future change under specified scenarios. Given the speed and magnitude of anthropogenic change in the marine environment and the consequent effects on food security, biodiversity, marine industries, and society, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. Here, we describe the Fisheries and Marine Ecosystem Model Intercomparison Project protocol version 1.0 (Fish-MIP v1.0), part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is a cross-sectoral network of climate impact modellers. Given the complexity of the marine ecosystem, this class of models has substantial heterogeneity of purpose, scope, theoretical underpinning, processes considered, parameterizations, resolution (grain size), and spatial extent. This heterogeneity reflects the lack of a unified understanding of the marine ecosystem and implies that the assemblage of all models is more likely to include a greater number of relevant processes than any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) Coupled Model Intercomparison Project Phase 5 (CMIP5) outputs under prescribed scenarios for historic (from the 1950s) and future (to 2100) time periods; it will be adapted to CMIP phase 6 (CMIP6) in future iterations. It also describes a standardized set of outputs for each participating Fish-MIP model to produce. This enables the broad characterization of differences between and uncertainties within models and projections when assessing climate and fisheries impacts on marine ecosystems and the services they provide. The systematic generation, collation, and comparison of results from Fish-MIP will inform an understanding of the range of plausible changes in marine ecosystems and improve our capacity to define and convey the strengths and weaknesses of model-based advice on future states of marine ecosystems and fisheries. Ultimately, Fish-MIP represents a step towards bringing together the marine ecosystem modelling community to produce consistent ensemble medium- and long-term projections of marine ecosystems.
Potential Applications of Gosat Based Carbon Budget Products to Refine Terrestrial Ecosystem Model

NASA Astrophysics Data System (ADS)

Kondo, M.; Ichii, K.

2011-12-01

Estimation of carbon exchange in terrestrial ecosystem associates with difficulties due to complex entanglement of physical and biological processes: thus, the net ecosystem productivity (NEP) estimated from simulation often differs among process-based terrestrial ecosystem models. In addition to complexity of the system, validation can only be conducted in a point scale since reliable observation is only available from ground observations. With a lack of large spatial data, extension of model simulation to a global scale results in significant uncertainty in the future carbon balance and climate change. Greenhouse gases Observing SATellite (GOSAT), launched by the Japanese space agency (JAXA) in January, 2009, is the 1st operational satellite promised to deliver the net land-atmosphere carbon budget to the terrestrial biosphere research community. Using that information, the model reproducibility of carbon budget is expected to improve: hence, gives a better estimation of the future climate change. This initial analysis is to seek and evaluate the potential applications of GOSAT observation toward the sophistication of terrestrial ecosystem model. The present study was conducted in two processes: site-based analysis using eddy covariance observation data to assess the potential use of terrestrial carbon fluxes (GPP, RE, and NEP) to refine the model, and extension of the point scale analysis to spatial using Carbon Tracker product as a prototype of GOSAT product. In the first phase of the experiment, it was verified that an optimization routine adapted to a terrestrial model, Biome-BGC, yielded the improved result with respect to eddy covariance observation data from AsiaFlux Network. Spatial data sets used in the second phase were consists of GPP from empirical algorithm (e.g. support vector machine), NEP from Carbon Tracker, and RE from the combination of these. These spatial carbon flux estimations was used to refine the model applying the exactly same optimization procedure as the point analysis, and found that these spatial data help to improve the model's overall reproducibility. The GOSAT product is expected to have higher accuracy since it uses global CO2 observations. Therefore, with the application of GOSAT data, a better estimation of terrestrial carbon cycle can be achieved with optimization. It is anticipated to carry out more detailed analysis upon the arrival of GOSAT product and to verify the reduction in the uncertainty in the future carbon budget and the climate change with the calibrated models, which is the major contribution can be achieved from GOSAT.
The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 3: Intensive use of living resources, agriculture. Part 2: Distribution effects

NASA Technical Reports Server (NTRS)

Bradford, D. F.; Kelejian, H. H.

1974-01-01

The results of an investigation of the value of improving information for forecasting future crop harvests are described. A theoretical model is developed to calculate the value of increased speed of availablitiy of that information. The analysis of U.S. domestic wheat consumption was implemented. New estimates of a demand function for wheat and of a cost of storage function were involved, along with a Monte Carlo simulation for the wheat spot and future markets and a model of market determinations of wheat inventories. Results are shown to depend critically on the accuracy of current and proposed measurement techniques.
On the Reconstruction of Palaeo-Ice Sheets: Recent Advances and Future Challenges

NASA Technical Reports Server (NTRS)

Stokes, Chris R.; Tarasov, Lev; Blomdin, Robin; Cronin, Thomas M.; Fisher, Timothy G.; Gyllencreutz, Richard; Hattestrand, Clas; Heyman, Jacob; Hindmarsh, Richard C. A.; Hughes, Anna L. C.;

2015-01-01

Reconstructing the growth and decay of palaeo-ice sheets is critical to understanding mechanisms of global climate change and associated sea-level fluctuations in the past, present and future. The significance of palaeo-ice sheets is further underlined by the broad range of disciplines concerned with reconstructing their behaviour, many of which have undergone a rapid expansion since the 1980s. In particular, there has been a major increase in the size and qualitative diversity of empirical data used to reconstruct and date ice sheets, and major improvements in our ability to simulate their dynamics in numerical ice sheet models. These developments have made it increasingly necessary to forge interdisciplinary links between sub-disciplines and to link numerical modelling with observations and dating of proxy records. The aim of this paper is to evaluate recent developments in the methods used to reconstruct ice sheets and outline some key challenges that remain, with an emphasis on how future work might integrate terrestrial and marine evidence together with numerical modelling. Our focus is on pan-ice sheet reconstructions of the last deglaciation, but regional case studies are used to illustrate methodological achievements, challenges and opportunities. Whilst various disciplines have made important progress in our understanding of ice-sheet dynamics, it is clear that data-model integration remains under-used, and that uncertainties remain poorly quantified in both empirically-based and numerical ice-sheet reconstructions. The representation of past climate will continue to be the largest source of uncertainty for numerical modelling. As such, palaeo-observations are critical to constrain and validate modelling. State-of-the-art numerical models will continue to improve both in model resolution and in the breadth of inclusion of relevant processes, thereby enabling more accurate and more direct comparison with the increasing range of palaeo-observations. Thus, the capability is developing to use all relevant palaeo-records to more strongly constrain deglacial (and to a lesser extent pre-LGM) ice sheet evolution. In working towards that goal, the accurate representation of uncertainties is required for both constraint data and model outputs. Close cooperation between modelling and data-gathering communities is essential to ensure this capability is realised and continues to progress.

On the reconstruction of palaeo-ice sheets: Recent advances and future challenges

USGS Publications Warehouse

Stokes, Chris R.; Tarasov, Lev; Blomdin, Robin; Cronin, Thomas M.; Fisher, Timothy G.; Gyllencreutz, Richard; Hattestrand, Clas; Heyman, Jakob; Hindmarsh, Richard C. A.; Hughes, Anna L. C.; Jakobsson, Martin; Kirchner, Nina; Livingstone, Stephen J.; Margold, Martin; Murton, Julian B.; Noormets, Riko; Peltier, W. Richard; Peteet, Dorothy M.; Piper, David J. W.; Preusser, Frank; Renssen, Hans; Roberts, David H.; Roche, Didier M.; Saint-Ange, Francky; Stroeven, Arjen P.; Teller, James T.

