Optimal observation network design for conceptual model discrimination and uncertainty reduction

NASA Astrophysics Data System (ADS)

Pham, Hai V.; Tsai, Frank T.-C.

2016-02-01

This study expands the Box-Hill discrimination function to design an optimal observation network to discriminate conceptual models and, in turn, identify a most favored model. The Box-Hill discrimination function measures the expected decrease in Shannon entropy (for model identification) before and after the optimal design for one additional observation. This study modifies the discrimination function to account for multiple future observations that are assumed spatiotemporally independent and Gaussian-distributed. Bayesian model averaging (BMA) is used to incorporate existing observation data and quantify future observation uncertainty arising from conceptual and parametric uncertainties in the discrimination function. In addition, the BMA method is adopted to predict future observation data in a statistical sense. The design goal is to find optimal locations and least data via maximizing the Box-Hill discrimination function value subject to a posterior model probability threshold. The optimal observation network design is illustrated using a groundwater study in Baton Rouge, Louisiana, to collect additional groundwater heads from USGS wells. The sources of uncertainty creating multiple groundwater models are geological architecture, boundary condition, and fault permeability architecture. Impacts of considering homoscedastic and heteroscedastic future observation data and the sources of uncertainties on potential observation areas are analyzed. Results show that heteroscedasticity should be considered in the design procedure to account for various sources of future observation uncertainty. After the optimal design is obtained and the corresponding data are collected for model updating, total variances of head predictions can be significantly reduced by identifying a model with a superior posterior model probability.

Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections

NASA Astrophysics Data System (ADS)

Aryal, Anil; Shrestha, Sangam; Babel, Mukand S.

2018-01-01

The objective of this paper is to quantify the various sources of uncertainty in the assessment of climate change impact on hydrology in the Tamakoshi River Basin, located in the north-eastern part of Nepal. Multiple climate and hydrological models were used to simulate future climate conditions and discharge in the basin. The simulated results of future climate and river discharge were analysed for the quantification of sources of uncertainty using two-way and three-way ANOVA. The results showed that temperature and precipitation in the study area are projected to change in near- (2010-2039), mid- (2040-2069) and far-future (2070-2099) periods. Maximum temperature is likely to rise by 1.75 °C under Representative Concentration Pathway (RCP) 4.5 and by 3.52 °C under RCP 8.5. Similarly, the minimum temperature is expected to rise by 2.10 °C under RCP 4.5 and by 3.73 °C under RCP 8.5 by the end of the twenty-first century. Similarly, the precipitation in the study area is expected to change by - 2.15% under RCP 4.5 and - 2.44% under RCP 8.5 scenarios. The future discharge in the study area was projected using two hydrological models, viz. Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's Hydrologic Modelling System (HEC-HMS). The SWAT model projected discharge is expected to change by small amount, whereas HEC-HMS model projected considerably lower discharge in future compared to the baseline period. The results also show that future climate variables and river hydrology contain uncertainty due to the choice of climate models, RCP scenarios, bias correction methods and hydrological models. During wet days, more uncertainty is observed due to the use of different climate models, whereas during dry days, the use of different hydrological models has a greater effect on uncertainty. Inter-comparison of the impacts of different climate models reveals that the REMO climate model shows higher uncertainty in the prediction of precipitation and, consequently, in the prediction of future discharge and maximum probable flood.

The uncertainty cascade in flood risk assessment under changing climatic conditions - the Biala Tarnowska case study

NASA Astrophysics Data System (ADS)

Doroszkiewicz, Joanna; Romanowicz, Renata

2016-04-01

Uncertainty in the results of the hydraulic model is not only associated with the limitations of that model and the shortcomings of data. An important factor that has a major impact on the uncertainty of the flood risk assessment in a changing climate conditions is associated with the uncertainty of future climate scenarios (IPCC WG I, 2013). Future climate projections provided by global climate models are used to generate future runoff required as an input to hydraulic models applied in the derivation of flood risk maps. Biala Tarnowska catchment, situated in southern Poland is used as a case study. Future discharges at the input to a hydraulic model are obtained using the HBV model and climate projections obtained from the EUROCORDEX project. The study describes a cascade of uncertainty related to different stages of the process of derivation of flood risk maps under changing climate conditions. In this context it takes into account the uncertainty of future climate projections, an uncertainty of flow routing model, the propagation of that uncertainty through the hydraulic model, and finally, the uncertainty related to the derivation of flood risk maps. One of the aims of this study is an assessment of a relative impact of different sources of uncertainty on the uncertainty of flood risk maps. Due to the complexity of the process, an assessment of total uncertainty of maps of inundation probability might be very computer time consuming. As a way forward we present an application of a hydraulic model simulator based on a nonlinear transfer function model for the chosen locations along the river reach. The transfer function model parameters are estimated based on the simulations of the hydraulic model at each of the model cross-section. The study shows that the application of the simulator substantially reduces the computer requirements related to the derivation of flood risk maps under future climatic conditions. Acknowledgements: This work was supported by the project CHIHE (Climate Change Impact on Hydrological Extremes), carried out in the Institute of Geophysics Polish Academy of Sciences, funded by Norway Grants (contract No. Pol-Nor/196243/80/2013). The hydro-meteorological observations were provided by the Institute of Meteorology and Water Management (IMGW), Poland.

Development of Structural Components of Future Technicians' Professional Competencies during Their Studies of General Disciplines in College

ERIC Educational Resources Information Center

Kopilov, Sergey N.; Dorozhkin, Evgenij M.; Tarasyuk, Olga V.; Osipova, Irina V.; Lazareva, Natalia V.