2015-01-01

Reconstructing the growth and decay of palaeo-ice sheets is critical to understanding mechanisms of global climate change and associated sea-level fluctuations in the past, present and future. The significance of palaeo-ice sheets is further underlined by the broad range of disciplines concerned with reconstructing their behaviour, many of which have undergone a rapid expansion since the 1980s. In particular, there has been a major increase in the size and qualitative diversity of empirical data used to reconstruct and date ice sheets, and major improvements in our ability to simulate their dynamics in numerical ice sheet models. These developments have made it increasingly necessary to forge interdisciplinary links between sub-disciplines and to link numerical modelling with observations and dating of proxy records. The aim of this paper is to evaluate recent developments in the methods used to reconstruct ice sheets and outline some key challenges that remain, with an emphasis on how future work might integrate terrestrial and marine evidence together with numerical modelling. Our focus is on pan-ice sheet reconstructions of the last deglaciation, but regional case studies are used to illustrate methodological achievements, challenges and opportunities. Whilst various disciplines have made important progress in our understanding of ice-sheet dynamics, it is clear that data-model integration remains under-used, and that uncertainties remain poorly quantified in both empirically-based and numerical ice-sheet reconstructions. The representation of past climate will continue to be the largest source of uncertainty for numerical modelling. As such, palaeo-observations are critical to constrain and validate modelling. State-of-the-art numerical models will continue to improve both in model resolution and in the breadth of inclusion of relevant processes, thereby enabling more accurate and more direct comparison with the increasing range of palaeo-observations. Thus, the capability is developing to use all relevant palaeo-records to more strongly constrain deglacial (and to a lesser extent pre-LGM) ice sheet evolution. In working towards that goal, the accurate representation of uncertainties is required for both constraint data and model outputs. Close cooperation between modelling and data-gathering communities is essential to ensure this capability is realised and continues to progress.
The Community Climate System Model.

NASA Astrophysics Data System (ADS)

Blackmon, Maurice; Boville, Byron; Bryan, Frank; Dickinson, Robert; Gent, Peter; Kiehl, Jeffrey; Moritz, Richard; Randall, David; Shukla, Jagadish; Solomon, Susan; Bonan, Gordon; Doney, Scott; Fung, Inez; Hack, James; Hunke, Elizabeth; Hurrell, James; Kutzbach, John; Meehl, Jerry; Otto-Bliesner, Bette; Saravanan, R.; Schneider, Edwin K.; Sloan, Lisa; Spall, Michael; Taylor, Karl; Tribbia, Joseph; Washington, Warren

2001-11-01

The Community Climate System Model (CCSM) has been created to represent the principal components of the climate system and their interactions. Development and applications of the model are carried out by the U.S. climate research community, thus taking advantage of both wide intellectual participation and computing capabilities beyond those available to most individual U.S. institutions. This article outlines the history of the CCSM, its current capabilities, and plans for its future development and applications, with the goal of providing a summary useful to present and future users. The initial version of the CCSM included atmosphere and ocean general circulation models, a land surface model that was grafted onto the atmosphere model, a sea-ice model, and a flux coupler that facilitates information exchanges among the component models with their differing grids. This version of the model produced a successful 300-yr simulation of the current climate without artificial flux adjustments. The model was then used to perform a coupled simulation in which the atmospheric CO2 concentration increased by 1% per year. In this version of the coupled model, the ocean salinity and deep-ocean temperature slowly drifted away from observed values. A subsequent correction to the roughness length used for sea ice significantly reduced these errors. An updated version of the CCSM was used to perform three simulations of the twentieth century's climate, and several pro-jections of the climate of the twenty-first century. The CCSM's simulation of the tropical ocean circulation has been significantly improved by reducing the background vertical diffusivity and incorporating an anisotropic horizontal viscosity tensor. The meridional resolution of the ocean model was also refined near the equator. These changes have resulted in a greatly improved simulation of both the Pacific equatorial undercurrent and the surface countercurrents. The interannual variability of the sea surface temperature in the central and eastern tropical Pacific is also more realistic in simulations with the updated model. Scientific challenges to be addressed with future versions of the CCSM include realistic simulation of the whole atmosphere, including the middle and upper atmosphere, as well as the troposphere; simulation of changes in the chemical composition of the atmosphere through the incorporation of an integrated chemistry model; inclusion of global, prognostic biogeochemical components for land, ocean, and atmosphere; simulations of past climates, including times of extensive continental glaciation as well as times with little or no ice; studies of natural climate variability on seasonal-to-centennial timescales; and investigations of anthropogenic climate change. In order to make such studies possible, work is under way to improve all components of the model. Plans call for a new version of the CCSM to be released in 2002. Planned studies with the CCSM will require much more computer power than is currently available.
Communicating Ocean Sciences to Informal Audiences (COSIA): Universities, Oceanographic Institutions, Science Centers and Aquariums Working Together to Improve Ocean Education and Public Outreach

NASA Astrophysics Data System (ADS)

Glenn, S.; McDonnell, J.; Halversen, C.; Zimmerman, T.

2006-12-01

Ocean observatories have already demonstrated their ability to maintain long-term time series, capture episodic events, provide context for improved shipboard sampling, and improve accessibility to a broader range of participants. Communicating Ocean Sciences, an already existing college course (http://www.cacosee.net/collegecourse) from COSEE California has demonstrated its ability to teach future scientists essential communication skills. The NSF-funded Communicating Ocean Sciences to Informal Audiences (COSIA) project will leverage these experiences and others to demonstrate a long-term model for promoting effective science communication skills and techniques applicable to diverse audiences. The COSIA effort will be one of the pathfinders for ensuring that the new scientific results from the increasing U.S. investments in ocean observatories is effectively communicated to the nation, and will serve as a model for other fields. Our presentation will describe a long-term model for promoting effective science communication skills and techniques applicable to diverse audiences. COSIA established partnerships between informal science education institutions and universities nationwide to facilitate quality outreach by scientists and the delivery of rigorous, cutting edge science by informal educators while teaching future scientists (college students) essential communication skills. The COSIA model includes scientist-educator partnerships that develop and deliver a college course derived from COS that teaches communication skills through the understanding of learning theory specifically related to informal learning environments and the practice of these skills at aquariums and science centers. The goals of COSIA are to: provide a model for establishing substantive, long-term partnerships between scientists and informal science education institutions to meet their respective outreach needs; provide future scientists with experiences delivering outreach to informal institutions and promoting the broader impact of research; and provide diverse role models and inquiry-based ocean sciences activities for children and families visiting ISEI. COSIA partners include: Hampton University Virginia Aquarium; Oregon State University Hatfield Marine Science Visitor's Center; Rutgers University Liberty Science Center; University of California, Berkeley Lawrence Hall of Science; and University of Southern California Aquarium of the Pacific. COS has been or will soon be taught at Rutgers University, UC Berkeley, Stanford, Woods Hole Oceanographic Institute, University of Oregon (GK-12 program), Scripps Institution of Oceanography, and others. Data from surveys of students demonstrates improvement in their understanding of how people learn and how to effectively communicate. For example, there was a decrease in agreement with statements describing traditional didactic teaching strategies suggesting that students who took the course developed a more sophisticated, inquiry-based philosophy of learning. Providing college students with a background in current learning theory, and applying that theory through practical science communication experiences, will empower future generations of scientists to meet the communication challenges they will encounter in their careers.
Creating Rural Allied Health Leadership Structures Using District Advisors: An Action Research Project Using Program Logic.

PubMed

Schmidt, David; Kurtz, Megan; Davidson, Stuart

2017-01-01

District advisors in five allied health disciplines were introduced in a local health district in rural Australia in 2013. These strategic leadership roles provide support to clinicians and managers. As there is little research exploring allied health leadership models from a strategic and operational perspective, the coordinated commencement of these roles provided opportunity to study the creation of this leadership structure. Four advisors participated in this action research study which used focus groups and program logic processes to explore the inputs, outputs, barriers, outcomes to date, and preferred future outcomes of the leadership model. A purpose-built questionnaire was sent to 134 allied health clinicians or managers with questionnaire responses used by advisors to visualise the leadership model. Advisors prioritised policy development, representing the profession outside the organisation, and supporting department managers, whilst clinicians prioritised communication and connection-building within the organisation. Outcomes of the leadership model included connection, coordination, and advocacy for clinicians. Future preferred outcomes included increased strategic and workforce planning. Barriers included limited time, a widespread workforce and limited resourcing. Instituting a leadership model improved communication, cohesion, and coordination within the organisation. Future increases in workforce planning and coordination are limited by advisor capacity and competing workloads.
Development of a hybrid model to predict construction and demolition waste: China as a case study.

PubMed

Song, Yiliao; Wang, Yong; Liu, Feng; Zhang, Yixin

2017-01-01

Construction and demolition waste (C&DW) is currently a worldwide issue, and the situation is the worst in China due to a rapid increase in the construction industry and the short life span of China's buildings. To create an opportunity out of this problem, comprehensive prevention measures and effective management strategies are urgently needed. One major gap in the literature of waste management is a lack of estimations on future C&DW generation. Therefore, this paper presents a forecasting procedure for C&DW in China that can forecast the quantity of each component in such waste. The proposed approach is based on a GM-SVR model that improves the forecasting effectiveness of the gray model (GM), which is achieved by adjusting the residual series by a support vector regression (SVR) method and a transition matrix that aims to estimate the discharge of each component in the C&DW. Through the proposed method, future C&DW volume are listed and analyzed containing their potential components and distribution in different provinces in China. Besides, model testing process provides mathematical evidence to validate the proposed model is an effective way to give future information of C&DW for policy makers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improving the Yield and Nutritional Quality of Forage Crops

PubMed Central

Capstaff, Nicola M.; Miller, Anthony J.

2018-01-01

Despite being some of the most important crops globally, there has been limited research on forages when compared with cereals, fruits, and vegetables. This review summarizes the literature highlighting the significance of forage crops, the current improvements and some of future directions for improving yield and nutritional quality. We make the point that the knowledge obtained from model plant and grain crops can be applied to forage crops. The timely development of genomics and bioinformatics together with genome editing techniques offer great scope to improve forage crops. Given the social, environmental and economic importance of forage across the globe and especially in poorer countries, this opportunity has enormous potential to improve food security and political stability. PMID:29740468
Ecological impact of historical and future land-use patterns in Senegal

USGS Publications Warehouse

Parton, W.; Tappan, G. Gray; Ojima, D.; Tschakert, P.

2004-01-01

The CENTURY model was used to simulate changes in total system carbon resulting from land-use history (1850–2000), and impacts of climatic changes and improved land-use management practices in Senegal. Results show that 0.477 Gtons of carbon have been lost from 1850 to 2000. Improved management practices have the potential of increasing carbon levels by 0.116 Gtons from 2000 to 2100. Potential to store carbon exists for improved forest management and agriculture practices in southern Senegal. Potential climatic changes decrease plant production (30 percent), total system carbon (14 percent), and the potential to store carbon from improved management practices (31 percent).
The Role of Lean Process Improvement in Implementation of Evidence-Based Practices in Behavioral Health Care.

PubMed

Steinfeld, Bradley; Scott, Jennifer; Vilander, Gavin; Marx, Larry; Quirk, Michael; Lindberg, Julie; Koerner, Kelly

2015-10-01

To effectively implement evidence-based practices (EBP) in behavioral health care, an organization needs to have operating structures and processes that can address core EBP implementation factors and stages. Lean, a widely used quality improvement process, can potentially address the factors crucial to successful implementation of EBP. This article provides an overview of Lean and the relationship between Lean process improvement steps, and EBP implementation models. Examples of how Lean process improvement methodologies can be used to help plan and carry out implementation of EBP in mental health delivery systems are presented along with limitations and recommendations for future research and clinical application.
An Improved Approach for Forecasting Ecological Impacts from Future Drilling in Unconventional Shale Oil and Gas Plays.

PubMed

Wolaver, Brad D; Pierre, Jon Paul; Ikonnikova, Svetlana A; Andrews, John R; McDaid, Guinevere; Ryberg, Wade A; Hibbitts, Toby J; Duran, Charles M; Labay, Benjamin J; LaDuc, Travis J

2018-04-13

Directional well drilling and hydraulic fracturing has enabled energy production from previously inaccessible resources, but caused vegetation conversion and landscape fragmentation, often in relatively undisturbed habitats. We improve forecasts of future ecological impacts from unconventional oil and gas play developments using a new, more spatially-explicit approach. We applied an energy production outlook model, which used geologic and economic data from thousands of wells and three oil price scenarios, to map future drilling patterns and evaluate the spatial distribution of vegetation conversion and habitat impacts. We forecast where future well pad construction may be most intense, illustrating with an example from the Eagle Ford Shale Play of Texas. We also illustrate the ecological utility of this approach using the Spot-tailed Earless Lizard (Holbrookia lacerata) as the focal species, which historically occupied much of the Eagle Ford and awaits a federal decision for possible Endangered Species Act protection. We found that ~17,000-45,500 wells would be drilled 2017‒2045 resulting in vegetation conversion of ~26,485-70,623 ha (0.73-1.96% of pre-development vegetation), depending on price scenario ($40-$80/barrel). Grasslands and row crop habitats were most affected (2.30 and 2.82% areal vegetation reduction). Our approach improves forecasts of where and to what extent future energy development in unconventional plays may change land-use and ecosystem services, enabling natural resource managers to anticipate and direct on-the-ground conservation actions to places where they will most effectively mitigate ecological impacts of well pads and associated infrastructure.
Capabilities and performance of the new generation ice-sheet model Elmer/Ice

NASA Astrophysics Data System (ADS)

Gagliardini, O.; Zwinger, T.; Durand, G.; Favier, L.; de Fleurian, B.; Gillet-chaulet, F.; Seddik, H.; Greve, R.; Mallinen, M.; Martin, C.; Raback, P.; Ruokolainen, J.; Schäfer, M.; Thies, J.

2012-12-01

Since the Fourth IPCC Assessment Report, and its conclusion about the inability of ice-sheet flow models to forecast the current increase of polar ice sheet discharge and associated contribution to sea-level rise, a huge development effort has been undertaken by the glaciological community. All around the world, models have been improved and, interestingly, a significant number of new ice-sheet models have emerged. Among them, the parallel finite-element model Elmer/Ice (based on the open-source multi-physics code Elmer) was one of the first full-Stokes models used to make projections of the future of the whole Greenland ice sheet for the coming two centuries. Originally developed to solve dedicated local ice flow problems of high mechanical and physical complexity, Elmer/Ice has today reached the maturity to solve larger scale problems, earning the status of an ice-sheet model. In this presentation, we summarise the almost 10 years of development performed by different groups. We present the components already included in Elmer/Ice, its numerical performance, selected applications, as well as developments planed for the future.
Using a dynamical advection to reconstruct a part of the SSH evolution in the context of SWOT, application to the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Rogé, Marine; Morrow, Rosemary; Ubelmann, Clément; Dibarboure, Gérald

2017-08-01

The main oceanographic objective of the future SWOT mission is to better characterize the ocean mesoscale and sub-mesoscale circulation, by observing a finer range of ocean topography dynamics down to 20 km wavelength. Despite the very high spatial resolution of the future satellite, it will not capture the time evolution of the shorter mesoscale signals, such as the formation and evolution of small eddies. SWOT will have an exact repeat cycle of 21 days, with near repeats around 5-10 days, depending on the latitude. Here, we investigate a technique to reconstruct the missing 2D SSH signal in the time between two satellite revisits. We use the dynamical interpolation (DI) technique developed by Ubelmann et al. (2015). Based on potential vorticity (hereafter PV) conservation using a one and a half layer quasi-geostrophic model, it features an active advection of the SSH field. This model has been tested in energetic open ocean regions such as the Gulf Stream and the Californian Current, and has given promising results. Here, we test this model in the Western Mediterranean Sea, a lower energy region with complex small scale physics, and compare the SSH reconstruction with the high-resolution Symphonie model. We investigate an extension of the simple dynamical model including a separated mean circulation. We find that the DI gives a 16-18% improvement in the reconstruction of the surface height and eddy kinetic energy fields, compared with a simple linear interpolation, and a 37% improvement in the Northern Current subregion. Reconstruction errors are higher during winter and autumn but statistically, the improvement from the DI is also better for these seasons.
Mathematical modelling and quantitative methods.