2016-01-01

The relevance of the problem stems from the necessity to develop and implement the formation model for structural components of future technicians' professional competencies during their studies of general professional disciplines. The purpose of the article is to carry out a theoretical study, to develop and approbate a model that forms the…

The importance of considering shifts in seasonal changes in discharges when predicting future phosphorus loads in streams

USGS Publications Warehouse

LaBeau, Meredith B.; Mayer, Alex S.; Griffis, Veronica; Watkins, David Jr.; Robertson, Dale M.; Gyawali, Rabi

2015-01-01

In this work, we hypothesize that phosphorus (P) concentrations in streams vary seasonally and with streamflow and that it is important to incorporate this variation when predicting changes in P loading associated with climate change. Our study area includes 14 watersheds with a range of land uses throughout the U.S. Great Lakes Basin. We develop annual seasonal load-discharge regression models for each watershed and apply these models with simulated discharges generated for future climate scenarios to simulate future P loading patterns for two periods: 2046–2065 and 2081–2100. We utilize output from the Coupled Model Intercomparison Project phase 3 downscaled climate change projections that are input into the Large Basin Runoff Model to generate future discharge scenarios, which are in turn used as inputs to the seasonal P load regression models. In almost all cases, the seasonal load-discharge models match observed loads better than the annual models. Results using the seasonal models show that the concurrence of nonlinearity in the load-discharge model and changes in high discharges in the spring months leads to the most significant changes in P loading for selected tributaries under future climate projections. These results emphasize the importance of using seasonal models to understand the effects of future climate change on nutrient loads.

Projecting future grassland productivity to assess thesustainability of potential biofuel feedstock areas in theGreater Platte River Basin

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.; Boyte, Stephen; Phuyal, Khem P.

2014-01-01

This study projects future (e.g., 2050 and 2099) grassland productivities in the Greater Platte River Basin (GPRB) using ecosystem performance (EP, a surrogate for measuring ecosystem productivity) models and future climate projections. The EP models developed from a previous study were based on the satellite vegetation index, site geophysical and biophysical features, and weather and climate drivers. The future climate data used in this study were derived from the National Center for Atmospheric Research Community Climate System Model 3.0 ‘SRES A1B’ (a ‘middle’ emissions path). The main objective of this study is to assess the future sustainability of the potential biofuel feedstock areas identified in a previous study. Results show that the potential biofuel feedstock areas (the more mesic eastern part of the GPRB) will remain productive (i.e., aboveground grassland biomass productivity >2750 kg ha−1 year−1) with a slight increasing trend in the future. The spatially averaged EPs for these areas are 3519, 3432, 3557, 3605, 3752, and 3583 kg ha−1 year−1 for current site potential (2000–2008 average), 2020, 2030, 2040, 2050, and 2099, respectively. Therefore, the identified potential biofuel feedstock areas will likely continue to be sustainable for future biofuel development. On the other hand, grasslands identified as having no biofuel potential in the drier western part of the GPRB would be expected to stay unproductive in the future (spatially averaged EPs are 1822, 1691, 1896, 2306, 1994, and 2169 kg ha−1 year−1 for site potential, 2020, 2030, 2040, 2050, and 2099). These areas should continue to be unsuitable for biofuel feedstock development in the future. These future grassland productivity estimation maps can help land managers to understand and adapt to the expected changes in future EP in the GPRB and to assess the future sustainability and feasibility of potential biofuel feedstock areas.

I think of Ronald Reagan: future selves in the present.

PubMed

Roberts, P

1992-01-01

A nonlinear perspective on time (where the future exists in and affects the present) has been described by several theorists but there is little research on the extent, quality or origins of the personal future perspective. The present study examined the existence and origin of the future in the present by asking adults aged nineteen to eighty-three to: 1) project themselves into the oldest age imaginable, 2) describe their hopes and fears for that age, and 3) name role models for those hopes and fears. Data analysis revealed that length of future perspective, number of hopes and number of role models for the distant future declined with age. In addition, types of fears for the future varied with age, with older adults stressing dependency issues while younger adults reported concerns about personality and mental health. Despite age differences, most participants could name role models for both their hopes and fears for aging, but specific models were identified more often for hopes than for fears. Personalized hopes and fears for the distant future as motivators for the present are discussed.

Beyond speculative robot ethics: a vision assessment study on the future of the robotic caretaker.

PubMed

van der Plas, Arjanna; Smits, Martijntje; Wehrmann, Caroline

2010-11-01

In this article we develop a dialogue model for robot technology experts and designated users to discuss visions on the future of robotics in long-term care. Our vision assessment study aims for more distinguished and more informed visions on future robots. Surprisingly, our experiment also led to some promising co-designed robot concepts in which jointly articulated moral guidelines are embedded. With our model, we think to have designed an interesting response on a recent call for a less speculative ethics of technology by encouraging discussions about the quality of positive and negative visions on the future of robotics.

Motivational Antecedents of Preventive Proactivity in Late Life: Linking Future Orientation and Exercise1

PubMed Central

Kahana, Eva; Kahana, Boaz; Zhang, Jianping

2007-01-01

Future orientation is considered as a motivational antecedent of late-life proactivity. In a panel study of 453 old-old adults, we linked future orientation to exercise, a key component of late-life proactivity. Findings based on hierarchical linear modeling reveal that future orientation at baseline predicts changes in exercise during the subsequent four years. Whereas exercise behavior generally declined over time, future orientation and female gender were associated with smaller decline. These results suggest that future-oriented thinking has a lasting impact on health promotion behavior. Future orientation thus represents a dispositional antecedent of preventive proactivity as proposed in our successful aging model. PMID:18080009

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.

Assessment of impacts of climate change on surface water availability using coupled SWAT and WEAP models: case of upper Pangani River Basin, Tanzania

NASA Astrophysics Data System (ADS)

Kishiwa, Peter; Nobert, Joel; Kongo, Victor; Ndomba, Preksedis

2018-05-01

This study was designed to investigate the dynamics of current and future surface water availability for different water users in the upper Pangani River Basin under changing climate. A multi-tier modeling technique was used in the study, by coupling the Soil and Water Assessment Tool (SWAT) and Water Evaluation And Planning (WEAP) models, to simulate streamflows under climate change and assess scenarios of future water availability to different socio-economic activities by year 2060. Six common Global Circulation Models (GCMs) from WCRP-CMIP3 with emissions Scenario A2 were selected. These are HadCM3, HadGEM1, ECHAM5, MIROC3.2MED, GFDLCM2.1 and CSIROMK3. They were downscaled by using LARS-WG to station scale. The SWAT model was calibrated with observed data and utilized the LARS-WG outputs to generate future streamflows before being used as input to WEAP model to assess future water availability to different socio-economic activities. GCMs results show future rainfall increase in upper Pangani River Basin between 16-18 % in 2050s relative to 1980-1999 periods. Temperature is projected to increase by an average of 2 °C in 2050s, relative to baseline period. Long-term mean streamflows is expected to increase by approximately 10 %. However, future peak flows are estimated to be lower than the prevailing average peak flows. Nevertheless, the overall annual water demand in Pangani basin will increase from 1879.73 Mm3 at present (2011) to 3249.69 Mm3 in the future (2060s), resulting to unmet demand of 1673.8 Mm3 (51.5 %). The impact of future shortage will be more severe in irrigation where 71.12 % of its future demand will be unmet. Future water demands of Hydropower and Livestock will be unmet by 27.47 and 1.41 % respectively. However, future domestic water use will have no shortage. This calls for planning of current and future surface water use in the upper Pangani River Basin.

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.

A Model for Preservice Teachers' Intentions to Use ICT in Future Lessons

ERIC Educational Resources Information Center

Baydas, Ozlem; Goktas, Yuksel

2017-01-01

This study proposes a model for determining preservice teachers' intentions to use information and communication technology (ICT) in future lessons. Data were collected from 21 preservice teachers via interview in the first stage of the study and from 2904 preservice teachers from 16 different universities via a designed scale in the second stage…

Partitioning uncertainty in streamflow projections under nonstationary model conditions

NASA Astrophysics Data System (ADS)

Chawla, Ila; Mujumdar, P. P.

2018-02-01

Assessing the impacts of Land Use (LU) and climate change on future streamflow projections is necessary for efficient management of water resources. However, model projections are burdened with significant uncertainty arising from various sources. Most of the previous studies have considered climate models and scenarios as major sources of uncertainty, but uncertainties introduced by land use change and hydrologic model assumptions are rarely investigated. In this paper an attempt is made to segregate the contribution from (i) general circulation models (GCMs), (ii) emission scenarios, (iii) land use scenarios, (iv) stationarity assumption of the hydrologic model, and (v) internal variability of the processes, to overall uncertainty in streamflow projections using analysis of variance (ANOVA) approach. Generally, most of the impact assessment studies are carried out with unchanging hydrologic model parameters in future. It is, however, necessary to address the nonstationarity in model parameters with changing land use and climate. In this paper, a regression based methodology is presented to obtain the hydrologic model parameters with changing land use and climate scenarios in future. The Upper Ganga Basin (UGB) in India is used as a case study to demonstrate the methodology. The semi-distributed Variable Infiltration Capacity (VIC) model is set-up over the basin, under nonstationary conditions. Results indicate that model parameters vary with time, thereby invalidating the often-used assumption of model stationarity. The streamflow in UGB under the nonstationary model condition is found to reduce in future. The flows are also found to be sensitive to changes in land use. Segregation results suggest that model stationarity assumption and GCMs along with their interactions with emission scenarios, act as dominant sources of uncertainty. This paper provides a generalized framework for hydrologists to examine stationarity assumption of models before considering them for future streamflow projections and segregate the contribution of various sources to the uncertainty.

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

NASA Astrophysics Data System (ADS)

Prasanna, V.

2018-01-01

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

Loneliness and Suicidal Risk in Young Adults: Does Believing in a Changeable Future Help Minimize Suicidal Risk Among the Lonely?

PubMed

Chang, Edward C; Wan, Liangqiu; Li, Pengzi; Guo, Yuncheng; He, Jiaying; Gu, Yu; Wang, Yingjie; Li, Xiaoqing; Zhang, Zhan; Sun, Yingrui; Batterbee, Casey N-H; Chang, Olivia D; Lucas, Abigael G; Hirsch, Jameson K

2017-07-04

This study examined loneliness and future orientation as predictors of suicidal risk, namely, depressive symptoms and suicide ideation, in a sample of 228 college students (54 males and 174 females). Results of regression analyses indicated that loneliness was a significant predictor of both indices of suicidal risk. The inclusion of future orientation was found to significantly augment the prediction model of both depressive symptoms and suicide ideation, even after accounting for loneliness. Noteworthy, beyond loneliness and future orientation, the Loneliness × Future Orientation interaction term was found to further augment both prediction models of suicidal risk. Consistent with the notion that future orientation is an important buffer of suicidal risk, among lonely students, those with high future orientation, compared to low future orientation, were found to report significantly lower levels of depressive symptoms and suicide ideation. Some implications of the present findings for studying both risk and protective factors associated with suicidal risk in young adults are discussed.

Application of Temperature Index Model to Assess the Future Hydrological Regime of the Glacierized Catchments in Nepal.

NASA Astrophysics Data System (ADS)

Kayastha, R.; Kayastha, R. B.

2017-12-01

Unavailability of hydro meteorological data in the Himalayan regions is challenging on understanding the flow regimes. Temperature index model is simple yet the powerful glacio-hydrological model to simulate the discharge in the glacierized basin. Modified Positive Degree Day (MPDD) Model Version 2.0 is a grid-ded based semi distributed model with baseflow module is a robust melt modelling tools to estimate the discharge. MPDD model uses temperature and precipitation as a forcing datasets to simulate the discharge and also to obtain the snowmelt, icemelt, rain and baseflow contribution on total discharge. In this study two glacierized, Marsyangdi and Langtang catchment were investigated for the future hydrological regimes. Marsyangdi encompasses an area of 4026.19 sq. km with 20% glaciated area, whereas Langtang catchment with area of 354.64 sq. km with 36% glaciated area is studied to examine for the future climatic scenarios. The model simulates discharge well for the observed period; (1992-1998) in Marsyangdi and from (2007-2013) in Langtang catchment. The Nash-Sutcliffe Efficiency (NSE) for the both catchment were above 0.75 with the volume difference less than - 8 %. The snow and ice melts contribution in Marsyangdi were 4.7% and 10.2% whereas in Langtang the contribution is 15.3% and 23.4%, respectively. Rain contribution ( 40%) is higher than the baseflow contribution in total discharge in both basins. The future river discharge is also predicted using the future climate data from the regional climate models (RCMs) of CORDEX South Asia experiments for the medium stabilization scenario RCP4.5 and very high radiative forcing scenario RCP8.5 after bias correction. The projected future discharge of both catchment shows slightly increase in both scenarios with increase of snow and ice melt contribution on discharge. The result generated from the model can be utilized to understand the future hydrological regimes of the glacierized catchment also the impact of climate change on the snow and ice contribution on discharge. The future discharge projection is also helpful for the water resource management and also for the strategic planners.