PubMed

Edler, L; Poirier, K; Dourson, M; Kleiner, J; Mileson, B; Nordmann, H; Renwick, A; Slob, W; Walton, K; Würtzen, G

2002-01-01

The present review reports on the mathematical methods and statistical techniques presently available for hazard characterisation. The state of the art of mathematical modelling and quantitative methods used currently for regulatory decision-making in Europe and additional potential methods for risk assessment of chemicals in food and diet are described. Existing practices of JECFA, FDA, EPA, etc., are examined for their similarities and differences. A framework is established for the development of new and improved quantitative methodologies. Areas for refinement, improvement and increase of efficiency of each method are identified in a gap analysis. Based on this critical evaluation, needs for future research are defined. It is concluded from our work that mathematical modelling of the dose-response relationship would improve the risk assessment process. An adequate characterisation of the dose-response relationship by mathematical modelling clearly requires the use of a sufficient number of dose groups to achieve a range of different response levels. This need not necessarily lead to an increase in the total number of animals in the study if an appropriate design is used. Chemical-specific data relating to the mode or mechanism of action and/or the toxicokinetics of the chemical should be used for dose-response characterisation whenever possible. It is concluded that a single method of hazard characterisation would not be suitable for all kinds of risk assessments, and that a range of different approaches is necessary so that the method used is the most appropriate for the data available and for the risk characterisation issue. Future refinements to dose-response characterisation should incorporate more clearly the extent of uncertainty and variability in the resulting output.
Revealing driving factors of China's PM2.5 pollution

NASA Astrophysics Data System (ADS)

Zheng, Y.; Zhao, H.; Zhang, Q.; Geng, G.; Tong, D.; Peng, L.; He, K.

2017-12-01

China's rapid economic development and intensive energy consumption are deteriorating the air quality significantly. Understanding the key driving factors behind China's growing emissions of air pollutants and the accompanying PM2.5 pollution is critical for the development of China's clean air policies and also provides insight into how other emerging economies may develop a clear sky future. Here we reveal the socioeconomic drivers of the variations of China's PM2.5 concentrations during 2002-2012 by using an interdisciplinary framework that integrates an emission inventory model, an index decomposition analysis model, and a regional air quality model. The decomposition results demostrate that the improvements in emission efficiency and energy efficiency failed to offset the increased emissions of both primary PM2.5 and gaseous PM2.5 precursors (including SO2 NOx, and volatile organic compounds) triggered by the surging economic growth during 2002-2012. During the same time, the effects of energy structure, production structure and population growth were relatively less significant to all pollutants, which indicates the potential of large emission abatements through energy structure and production structure adjustment. Sensitivity simulations by the air quality model based on the provincial decomposition results also show that the economic growth have outpaced efficiency improvements in the increments of PM2.5 concentrations during the study years. As China continues to develop rapidly, future policies should promote further improvements in efficiency and accelerate the adjustments toward clean energy and production structures, which are critical for reducing China's emissions and alleviating the severe PM2.5 pollution.
Progress and challenges in coupled hydrodynamic-ecological estuarine modeling.

PubMed

Ganju, Neil K; Brush, Mark J; Rashleigh, Brenda; Aretxabaleta, Alfredo L; Del Barrio, Pilar; Grear, Jason S; Harris, Lora A; Lake, Samuel J; McCardell, Grant; O'Donnell, James; Ralston, David K; Signell, Richard P; Testa, Jeremy M; Vaudrey, Jamie M P

2016-03-01

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear, because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a "theory of everything" for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.
Progress and challenges in coupled hydrodynamic-ecological estuarine modeling

USGS Publications Warehouse

Ganju, Neil K.; Brush, Mark J.; Rashleigh, Brenda; Aretxabaleta, Alfredo L.; del Barrio, Pilar; Grear, Jason S.; Harris, Lora A.; Lake, Samuel J.; McCardell, Grant; O'Donnell, James; Ralston, David K.; Signell, Richard P.; Testa, Jeremy; Vaudrey, Jamie M. P.

2016-01-01

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review, we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.
Progress and challenges in coupled hydrodynamic-ecological estuarine modeling

PubMed Central

Ganju, Neil K.; Brush, Mark J.; Rashleigh, Brenda; Aretxabaleta, Alfredo L.; del Barrio, Pilar; Grear, Jason S.; Harris, Lora A.; Lake, Samuel J.; McCardell, Grant; O’Donnell, James; Ralston, David K.; Signell, Richard P.; Testa, Jeremy M.; Vaudrey, Jamie M.P.

2016-01-01

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear, because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy. PMID:27721675
Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution

PubMed Central

Weiss, Jeremy; Kuusisto, Finn; Boyd, Kendrick; Liu, Jie; Page, David

2015-01-01

Clinical studies model the average treatment effect (ATE), but apply this population-level effect to future individuals. Due to recent developments of machine learning algorithms with useful statistical guarantees, we argue instead for modeling the individualized treatment effect (ITE), which has better applicability to new patients. We compare ATE-estimation using randomized and observational analysis methods against ITE-estimation using machine learning, and describe how the ITE theoretically generalizes to new population distributions, whereas the ATE may not. On a synthetic data set of statin use and myocardial infarction (MI), we show that a learned ITE model improves true ITE estimation and outperforms the ATE. We additionally argue that ITE models should be learned with a consistent, nonparametric algorithm from unweighted examples and show experiments in favor of our argument using our synthetic data model and a real data set of D-penicillamine use for primary biliary cirrhosis. PMID:26958271
Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution.

PubMed

Weiss, Jeremy; Kuusisto, Finn; Boyd, Kendrick; Liu, Jie; Page, David

2015-01-01

Clinical studies model the average treatment effect (ATE), but apply this population-level effect to future individuals. Due to recent developments of machine learning algorithms with useful statistical guarantees, we argue instead for modeling the individualized treatment effect (ITE), which has better applicability to new patients. We compare ATE-estimation using randomized and observational analysis methods against ITE-estimation using machine learning, and describe how the ITE theoretically generalizes to new population distributions, whereas the ATE may not. On a synthetic data set of statin use and myocardial infarction (MI), we show that a learned ITE model improves true ITE estimation and outperforms the ATE. We additionally argue that ITE models should be learned with a consistent, nonparametric algorithm from unweighted examples and show experiments in favor of our argument using our synthetic data model and a real data set of D-penicillamine use for primary biliary cirrhosis.
Assessment of winter wheat loss risk impacted by climate change from 1982 to 2011

NASA Astrophysics Data System (ADS)

Du, Xin

2017-04-01

The world's farmers will face increasing pressure to grow more food on less land in succeeding few decades, because it seems that the continuous population growth and agricultural products turning to biofuels would extend several decades into the future. Therefore, the increased demand for food supply worldwide calls for improved accuracy of crop productivity estimation and assessment of grain production loss risk. Extensive studies have been launched to evaluate the impacts of climate change on crop production based on various crop models drove with global or regional climate model (GCM/RCM) output. However, assessment of climate change impacts on agriculture productivity is plagued with uncertainties of the future climate change scenarios and complexity of crop model. Therefore, given uncertain climate conditions and a lack of model parameters, these methods are strictly limited in application. In this study, an empirical assessment approach for crop loss risk impacted by water stress has been established and used to evaluate the risk of winter wheat loss in China, United States, Germany, France and United Kingdom. The average value of winter wheat loss risk impacted by water stress for the three countries of Europe is about -931kg/ha, which is obviously higher in contrast with that in China (-570kg/ha) and in United States (-367kg/ha). Our study has important implications for further application of operational assessment of crop loss risk at a country or region scale. Future studies should focus on using higher spatial resolution remote sensing data, combining actual evapo-transpiration to estimate water stress, improving the method for downscaling of statistic crop yield data, and establishing much more rational and elaborate zoning method.
Performance of a system of reservoirs on futuristic front

NASA Astrophysics Data System (ADS)

Saha, Satabdi; Roy, Debasri; Mazumdar, Asis

2017-10-01

Application of simulation model HEC-5 to analyze the performance of the DVC Reservoir System (a multipurpose system with a network of five reservoirs and one barrage) on the river Damodar in Eastern India in meeting projected future demand as well as controlling flood for synthetically generated future scenario is addressed here with a view to develop an appropriate strategy for its operation. Thomas-Fiering model (based on Markov autoregressive model) has been adopted for generation of synthetic scenario (monthly streamflow series) and subsequently downscaling of modeled monthly streamflow to daily values was carried out. The performance of the system (analysed on seasonal basis) in terms of `Performance Indices' (viz., both quantity based reliability and time based reliability, mean daily deficit, average failure period, resilience and maximum vulnerability indices) for the projected scenario with enhanced demand turned out to be poor compared to that for historical scenario. However, judicious adoption of resource enhancement (marginal reallocation of reservoir storage capacity) and demand management strategy (curtailment of projected high water requirements and trading off between demands) was found to be a viable option for improvement of the performance of the reservoir system appreciably [improvement being (1-51 %), (2-35 %), (16-96 %), (25-50 %), (8-36 %) and (12-30 %) for the indices viz., quantity based reliability, time based reliability, mean daily deficit, average failure period, resilience and maximum vulnerability, respectively] compared to that with normal storage and projected demand. Again, 100 % reliability for flood control for current as well as future synthetically generated scenarios was noted. The results from the study would assist concerned authority in successful operation of reservoirs in the context of growing demand and dwindling resource.
Integrated modeling of protein-coding genes in the Manduca sexta genome using RNA-Seq data from the biochemical model insect