Impacts of future climate change on river discharge based on hydrological inference: A case study of the Grand River Watershed in Ontario, Canada.

PubMed

Li, Zhong; Huang, Guohe; Wang, Xiuquan; Han, Jingcheng; Fan, Yurui

2016-04-01

Over the recent years, climate change impacts have been increasingly studied at the watershed scale. However, the impact assessment is strongly dependent upon the performance of the climatic and hydrological models. This study developed a two-step method to assess climate change impacts on water resources based on the Providing Regional Climates for Impacts Studies (PRECIS) modeling system and a Hydrological Inference Model (HIM). PRECIS runs provided future temperature and precipitation projections for the watershed under the Intergovernmental Panel on Climate Change SRES A2 and B2 emission scenarios. The HIM based on stepwise cluster analysis is developed to imitate the complex nonlinear relationships between climate input variables and targeted hydrological variables. Its robust mathematical structure and flexibility in predictor selection makes it a desirable tool for fully utilizing various climate modeling outputs. Although PRECIS and HIM cannot fully cover the uncertainties in hydro-climate modeling, they could provide efficient decision support for investigating the impacts of climate change on water resources. The proposed method is applied to the Grand River Watershed in Ontario, Canada. The model performance is demonstrated with comparison to observation data from the watershed during the period 1972-2006. Future river discharge intervals that accommodate uncertainties in hydro-climatic modeling are presented and future river discharge variations are analyzed. The results indicate that even though the total annual precipitation would not change significantly in the future, the inter-annual distribution is very likely to be altered. The water availability is expected to increase in Winter while it is very likely to decrease in Summer over the Grand River Watershed, and adaptation strategies would be necessary. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimation of future outflows of e-waste in India.

PubMed

Dwivedy, Maheshwar; Mittal, R K

2010-03-01

The purpose of this study is to construct an approach and a methodology to estimate the future outflows of electronic waste (e-waste) in India. Consequently, the study utilizes a time-series multiple lifespan end-of-life model proposed by Peralta and Fontanos for estimating the current and future quantities of e-waste in India. The model estimates future e-waste generation quantities by modeling their usage and disposal. The present work considers two scenarios for the approximation of e-waste generation based on user preferences to store or to recycle the e-waste. This model will help formal recyclers in India to make strategic decisions in planning for appropriate recycling infrastructure and institutional capacity building. Also an extension of the model proposed by Peralta and Fontanos is developed with the objective of helping decision makers to conduct WEEE estimates under a variety of assumptions to suit their region of study. During 2007-2011, the total WEEE estimates will be around 2.5 million metric tons which include waste from personal computers (PC), television, refrigerators and washing machines. During the said period, the waste from PC will account for 30% of total units of WEEE generated. Copyright 2009 Elsevier Ltd. All rights reserved.

Estimation of future outflows of e-waste in India

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

Dwivedy, Maheshwar, E-mail: dwivedy_m@bits-pilani.ac.i; Mittal, R.K.

2010-03-15

The purpose of this study is to construct an approach and a methodology to estimate the future outflows of electronic waste (e-waste) in India. Consequently, the study utilizes a time-series multiple lifespan end-of-life model proposed by Peralta and Fontanos for estimating the current and future quantities of e-waste in India. The model estimates future e-waste generation quantities by modeling their usage and disposal. The present work considers two scenarios for the approximation of e-waste generation based on user preferences to store or to recycle the e-waste. This model will help formal recyclers in India to make strategic decisions in planningmore » for appropriate recycling infrastructure and institutional capacity building. Also an extension of the model proposed by Peralta and Fontanos is developed with the objective of helping decision makers to conduct WEEE estimates under a variety of assumptions to suit their region of study. During 2007-2011, the total WEEE estimates will be around 2.5 million metric tons which include waste from personal computers (PC), television, refrigerators and washing machines. During the said period, the waste from PC will account for 30% of total units of WEEE generated.« less

Changes of glaciers in the Andes of Chile and priorities for future work.

PubMed

Pellicciotti, F; Ragettli, S; Carenzo, M; McPhee, J

2014-09-15

Glaciers in the Andes of Chile seem to be shrinking and possibly loosing mass, but the number and types of studies conducted, constrained mainly by data availability, are not sufficient to provide a synopsis of glacier changes for the past or future or explain in an explicit way causes of the observed changes. In this paper, we provide a systematic review of changes in glaciers for the entire country, followed by a discussion of the studies that have provided evidence of such changes. We identify a missing type of work in distributed, physically-oriented modelling studies that are needed to bridge the gap between the numerous remote sensing studies and the specific, point scale works focused on process understanding. We use an advanced mass balance model applied to one of the best monitored glaciers in the region to investigate four main research issues that should be addressed in modelling studies for a sound assessment of glacier changes: 1) the use of physically-based models of glacier ablation (energy balance models) versus more empirical models (enhanced temperature index approaches); 2) the importance of the correct extrapolation of air temperature forcing on glaciers and in high elevation areas and the large uncertainty in model outputs associated with it; 3) the role played by snow gravitational redistribution; and 4) the uncertainty associated with future climate scenarios. We quantify differences in model outputs associated with each of these choices, and conclude with suggestions for future work directions. © 2013 Elsevier B.V. All rights reserved.

Modeling Pathways of Character Development across the First Three Decades of Life: An Application of Integrative Data Analysis Techniques to Understanding the Development of Hopeful Future Expectations.

PubMed

Callina, Kristina Schmid; Johnson, Sara K; Tirrell, Jonathan M; Batanova, Milena; Weiner, Michelle B; Lerner, Richard M

2017-06-01

There were two purposes of the present research: first, to add to scholarship about a key character virtue, hopeful future expectations; and second, to demonstrate a recent innovation in longitudinal methodology that may be especially useful in enhancing the understanding of the developmental course of hopeful future expectations and other character virtues that have been the focus of recent scholarship in youth development. Burgeoning interest in character development has led to a proliferation of short-term, longitudinal studies on character. These data sets are sometimes limited in their ability to model character development trajectories due to low power or relatively brief time spans assessed. However, the integrative data analysis approach allows researchers to pool raw data across studies in order to fit one model to an aggregated data set. The purpose of this article is to demonstrate the promises and challenges of this new tool for modeling character development. We used data from four studies evaluating youth character strengths in different settings to fit latent growth curve models of hopeful future expectations from participants aged 7 through 26 years. We describe the analytic strategy for pooling the data and modeling the growth curves. Implications for future research are discussed in regard to the advantages of integrative data analysis. Finally, we discuss issues researchers should consider when applying these techniques in their own work.

Estimating ecosystem service changes as a precursor to modeling

EPA Science Inventory

EPA's Future Midwestern Landscapes Study will project changes in ecosystem services (ES) for alternative future policy scenarios in the Midwestern U.S. Doing so for detailed landscapes over large spatial scales will require serial application of economic and ecological models. W...

Emotional distress impacts fear of the future among breast cancer survivors not the reverse.

PubMed

Lebel, Sophie; Rosberger, Zeev; Edgar, Linda; Devins, Gerald M

2009-06-01

Fear of the future is one of the most stressful aspects of having cancer. Research to date has conceptualized fear of the future as a precursor of distress or stress-response symptoms. Yet it is equally plausible that distress would predict increased fear of the future or that they would have a reciprocal influence on each other. The purpose of the present study was to examine the bidirectional relations between fear of the future and distress as well as intrusion and avoidance among breast cancer survivors at 3, 7, 11, and 15 months after diagnosis. We used a bivariate latent difference score model for dynamic change to examine these bidirectional relationships among 146 early-stage breast cancer survivors. Using Lisrel version 8.80, we examined four models testing different hypothesized relationships between fear of the future and distress and intrusion and avoidance. Based on model fit evaluation, our data shows that decreases in distress over time lead to a reduction of fear of the future but that changes in fear do not lead to changes in distress. On the other hand, there is no relationship between changes in fear of the future and intrusion and avoidance over time. Ongoing fear of the future does not appear to be a necessary condition for the development of stress-response symptoms. Future studies need to explore the role of distressing emotions in the development and exacerbation of fear of the future among cancer survivors.

Impacts of climate changes on ocean surface gravity waves over the eastern Canadian shelf

NASA Astrophysics Data System (ADS)

Guo, Lanli; Sheng, Jinyu

2017-05-01

A numerical study is conducted to investigate the impact of climate changes on ocean surface gravity waves over the eastern Canadian shelf (ECS). The "business-as-usual" climate scenario known as Representative Concentration Pathway RCP8.5 is considered in this study. Changes in the ocean surface gravity waves over the study region for the period 1979-2100 are examined based on 3 hourly ocean waves simulated by the third-generation ocean wave model known as WAVEWATCHIII. The wave model is driven by surface winds and ice conditions produced by the Canadian Regional Climate Model (CanRCM4). The whole study period is divided into the present (1979-2008), near future (2021-2050) and far future (2071-2100) periods to quantify possible future changes of ocean waves over the ECS. In comparison with the present ocean wave conditions, the time-mean significant wave heights ( H s ) are expected to increase over most of the ECS in the near future and decrease over this region in the far future period. The time-means of the annual 5% largest H s are projected to increase over the ECS in both near and far future periods due mainly to the changes in surface winds. The future changes in the time-means of the annual 5% largest H s and 10-m wind speeds are projected to be twice as strong as the changes in annual means. An analysis of inverse wave ages suggests that the occurrence of wind seas is projected to increase over the southern Labrador and central Newfoundland Shelves in the near future period, and occurrence of swells is projected to increase over other areas of the ECS in both the near and far future periods.

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

PubMed

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

2017-08-15

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

Quantifying Direct and Indirect Impact of Future Climate on Sub-Arctic Hydrology

NASA Astrophysics Data System (ADS)

Endalamaw, A. M.; Bolton, W. R.; Young-Robertson, J. M.; Morton, D.; Hinzman, L. D.

2016-12-01

Projected future climate will have a significant impact on the hydrology of interior Alaskan sub-arctic watersheds, directly though the changes in precipitation and temperature patterns, and indirectly through the cryospheric and ecological impacts. Although the latter is the dominant factor controlling the hydrological processes in the interior Alaska sub-arctic, it is often overlooked in many climate change impact studies. In this study, we aim to quantify and compare the direct and indirect impact of the projected future climate on the hydrology of the interior Alaskan sub-arctic watersheds. The Variable Infiltration Capacity (VIC) meso-scale hydrological model will be implemented to simulate the hydrological processes, including runoff, evapotranspiration, and soil moisture dynamics in the Chena River Basin (area = 5400km2), located in the interior Alaska sub-arctic region. Permafrost and vegetation distribution will be derived from the Geophysical Institute Permafrost Lab (GIPL) model and the Lund-Potsdam-Jena Dynamic Global Model (LPJ) model, respectively. All models will be calibrated and validated using historical data. The Scenario Network for Alaskan and Arctic Planning (SNAP) 5-model average projected climate data products will be used as forcing data for each of these models. The direct impact of climate change on hydrology is estimated using surface parameterization derived from the present day permafrost and vegetation distribution, and future climate forcing from SNAP projected climate data products. Along with the projected future climate, outputs of GIPL and LPJ will be incorporated into the VIC model to estimate the indirect and overall impact of future climate on the hydrology processes in the interior Alaskan sub-arctic watersheds. Finally, we will present the potential hydrological and ecological changes by the end of the 21st century.

Evaluating hydrological response to forecasted land-use change—scenario testing with the automated geospatial watershed assessment (AGWA) tool

USGS Publications Warehouse

Kepner, William G.; Semmens, Darius J.; Hernandez, Mariano; Goodrich, David C.

2009-01-01

Envisioning and evaluating future scenarios has emerged as a critical component of both science and social decision-making. The ability to assess, report, map, and forecast the life support functions of ecosystems is absolutely critical to our capacity to make informed decisions to maintain the sustainable nature of our ecosystem services now and into the future. During the past two decades, important advances in the integration of remote imagery, computer processing, and spatial-analysis technologies have been used to develop landscape information that can be integrated with hydrologic models to determine long-term change and make predictive inferences about the future. Two diverse case studies in northwest Oregon (Willamette River basin) and southeastern Arizona (San Pedro River) were examined in regard to future land use scenarios relative to their impact on surface water conditions (e.g., sediment yield and surface runoff) using hydrologic models associated with the Automated Geospatial Watershed Assessment (AGWA) tool. The base reference grid for land cover was modified in both study locations to reflect stakeholder preferences 20 to 60 yrs into the future, and the consequences of landscape change were evaluated relative to the selected future scenarios. The two studies provide examples of integrating hydrologic modeling with a scenario analysis framework to evaluate plausible future forecasts and to understand the potential impact of landscape change on ecosystem services.