PubMed Central

Cao, Xiaolong; Jiang, Haobo

2015-01-01

The genome sequence of Manduca sexta was recently determined using 454 technology. Cufflinks and MAKER2 were used to establish gene models in the genome assembly based on the RNA-Seq data and other species' sequences. Aided by the extensive RNA-Seq data from 50 tissue samples at various life stages, annotators over the world (including the present authors) have manually confirmed and improved a small percentage of the models after spending months of effort. While such collaborative efforts are highly commendable, many of the predicted genes still have problems which may hamper future research on this insect species. As a biochemical model representing lepidopteran pests, M. sexta has been used extensively to study insect physiological processes for over five decades. In this work, we assembled Manduca datasets Cufflinks 3.0, Trinity 4.0, and Oases 4.0 to assist the manual annotation efforts and development of Official Gene Set (OGS) 2.0. To further improve annotation quality, we developed methods to evaluate gene models in the MAKER2, Cufflinks, Oases and Trinity assemblies and selected the best ones to constitute MCOT 1.0 after thorough crosschecking. MCOT 1.0 has 18,089 genes encoding 31,666 proteins: 32.8% match OGS 2.0 models perfectly or near perfectly, 11,747 differ considerably, and 29.5% are absent in OGS 2.0. Future automation of this process is anticipated to greatly reduce human efforts in generating comprehensive, reliable models of structural genes in other genome projects where extensive RNA-Seq data are available. PMID:25612938
Business intelligence modeling in launch operations

NASA Astrophysics Data System (ADS)

Bardina, Jorge E.; Thirumalainambi, Rajkumar; Davis, Rodney D.

2005-05-01

The future of business intelligence in space exploration will focus on the intelligent system-of-systems real-time enterprise. In present business intelligence, a number of technologies that are most relevant to space exploration are experiencing the greatest change. Emerging patterns of set of processes rather than organizational units leading to end-to-end automation is becoming a major objective of enterprise information technology. The cost element is a leading factor of future exploration systems. This technology project is to advance an integrated Planning and Management Simulation Model for evaluation of risks, costs, and reliability of launch systems from Earth to Orbit for Space Exploration. The approach builds on research done in the NASA ARC/KSC developed Virtual Test Bed (VTB) to integrate architectural, operations process, and mission simulations for the purpose of evaluating enterprise level strategies to reduce cost, improve systems operability, and reduce mission risks. The objectives are to understand the interdependency of architecture and process on recurring launch cost of operations, provide management a tool for assessing systems safety and dependability versus cost, and leverage lessons learned and empirical models from Shuttle and International Space Station to validate models applied to Exploration. The systems-of-systems concept is built to balance the conflicting objectives of safety, reliability, and process strategy in order to achieve long term sustainability. A planning and analysis test bed is needed for evaluation of enterprise level options and strategies for transit and launch systems as well as surface and orbital systems. This environment can also support agency simulation based acquisition process objectives. The technology development approach is based on the collaborative effort set forth in the VTB's integrating operations, process models, systems and environment models, and cost models as a comprehensive disciplined enterprise analysis environment. Significant emphasis is being placed on adapting root cause from existing Shuttle operations to exploration. Technical challenges include cost model validation, integration of parametric models with discrete event process and systems simulations, and large-scale simulation integration. The enterprise architecture is required for coherent integration of systems models. It will also require a plan for evolution over the life of the program. The proposed technology will produce long-term benefits in support of the NASA objectives for simulation based acquisition, will improve the ability to assess architectural options verses safety/risk for future exploration systems, and will facilitate incorporation of operability as a systems design consideration, reducing overall life cycle cost for future systems.
Business Intelligence Modeling in Launch Operations

NASA Technical Reports Server (NTRS)

Bardina, Jorge E.; Thirumalainambi, Rajkumar; Davis, Rodney D.

2005-01-01

This technology project is to advance an integrated Planning and Management Simulation Model for evaluation of risks, costs, and reliability of launch systems from Earth to Orbit for Space Exploration. The approach builds on research done in the NASA ARC/KSC developed Virtual Test Bed (VTB) to integrate architectural, operations process, and mission simulations for the purpose of evaluating enterprise level strategies to reduce cost, improve systems operability, and reduce mission risks. The objectives are to understand the interdependency of architecture and process on recurring launch cost of operations, provide management a tool for assessing systems safety and dependability versus cost, and leverage lessons learned and empirical models from Shuttle and International Space Station to validate models applied to Exploration. The systems-of-systems concept is built to balance the conflicting objectives of safety, reliability, and process strategy in order to achieve long term sustainability. A planning and analysis test bed is needed for evaluation of enterprise level options and strategies for transit and launch systems as well as surface and orbital systems. This environment can also support agency simulation .based acquisition process objectives. The technology development approach is based on the collaborative effort set forth in the VTB's integrating operations. process models, systems and environment models, and cost models as a comprehensive disciplined enterprise analysis environment. Significant emphasis is being placed on adapting root cause from existing Shuttle operations to exploration. Technical challenges include cost model validation, integration of parametric models with discrete event process and systems simulations. and large-scale simulation integration. The enterprise architecture is required for coherent integration of systems models. It will also require a plan for evolution over the life of the program. The proposed technology will produce long-term benefits in support of the NASA objectives for simulation based acquisition, will improve the ability to assess architectural options verses safety/risk for future exploration systems, and will facilitate incorporation of operability as a systems design consideration, reducing overall life cycle cost for future systems. The future of business intelligence of space exploration will focus on the intelligent system-of-systems real-time enterprise. In present business intelligence, a number of technologies that are most relevant to space exploration are experiencing the greatest change. Emerging patterns of set of processes rather than organizational units leading to end-to-end automation is becoming a major objective of enterprise information technology. The cost element is a leading factor of future exploration systems.
Implication of Agricultural Land Use Change on Regional Climate Projection

NASA Astrophysics Data System (ADS)

Wang, G.; Ahmed, K. F.; You, L.

2015-12-01

Agricultural land use plays an important role in land-atmosphere interaction. Agricultural activity is one of the most important processes driving human-induced land use land cover change (LULCC) in a region. In addition to future socioeconomic changes, climate-induced changes in crop yield represent another important factor shaping agricultural land use. In feedback, the resulting LULCC influences the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. Therefore, assessment of climate change impact on future agricultural land use and its feedback is of great importance in climate change study. In this study, to evaluate the feedback of projected land use changes to the regional climate in West Africa, we employed an asynchronous coupling between a regional climate model (RegCM) and a prototype land use projection model (LandPro). The LandPro model, which was developed to project the future change in agricultural land use and the resulting shift in natural vegetation in West Africa, is a spatially explicit model that can account for both climate and socioeconomic changes in projecting future land use changes. In the asynchronously coupled modeling framework, LandPro was run for every five years during the period of 2005-2050 accounting for climate-induced change in crop yield and socioeconomic changes to project the land use pattern by the mid-21st century. Climate data at 0.5˚ was derived from RegCM to drive the crop model DSSAT for each of the five-year periods to simulate crop yields, which was then provided as input data to LandPro. Subsequently, the land use land cover map required to run RegCM was updated every five years using the outputs from the LandPro simulations. Results from the coupled model simulations improve the understanding of climate change impact on future land use and the resulting feedback to regional climate.
Climate projections and extremes in dynamically downscaled CMIP5 model outputs over the Bengal delta: a quartile based bias-correction approach with new gridded data