Mental models accurately predict emotion transitions.

PubMed

Thornton, Mark A; Tamir, Diana I

2017-06-06

Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

NASA Astrophysics Data System (ADS)

Prudhomme, C.; Haxton, T.; Crooks, S.; Jackson, C.; Barkwith, A.; Williamson, J.; Kelvin, J.; Mackay, J.; Wang, L.; Young, A.; Watts, G.

2012-12-01

The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels" to provide a consistent set of transient daily river flow and monthly groundwater levels projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate-hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961-1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with the dataset are provided, along with practical recommendation of use. Future Flows Hydrology is freely available for non-commercial use under certain licensing conditions. For each study site, catchment averages of daily precipitation and monthly potential evapotranspiration, used to drive the hydrological models, are made available, so that hydrological modelling uncertainty under climate change conditions can be explored further. doi:10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b.

Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

NASA Astrophysics Data System (ADS)

Prudhomme, C.; Haxton, T.; Crooks, S.; Jackson, C.; Barkwith, A.; Williamson, J.; Kelvin, J.; Mackay, J.; Wang, L.; Young, A.; Watts, G.

2013-03-01

The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels'' to provide a consistent set of transient daily river flow and monthly groundwater level projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate-hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961-1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with the dataset are provided, along with practical recommendation of use. Future Flows Hydrology is freely available for non-commercial use under certain licensing conditions. For each study site, catchment averages of daily precipitation and monthly potential evapotranspiration, used to drive the hydrological models, are made available, so that hydrological modelling uncertainty under climate change conditions can be explored further. doi:10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b

Future Climate Change Impact Assessment of River Flows at Two Watersheds of Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Ercan, A.; Ishida, K.; Kavvas, M. L.; Chen, Z. R.; Jang, S.; Amin, M. Z. M.; Shaaban, A. J.

2016-12-01

Impacts of climate change on the river flows under future climate change conditions were assessed over Muda and Dungun watersheds of Peninsular Malaysia by means of a coupled regional climate model and a physically-based hydrology model utilizing an ensemble of 15 different future climate realizations. Coarse resolution GCMs' future projections covering a wide range of emission scenarios were dynamically downscaled to 6 km resolution over the study area. Hydrologic simulations of the two selected watersheds were carried out at hillslope-scale and at hourly increments.

Univariate time series modeling and an application to future claims amount in SOCSO's invalidity pension scheme

NASA Astrophysics Data System (ADS)

Chek, Mohd Zaki Awang; Ahmad, Abu Bakar; Ridzwan, Ahmad Nur Azam Ahmad; Jelas, Imran Md.; Jamal, Nur Faezah; Ismail, Isma Liana; Zulkifli, Faiz; Noor, Syamsul Ikram Mohd

2012-09-01

The main objective of this study is to forecast the future claims amount of Invalidity Pension Scheme (IPS). All data were derived from SOCSO annual reports from year 1972 - 2010. These claims consist of all claims amount from 7 benefits offered by SOCSO such as Invalidity Pension, Invalidity Grant, Survivors Pension, Constant Attendance Allowance, Rehabilitation, Funeral and Education. Prediction of future claims of Invalidity Pension Scheme will be made using Univariate Forecasting Models to predict the future claims among workforce in Malaysia.

Modeling vulnerability of groundwater to pollution under future scenarios of climate change and biofuels-related land use change: a case study in North Dakota, USA.

PubMed

Li, Ruopu; Merchant, James W

2013-03-01

Modeling groundwater vulnerability to pollution is critical for implementing programs to protect groundwater quality. Most groundwater vulnerability modeling has been based on current hydrogeology and land use conditions. However, groundwater vulnerability is strongly dependent on factors such as depth-to-water, recharge and land use conditions that may change in response to future changes in climate and/or socio-economic conditions. In this research, a modeling framework, which employs three sets of models linked within a geographic information system (GIS) environment, was used to evaluate groundwater pollution risks under future climate and land use changes in North Dakota. The results showed that areas with high vulnerability will expand northward and/or northwestward in Eastern North Dakota under different scenarios. GIS-based models that account for future changes in climate and land use can help decision-makers identify potential future threats to groundwater quality and take early steps to protect this critical resource. Copyright © 2013 Elsevier B.V. All rights reserved.

Expansion of the Lyme Disease Vector Ixodes scapularis in Canada inferred from CMIP5 Climate Projections

NASA Astrophysics Data System (ADS)

McPherson, Michelle Yvonne; García-García, Almudena; José Cuesta-Valero, Francisco; Beltrami, Hugo; Hansen-Ketchum, Patti; MacDougall, Donna; Hume Ogden, Nicholas

2017-04-01

A number of studies have assessed possible climate change impacts on the Lyme disease vector, Ixodes scapularis. However, most have used surface air temperature from only one climate model simulation and/or one emission scenario, representing only one possible climate future. We quantified effects of different Representative Concentration Pathway (RCP) and climate model outputs on the projected future changes in the basic reproduction number (R0) of I. scapularis to explore uncertainties in future R0 estimates. We used surface air temperature generated by a complete set of General Circulation Models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to hindcast historical and forecast future effects of climate change on the R0 of I. scapularis. As in previous studies, R0 of I. scapularis increased with a warming climate under future projected climate. Increases in the multi-model mean R0 values showed significant changes over time under all RCP scenarios, however; only the estimated R0 mean values between RCP6.0 and RCP8.5 showed statistically significant differences. Our results highlight the potential for climate change to have an effect on future Lyme disease risk in Canada even if the Paris Agreement's goal to keep global warming below 2°C is achieved, although mitigation reducing emissions from RCP8.5 levels to those of RCP6.0 or less would be expected to slow tick invasion after the 2030s. On-going planning is needed to inform and guide adaptation in light of the projected range of possible futures.

Mid-21st century projections of hydroclimate in Western Himalayas and Satluj River basin

NASA Astrophysics Data System (ADS)

Tiwari, Sarita; Kar, Sarat C.; Bhatla, R.

2018-02-01

The Himalayan climate system is sensitive to global warming and climate change. Regional hydrology and the downstream water flow in the rivers of Himalayan origin may change due to variations in snow and glacier melt in the region. This study examines the mid-21st century climate projections over western Himalayas from the Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models under Representative Concentration Pathways (RCP) scenarios (RCP4.5 and RCP8.5). All the global climate models used in the present analysis indicate that the study region would be warmer by mid-century. The temperature trends from all the models studied here are statistically significant at 95% confidence interval. Multi-model ensemble spreads show that there are large differences among the models in their projections of future climate with spread in temperature ranging from about 1.5 °C to 5 °C over various areas of western Himalayas in all the seasons. Spread in precipitation projections lies between 0.3 and 1 mm/day in all the seasons. Major shift in the timing of evaporation maxima and minima is noticed. The GFDL_ESM2G model products have been downscaled to Satluj River basin using the weather research and forecast (WRF) model and impact of climate change on streamflow has been studied. The reduction of precipitation during JJAS is expected to be > 3-6 mm/day in RCP8.5 as compared to present climate. It is expected that precipitation amount shall increase over Satluj basin in future (mid-21st century) The soil and water assessment tool (SWAT) model has been used to simulate the Satluj streamflow for the present and future climate using GFDL_ESM2G precipitation and temperature data as well as the WRF model downscaled data. The computations using the global model data show that total annual discharge from Satluj will be less in future than that in present climate, especially in peak discharge season (JJAS). The SWAT model with downscaled output indicates that during winter and spring, more discharge shall occur in future (RCP8.5) in Satluj River.

The lead-lag relationship between stock index and stock index futures: A thermal optimal path method

NASA Astrophysics Data System (ADS)

Gong, Chen-Chen; Ji, Shen-Dan; Su, Li-Ling; Li, Sai-Ping; Ren, Fei

2016-02-01

The study of lead-lag relationship between stock index and stock index futures is of great importance for its wide application in hedging and portfolio investments. Previous works mainly use conventional methods like Granger causality test, GARCH model and error correction model, and focus on the causality relation between the index and futures in a certain period. By using a non-parametric approach-thermal optimal path (TOP) method, we study the lead-lag relationship between China Securities Index 300 (CSI 300), Hang Seng Index (HSI), Standard and Poor 500 (S&P 500) Index and their associated futures to reveal the variance of their relationship over time. Our finding shows evidence of pronounced futures leadership for well established index futures, namely HSI and S&P 500 index futures, while index of developing market like CSI 300 has pronounced leadership. We offer an explanation based on the measure of an indicator which quantifies the differences between spot and futures prices for the surge of lead-lag function. Our results provide new perspectives for the understanding of the dynamical evolution of lead-lag relationship between stock index and stock index futures, which is valuable for the study of market efficiency and its applications.

Impact of Future Climate on Radial Growth of Four Major Boreal Tree Species in the Eastern Canadian Boreal Forest

PubMed Central

Huang, Jian-Guo; Bergeron, Yves; Berninger, Frank; Zhai, Lihong; Tardif, Jacques C.; Denneler, Bernhard

2013-01-01

Immediate phenotypic variation and the lagged effect of evolutionary adaptation to climate change appear to be two key processes in tree responses to climate warming. This study examines these components in two types of growth models for predicting the 2010–2099 diameter growth change of four major boreal species Betula papyrifera, Pinus banksiana, Picea mariana, and Populus tremuloides along a broad latitudinal gradient in eastern Canada under future climate projections. Climate-growth response models for 34 stands over nine latitudes were calibrated and cross-validated. An adaptive response model (A-model), in which the climate-growth relationship varies over time, and a fixed response model (F-model), in which the relationship is constant over time, were constructed to predict future growth. For the former, we examined how future growth of stands in northern latitudes could be forecasted using growth-climate equations derived from stands currently growing in southern latitudes assuming that current climate in southern locations provide an analogue for future conditions in the north. For the latter, we tested if future growth of stands would be maximally predicted using the growth-climate equation obtained from the given local stand assuming a lagged response to climate due to genetic constraints. Both models predicted a large growth increase in northern stands due to more benign temperatures, whereas there was a minimal growth change in southern stands due to potentially warm-temperature induced drought-stress. The A-model demonstrates a changing environment whereas the F-model highlights a constant growth response to future warming. As time elapses we can predict a gradual transition between a response to climate associated with the current conditions (F-model) to a more adapted response to future climate (A-model). Our modeling approach provides a template to predict tree growth response to climate warming at mid-high latitudes of the Northern Hemisphere. PMID:23468879

Impact of future climate on radial growth of four major boreal tree species in the Eastern Canadian boreal forest.

PubMed

Huang, Jian-Guo; Bergeron, Yves; Berninger, Frank; Zhai, Lihong; Tardif, Jacques C; Denneler, Bernhard

2013-01-01

Immediate phenotypic variation and the lagged effect of evolutionary adaptation to climate change appear to be two key processes in tree responses to climate warming. This study examines these components in two types of growth models for predicting the 2010-2099 diameter growth change of four major boreal species Betula papyrifera, Pinus banksiana, Picea mariana, and Populus tremuloides along a broad latitudinal gradient in eastern Canada under future climate projections. Climate-growth response models for 34 stands over nine latitudes were calibrated and cross-validated. An adaptive response model (A-model), in which the climate-growth relationship varies over time, and a fixed response model (F-model), in which the relationship is constant over time, were constructed to predict future growth. For the former, we examined how future growth of stands in northern latitudes could be forecasted using growth-climate equations derived from stands currently growing in southern latitudes assuming that current climate in southern locations provide an analogue for future conditions in the north. For the latter, we tested if future growth of stands would be maximally predicted using the growth-climate equation obtained from the given local stand assuming a lagged response to climate due to genetic constraints. Both models predicted a large growth increase in northern stands due to more benign temperatures, whereas there was a minimal growth change in southern stands due to potentially warm-temperature induced drought-stress. The A-model demonstrates a changing environment whereas the F-model highlights a constant growth response to future warming. As time elapses we can predict a gradual transition between a response to climate associated with the current conditions (F-model) to a more adapted response to future climate (A-model). Our modeling approach provides a template to predict tree growth response to climate warming at mid-high latitudes of the Northern Hemisphere.