NASA Astrophysics Data System (ADS)

Hasan, M. Alfi; Islam, A. K. M. Saiful; Akanda, Ali Shafqat

2017-11-01

In the era of global warning, the insight of future climate and their changing extremes is critical for climate-vulnerable regions of the world. In this study, we have conducted a robust assessment of Regional Climate Model (RCM) results in a monsoon-dominated region within the new Coupled Model Intercomparison Project Phase 5 (CMIP5) and the latest Representative Concentration Pathways (RCP) scenarios. We have applied an advanced bias correction approach to five RCM simulations in order to project future climate and associated extremes over Bangladesh, a critically climate-vulnerable country with a complex monsoon system. We have also generated a new gridded product that performed better in capturing observed climatic extremes than existing products. The bias-correction approach provided a notable improvement in capturing the precipitation extremes as well as mean climate. The majority of projected multi-model RCMs indicate an increase of rainfall, where one model shows contrary results during the 2080s (2071-2100) era. The multi-model mean shows that nighttime temperatures will increase much faster than daytime temperatures and the average annual temperatures are projected to be as hot as present-day summer temperatures. The expected increase of precipitation and temperature over the hilly areas are higher compared to other parts of the country. Overall, the projected extremities of future rainfall are more variable than temperature. According to the majority of the models, the number of the heavy rainy days will increase in future years. The severity of summer-day temperatures will be alarming, especially over hilly regions, where winters are relatively warm. The projected rise of both precipitation and temperature extremes over the intense rainfall-prone northeastern region of the country creates a possibility of devastating flash floods with harmful impacts on agriculture. Moreover, the effect of bias-correction, as presented in probable changes of both bias-corrected and uncorrected extremes, can be considered in future policy making.

Simulating future water temperatures in the North Santiam River, Oregon

NASA Astrophysics Data System (ADS)

Buccola, Norman L.; Risley, John C.; Rounds, Stewart A.

2016-04-01

A previously calibrated two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2) of Detroit Lake in western Oregon was used in conjunction with inflows derived from Precipitation-Runoff Modeling System (PRMS) hydrologic models to examine in-lake and downstream water temperature effects under future climate conditions. Current and hypothetical operations and structures at Detroit Dam were imposed on boundary conditions derived from downscaled General Circulation Models in base (1990-1999) and future (2059-2068) periods. Compared with the base period, future air temperatures were about 2 °C warmer year-round. Higher air temperature and lower precipitation under the future period resulted in a 23% reduction in mean annual PRMS-simulated discharge and a 1 °C increase in mean annual estimated stream temperatures flowing into the lake compared to the base period. Simulations incorporating current operational rules and minimum release rates at Detroit Dam to support downstream habitat, irrigation, and water supply during key times of year resulted in lower future lake levels. That scenario results in a lake level that is above the dam's spillway crest only about half as many days in the future compared to historical frequencies. Managing temperature downstream of Detroit Dam depends on the ability to blend warmer water from the lake's surface with cooler water from deep in the lake, and the spillway is an important release point near the lake's surface. Annual average in-lake and release temperatures from Detroit Lake warmed 1.1 °C and 1.5 °C from base to future periods under present-day dam operational rules and fill schedules. Simulated dam operations such as beginning refill of the lake 30 days earlier or reducing minimum release rates (to keep more water in the lake to retain the use of the spillway) mitigated future warming to 0.4 and 0.9 °C below existing operational scenarios during the critical autumn spawning period for endangered salmonids. A hypothetical floating surface withdrawal at Detroit Dam improved temperature control in summer and autumn (0.6 °C warmer in summer, 0.6 °C cooler in autumn compared to existing structures) without altering release rates or lake level management rules.
An improved predictive functional control method with application to PMSM systems

NASA Astrophysics Data System (ADS)

Li, Shihua; Liu, Huixian; Fu, Wenshu

2017-01-01

In common design of prediction model-based control method, usually disturbances are not considered in the prediction model as well as the control design. For the control systems with large amplitude or strong disturbances, it is difficult to precisely predict the future outputs according to the conventional prediction model, and thus the desired optimal closed-loop performance will be degraded to some extent. To this end, an improved predictive functional control (PFC) method is developed in this paper by embedding disturbance information into the system model. Here, a composite prediction model is thus obtained by embedding the estimated value of disturbances, where disturbance observer (DOB) is employed to estimate the lumped disturbances. So the influence of disturbances on system is taken into account in optimisation procedure. Finally, considering the speed control problem for permanent magnet synchronous motor (PMSM) servo system, a control scheme based on the improved PFC method is designed to ensure an optimal closed-loop performance even in the presence of disturbances. Simulation and experimental results based on a hardware platform are provided to confirm the effectiveness of the proposed algorithm.
Improved Modeling in a Matlab-Based Navigation System

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack; Harman, Rick; Larimore, Wallace E.

1999-01-01

An innovative approach to autonomous navigation is available for low earth orbit satellites. The system is developed in Matlab and utilizes an Extended Kalman Filter (EKF) to estimate the attitude and trajectory based on spacecraft magnetometer and gyro data. Preliminary tests of the system with real spacecraft data from the Rossi X-Ray Timing Explorer Satellite (RXTE) indicate the existence of unmodeled errors in the magnetometer data. Incorporating into the EKF a statistical model that describes the colored component of the effective measurement of the magnetic field vector could improve the accuracy of the trajectory and attitude estimates and also improve the convergence time. This model is identified as a first order Markov process. With the addition of the model, the EKF attempts to identify the non-white components of the noise allowing for more accurate estimation of the original state vector, i.e. the orbital elements and the attitude. Working in Matlab allows for easy incorporation of new models into the EKF and the resulting navigation system is generic and can easily be applied to future missions resulting in an alternative in onboard or ground-based navigation.
An improved empirical dynamic control system model of global mean sea level rise and surface temperature change

NASA Astrophysics Data System (ADS)

Wu, Qing; Luu, Quang-Hung; Tkalich, Pavel; Chen, Ge

2018-04-01

Having great impacts on human lives, global warming and associated sea level rise are believed to be strongly linked to anthropogenic causes. Statistical approach offers a simple and yet conceptually verifiable combination of remotely connected climate variables and indices, including sea level and surface temperature. We propose an improved statistical reconstruction model based on the empirical dynamic control system by taking into account the climate variability and deriving parameters from Monte Carlo cross-validation random experiments. For the historic data from 1880 to 2001, we yielded higher correlation results compared to those from other dynamic empirical models. The averaged root mean square errors are reduced in both reconstructed fields, namely, the global mean surface temperature (by 24-37%) and the global mean sea level (by 5-25%). Our model is also more robust as it notably diminished the unstable problem associated with varying initial values. Such results suggest that the model not only enhances significantly the global mean reconstructions of temperature and sea level but also may have a potential to improve future projections.
Variances in the projections, resulting from CLIMEX, Boosted Regression Trees and Random Forests techniques

NASA Astrophysics Data System (ADS)

Shabani, Farzin; Kumar, Lalit; Solhjouy-fard, Samaneh

2017-08-01

The aim of this study was to have a comparative investigation and evaluation of the capabilities of correlative and mechanistic modeling processes, applied to the projection of future distributions of date palm in novel environments and to establish a method of minimizing uncertainty in the projections of differing techniques. The location of this study on a global scale is in Middle Eastern Countries. We compared the mechanistic model CLIMEX (CL) with the correlative models MaxEnt (MX), Boosted Regression Trees (BRT), and Random Forests (RF) to project current and future distributions of date palm ( Phoenix dactylifera L.). The Global Climate Model (GCM), the CSIRO-Mk3.0 (CS) using the A2 emissions scenario, was selected for making projections. Both indigenous and alien distribution data of the species were utilized in the modeling process. The common areas predicted by MX, BRT, RF, and CL from the CS GCM were extracted and compared to ascertain projection uncertainty levels of each individual technique. The common areas identified by all four modeling techniques were used to produce a map indicating suitable and unsuitable areas for date palm cultivation for Middle Eastern countries, for the present and the year 2100. The four different modeling approaches predict fairly different distributions. Projections from CL were more conservative than from MX. The BRT and RF were the most conservative methods in terms of projections for the current time. The combination of the final CL and MX projections for the present and 2100 provide higher certainty concerning those areas that will become highly suitable for future date palm cultivation. According to the four models, cold, hot, and wet stress, with differences on a regional basis, appears to be the major restrictions on future date palm distribution. The results demonstrate variances in the projections, resulting from different techniques. The assessment and interpretation of model projections requires reservations, especially in correlative models such as MX, BRT, and RF. Intersections between different techniques may decrease uncertainty in future distribution projections. However, readers should not miss the fact that the uncertainties are mostly because the future GHG emission scenarios are unknowable with sufficient precision. Suggestions towards methodology and processing for improving projections are included.
GEOS S2S-2_1: GMAO's New High Resolution Seasonal Prediction System

NASA Technical Reports Server (NTRS)

Molod, Andrea; Akella, Santha; Andrews, Lauren; Barahona, Donifan; Borovikov, Anna; Chang, Yehui; Cullather, Richard; Hackert, Eric; Kovach, Robin; Koster, Randal;

2017-01-01

A new version of the modeling and analysis system used to produce sub-seasonal to seasonal forecasts has just been released by the NASA Goddard Global Modeling and Assimilation Office. The new version runs at higher atmospheric resolution (approximately 12 degree globally), contains a substantially improved model description of the cryosphere, and includes additional interactive earth system model components (aerosol model). In addition, the Ocean data assimilation system has been replaced with a Local Ensemble Transform Kalman Filter. Here will describe the new system, along with the plans for the future (GEOS S2S-3_0) which will include a higher resolution ocean model and more interactive earth system model components (interactive vegetation, biomass burning from fires). We will also present results from a free-running coupled simulation with the new system and results from a series of retrospective seasonal forecasts. Results from retrospective forecasts show significant improvements in surface temperatures over much of the northern hemisphere and a much improved prediction of sea ice extent in both hemispheres. The precipitation forecast skill is comparable to previous S2S systems, and the only trade off is an increased double ITCZ, which is expected as we go to higher atmospheric resolution.

The Local Ensemble Transform Kalman Filter with the Weather Research and Forecasting Model: Experiments with Real Observations

NASA Astrophysics Data System (ADS)

Miyoshi, Takemasa; Kunii, Masaru

2012-03-01

The local ensemble transform Kalman filter (LETKF) is implemented with the Weather Research and Forecasting (WRF) model, and real observations are assimilated to assess the newly-developed WRF-LETKF system. The WRF model is a widely-used mesoscale numerical weather prediction model, and the LETKF is an ensemble Kalman filter (EnKF) algorithm particularly efficient in parallel computer architecture. This study aims to provide the basis of future research on mesoscale data assimilation using the WRF-LETKF system, an additional testbed to the existing EnKF systems with the WRF model used in the previous studies. The particular LETKF system adopted in this study is based on the system initially developed in 2004 and has been continuously improved through theoretical studies and wide applications to many kinds of dynamical models including realistic geophysical models. Most recent and important improvements include an adaptive covariance inflation scheme which considers the spatial and temporal inhomogeneity of inflation parameters. Experiments show that the LETKF successfully assimilates real observations and that adaptive inflation is advantageous. Additional experiments with various ensemble sizes show that using more ensemble members improves the analyses consistently.
Evaluation of advanced geopotential models for operational orbit determination

NASA Technical Reports Server (NTRS)

Radomski, M. S.; Davis, B. E.; Samii, M. V.; Engel, C. J.; Doll, C. E.

1988-01-01

To meet future orbit determination accuracy requirements for different NASA projects, analyses are performed using Tracking and Data Relay Satellite System (TDRSS) tracking measurements and orbit determination improvements in areas such as the modeling of the Earth's gravitational field. Current operational requirements are satisfied using the Goddard Earth Model-9 (GEM-9) geopotential model with the harmonic expansion truncated at order and degree 21 (21-by-21). This study evaluates the performance of 36-by-36 geopotential models, such as the GEM-10B and Preliminary Goddard Solution-3117 (PGS-3117) models. The Earth Radiation Budget Satellite (ERBS) and LANDSAT-5 are the spacecraft considered in this study.
Post-processing of multi-hydrologic model simulations for improved streamflow projections

NASA Astrophysics Data System (ADS)

khajehei, sepideh; Ahmadalipour, Ali; Moradkhani, Hamid

2016-04-01

Hydrologic model outputs are prone to bias and uncertainty due to knowledge deficiency in model and data. Uncertainty in hydroclimatic projections arises due to uncertainty in hydrologic model as well as the epistemic or aleatory uncertainties in GCM parameterization and development. This study is conducted to: 1) evaluate the recently developed multi-variate post-processing method for historical simulations and 2) assess the effect of post-processing on uncertainty and reliability of future streamflow projections in both high-flow and low-flow conditions. The first objective is performed for historical period of 1970-1999. Future streamflow projections are generated for 10 statistically downscaled GCMs from two widely used downscaling methods: Bias Corrected Statistically Downscaled (BCSD) and Multivariate Adaptive Constructed Analogs (MACA), over the period of 2010-2099 for two representative concentration pathways of RCP4.5 and RCP8.5. Three semi-distributed hydrologic models were employed and calibrated at 1/16 degree latitude-longitude resolution for over 100 points across the Columbia River Basin (CRB) in the pacific northwest USA. Streamflow outputs are post-processed through a Bayesian framework based on copula functions. The post-processing approach is relying on a transfer function developed based on bivariate joint distribution between the observation and simulation in historical period. Results show that application of post-processing technique leads to considerably higher accuracy in historical simulations and also reducing model uncertainty in future streamflow projections.
Organ-on-chip models of cancer metastasis for future personalized medicine: From chip to the patient.

PubMed

Caballero, D; Kaushik, S; Correlo, V M; Oliveira, J M; Reis, R L; Kundu, S C

2017-12-01

Most cancer patients do not die from the primary tumor but from its metastasis. Current in vitro and in vivo cancer models are incapable of satisfactorily predicting the outcome of various clinical treatments on patients. This is seen as a serious limitation and efforts are underway to develop a new generation of highly predictive cancer models with advanced capabilities. In this regard, organ-on-chip models of cancer metastasis emerge as powerful predictors of disease progression. They offer physiological-like conditions where the (hypothesized) mechanistic determinants of the disease can be assessed with ease. Combined with high-throughput characteristics, the employment of organ-on-chip technology would allow pharmaceutical companies and clinicians to test new therapeutic compounds and therapies. This will permit the screening of a large battery of new drugs in a fast and economic manner, to accelerate the diagnosis of the disease in the near future, and to test personalized treatments using cells from patients. In this review, we describe the latest advances in the field of organ-on-chip models of cancer metastasis and their integration with advanced imaging, screening and biosensing technologies for future precision medicine applications. We focus on their clinical applicability and market opportunities to drive us forward to the next generation of tumor models for improved cancer patient theranostics. Copyright © 2017 Elsevier Ltd. All rights reserved.
Life expectancy living with HIV: recent estimates and future implications.

PubMed

Nakagawa, Fumiyo; May, Margaret; Phillips, Andrew

2013-02-01

The life expectancy of people living with HIV has dramatically increased since effective antiretroviral therapy has been available, and still continues to improve. Here, we review the latest literature on estimates of life expectancy and consider the implications for future research. With timely diagnosis, access to a variety of current drugs and good lifelong adherence, people with recently acquired infections can expect to have a life expectancy which is nearly the same as that of HIV-negative individuals. Modelling studies suggest that life expectancy could improve further if there were increased uptake of HIV testing, better antiretroviral regimens and treatment strategies, and the adoption of healthier lifestyles by those living with HIV. In particular, earlier diagnosis is one of the most important factors associated with better life expectancy. A consequence of improved survival is the increasing number of people with HIV who are aged over 50 years old, and further research into the impact of ageing on HIV-positive people will therefore become crucial. The development of age-specific HIV treatment and management guidelines is now called for. Analyses on cohort studies and mathematical modelling studies have been used to estimate life expectancy of those with HIV, providing useful insights of importance to individuals and healthcare planning.
Causes and Implications of Persistent Atmospheric Carbon Dioxide Biases in Earth System Models

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

Hoffman, Forrest M; Randerson, James T.; Arora, Vivek K.

The strength of feedbacks between a changing climate and future CO2 concentrations are uncertain and difficult to predict using Earth System Models (ESMs). We analyzed emission-driven simulations--in which atmospheric CO2 levels were computed prognostically--for historical (1850-2005) and future periods (RCP 8.5 for 2006-2100) produced by 15 ESMs for the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). Comparison of ESM prognostic atmospheric CO2 over the historical period with observations indicated that ESMs, on average, had a small positive bias in predictions of contemporary atmospheric CO2. Weak ocean carbon uptake in many ESMs contributed to this bias, based on comparisonsmore » with observations of ocean and atmospheric anthropogenic carbon inventories. We found a significant linear relationship between contemporary atmospheric CO2 biases and future CO2 levels for the multi-model ensemble. We used this relationship to create a contemporary CO2 tuned model (CCTM) estimate of the atmospheric CO2 trajectory for the 21st century. The CCTM yielded CO2 estimates of 600 {plus minus} 14 ppm at 2060 and 947 {plus minus} 35 ppm at 2100, which were 21 ppm and 32 ppm below the multi-model mean during these two time periods. Using this emergent constraint approach, the likely ranges of future atmospheric CO2, CO2-induced radiative forcing, and CO2-induced temperature increases for the RCP 8.5 scenario were considerably narrowed compared to estimates from the full ESM ensemble. Our analysis provided evidence that much of the model-to-model variation in projected CO2 during the 21st century was tied to biases that existed during the observational era, and that model differences in the representation of concentration-carbon feedbacks and other slowly changing carbon cycle processes appear to be the primary driver of this variability. By improving models to more closely match the long-term time series of CO2 from Mauna Loa, our analysis suggests uncertainties in future climate projections can be reduced.« less
Radioactive threat detection using scintillant-based detectors

NASA Astrophysics Data System (ADS)

Chalmers, Alex

2004-09-01

An update to the performance of AS&E's Radioactive Threat Detection sensor technology. A model is presented detailing the components of the scintillant-based RTD system employed in AS&E products aimed at detecting radiological WMD. An overview of recent improvements in the sensors, electrical subsystems and software algorithms are presented. The resulting improvements in performance are described and sample results shown from existing systems. Advanced and future capabilities are described with an assessment of their feasibility and their application to Homeland Defense.
[The growing importance of ethics in medical care and research].

PubMed

Sass, Hans-Martin

2009-01-01

The integration of medical humanities into future patient care and medical research will become as importance for trust, care and health as the natural sciences were during the last 100 years. In particular, improvements of lay health literacy and responsibility, new forms of physician-nurse partnership and expert-lay interaction, also revisions of clinical research towards models of informed contract will improve trust and health on a global scale, allow for healthier and happier citizens and populations and eventually might reduce health care costs.
Duct flow nonuniformities study for space shuttle main engine

NASA Technical Reports Server (NTRS)

Thoenes, J.

1985-01-01

To improve the Space Shuttle Main Engine (SSME) design and for future use in the development of generation rocket engines, a combined experimental/analytical study was undertaken with the goals of first, establishing an experimental data base for the flow conditions in the SSME high pressure fuel turbopump (HPFTP) hot gas manifold (HGM) and, second, setting up a computer model of the SSME HGM flow field. Using the test data to verify the computer model it should be possible in the future to computationally scan contemplated advanced design configurations and limit costly testing to the most promising design. The effort of establishing and using the computer model is detailed. The comparison of computational results and experimental data observed clearly demonstrate that computational fluid mechanics (CFD) techniques can be used successfully to predict the gross features of three dimensional fluid flow through configurations as intricate as the SSME turbopump hot gas manifold.
Positive psychological determinants of treatment adherence among primary care patients.

PubMed

Nsamenang, Sheri A; Hirsch, Jameson K

2015-07-01

Patient adherence to medical treatment recommendations can affect disease prognosis, and may be beneficially or deleteriously influenced by psychological factors. Aim We examined the relationships between both adaptive and maladaptive psychological factors and treatment adherence among a sample of primary care patients. One hundred and one rural, primary care patients completed the Life Orientation Test-Revised, Trait Hope Scale, Future Orientation Scale, NEO-FFI Personality Inventory (measuring positive and negative affect), and Medical Outcomes Study General Adherence Scale. In independent models, positive affect, optimism, hope, and future orientation were beneficially associated with treatment adherence, whereas pessimism and negative affect were negatively related to adherence. In multivariate models, only negative affect, optimism and hope remained significant and, in a comparative model, trait hope was most robustly associated with treatment adherence. Therapeutically, addressing negative emotions and expectancies, while simultaneously bolstering motivational and goal-directed attributes, may improve adherence to treatment regimens.
Effects of engine emissions from high-speed civil transport aircraft: A two-dimensional modeling study, part 1

NASA Technical Reports Server (NTRS)

Ko, Malcolm K. W.; Weisenstein, Debra K.; Sze, Nein Dak; Rodriguez, Jose M.; Heisey, Curtis

1991-01-01

The AER two-dimensional chemistry-transport model is used to study the effect on stratospheric ozone (O3) from operations of supersonic and subsonic aircraft. The study is based on six emission scenarios provided to AER. The study showed that: (1) the O3 response is dominated by the portion of the emitted nitrogen compounds that is entrained in the stratosphere; (2) the entrainment is a sensitive function of the altitude at which the material is injected; (3) the O3 removal efficiency of the emitted material depends on the concentrations of trace gases in the background atmosphere; and (4) evaluation of the impact of fleet operations in the future atmosphere must take into account the expected changes in trace gas concentrations from other activities. Areas for model improvements in future studies are also discussed.
Different models to mobilize peer support to improve diabetes self-management and clinical outcomes: evidence, logistics, evaluation considerations and needs for future research.

PubMed

Heisler, Michele

2010-06-01

Much of diabetes care needs to be carried out by patients between office visits with their health care providers. Yet, many patients face difficulties carrying out these tasks. In addition, many adults with diabetes cannot count on effective support from their families and friends to help them with their self-management. Peer support programmes are a promising approach to enhance social and emotional support, assist patients in daily management and living with diabetes and promote linkages to clinical care. This background paper provides a brief overview of different approaches to mobilize peer support for diabetes self-management support, discusses evidence to date on the effectiveness of each of these models, highlights logistical and evaluation issues for each model and concludes with a discussion of directions for future research in this area.
Different models to mobilize peer support to improve diabetes self-management and clinical outcomes: evidence, logistics, evaluation considerations and needs for future research

PubMed Central

2010-01-01

Much of diabetes care needs to be carried out by patients between office visits with their health care providers. Yet, many patients face difficulties carrying out these tasks. In addition, many adults with diabetes cannot count on effective support from their families and friends to help them with their self-management. Peer support programmes are a promising approach to enhance social and emotional support, assist patients in daily management and living with diabetes and promote linkages to clinical care. This background paper provides a brief overview of different approaches to mobilize peer support for diabetes self-management support, discusses evidence to date on the effectiveness of each of these models, highlights logistical and evaluation issues for each model and concludes with a discussion of directions for future research in this area. PMID:19293400
Future WGCEP Models and the Need for Earthquake Simulators

NASA Astrophysics Data System (ADS)

Field, E. H.

2008-12-01

The 2008 Working Group on California Earthquake Probabilities (WGCEP) recently released the Uniform California Earthquake Rupture Forecast version 2 (UCERF 2), developed jointly by the USGS, CGS, and SCEC with significant support from the California Earthquake Authority. Although this model embodies several significant improvements over previous WGCEPs, the following are some of the significant shortcomings that we hope to resolve in a future UCERF3: 1) assumptions of fault segmentation and the lack of fault-to-fault ruptures; 2) the lack of an internally consistent methodology for computing time-dependent, elastic-rebound-motivated renewal probabilities; 3) the lack of earthquake clustering/triggering effects; and 4) unwarranted model complexity. It is believed by some that physics-based earthquake simulators will be key to resolving these issues, either as exploratory tools to help guide the present statistical approaches, or as a means to forecast earthquakes directly (although significant challenges remain with respect to the latter).

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