Impacts of weighting climate models for hydro-meteorological climate change studies

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel

2017-06-01

Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.

Forecasting Educational Futures. Resolving Uncertainties and Disagreements through Compact Policy Assessment.

ERIC Educational Resources Information Center

Hudson, Barclay M.

Descriptions of models for policy analysis in future studies are presented. Separate sections of the paper focus on the need for appropriate technologies of social science in future studies, a description of "compact policy assessment" (CPA), and a comparison of two CPA methods, Compass and Delphi. Compact policy assessment refers to any low-cost,…

Emerging Adulthood among Palestinian Minority in Israel: The Relation between Perceived Career Barriers, Future Orientation and Career Decisions

ERIC Educational Resources Information Center

Mahajna, Sami

2017-01-01

This study examines the relation between perceived career barriers, future orientation and career decisions among young Palestinian-Israeli youth. The study employs a theoretical model that links perceived career barriers and career decisions via variables of future orientation. Three hundred eighty-eight young Palestinian-Israeli women (73.20%)…

SOFRA and RPA: two views of the future of southern timber supply.

Treesearch

Darius Adams; John Mills; Ralph Alig; Richard Haynes

2005-01-01

Two recent studies provide alternative views of the current state and future prospects of southern forests and timber supply: the Southern Forest Resource Assessment (SOFRA) and the Fifth Resources Planning Act Timber Assessment (RPA). Using apparently comparable data but different models and methods, the studies portray futures that in some aspects are quite similar...

"On solid ground": family and school connectedness promotes adolescents' future orientation.

PubMed

Crespo, Carla; Jose, Paul E; Kielpikowski, Magdalena; Pryor, Jan

2013-10-01

The present study investigated the role of connectedness to the family and school contexts on future orientation of New Zealand adolescents. Participants were 1774 young people (51.9% female) aged between 9 and 16 years at time 1 of the study, who reported their connectedness to family and school and their perceptions of future orientation at three times of measurement one year apart. Structural equation modelling was used to test the combined role of family and school connectedness on future orientation over time. Findings supported a multiple mediation model in that adolescents' connectedness to family and school predicted more positive perceptions of future orientation both directly and indirectly via the effect of the context variables on each other. Copyright © 2013 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Modeling conflict : research methods, quantitative modeling, and lessons learned.

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

Rexroth, Paul E.; Malczynski, Leonard A.; Hendrickson, Gerald A.

2004-09-01

This study investigates the factors that lead countries into conflict. Specifically, political, social and economic factors may offer insight as to how prone a country (or set of countries) may be for inter-country or intra-country conflict. Largely methodological in scope, this study examines the literature for quantitative models that address or attempt to model conflict both in the past, and for future insight. The analysis concentrates specifically on the system dynamics paradigm, not the political science mainstream approaches of econometrics and game theory. The application of this paradigm builds upon the most sophisticated attempt at modeling conflict as a resultmore » of system level interactions. This study presents the modeling efforts built on limited data and working literature paradigms, and recommendations for future attempts at modeling conflict.« less

Fire risk in San Diego County, California: A weighted Bayesian model approach

USGS Publications Warehouse

Kolden, Crystal A.; Weigel, Timothy J.

2007-01-01

Fire risk models are widely utilized to mitigate wildfire hazards, but models are often based on expert opinions of less understood fire-ignition and spread processes. In this study, we used an empirically derived weights-of-evidence model to assess what factors produce fire ignitions east of San Diego, California. We created and validated a dynamic model of fire-ignition risk based on land characteristics and existing fire-ignition history data, and predicted ignition risk for a future urbanization scenario. We then combined our empirical ignition-risk model with a fuzzy fire behavior-risk model developed by wildfire experts to create a hybrid model of overall fire risk. We found that roads influence fire ignitions and that future growth will increase risk in new rural development areas. We conclude that empirically derived risk models and hybrid models offer an alternative method to assess current and future fire risk based on management actions.

A Model for settlement of health insurance organizations’ debt to health service delivery institutions

PubMed Central

Abolhallaj, Masood; Hosseini, Seyed Mohammadreza; Jafari, Mehdi; Alaei, Fatemeh

2017-01-01

Background: Sukuk is a type of financial instrument backed by balance sheet and physical assets. This applied and descriptive study aimed at providing solutions to the problems faced by insurance companies in the health sector. Methods: In this study, we achieved operational models by reviewing the release nature and mechanism of any of the securities and combining them. Results: According to the model presented in this study, 2 problems could be solved: settling the past debts and avoiding future debts. This model was deigned based on asset backed securities. Conclusion: Utilizing financing instruments (such as Sukuk), creating investment funds, and finding a solution to this problem, this study was conducted in 2 aspects: (1) models that are settling old debts of the organization, and (2) models that prevent debts in the future.

Analyzing Future Flooding under Climate Change Scenario using CMIP5 Streamflow Data

NASA Astrophysics Data System (ADS)

Parajuli, Ranjan; Nyaupane, Narayan; Kalra, Ajay

2017-12-01

Flooding is a severe and costlier natural hazard. The effect of climate change has intensified the scenario in recent years. Flood prevention practice along with a proper understanding of flooding event can mitigate the risk of such hazard. The floodplain mapping is one of the technique to quantify the severity of the flooding. Carson City, which is one of the agricultural areas in the desert of Nevada has experienced peak flood in the recent year. The underlying probability distribution for the area, latest Coupled Model Intercomparison Project (CMIP5) streamflow data of Carson River were analyzed for 27 different statistical distributions. The best-fitted distribution underlying was used to forecast the 100yr flood (design flood). The data from 1950-2099 derived from 31 model and total 97 projections were used to predict the future streamflow. Delta change method is adopted to quantify the amount of future (2050-2099) flood. To determine the extent of flooding 3 scenarios (i) historic design flood, (ii) 500yr flood and (iii) future 100yr flood were routed on an HEC-RAS model, prepared using available terrain data. Some of the climate projection shows an extreme increase in future design flood. This study suggests an approach to quantify the future flood and floodplain using climate model projections. The study would provide helpful information to the facility manager, design engineer, and stakeholders.

Exposing the dark sector with future Z factories

NASA Astrophysics Data System (ADS)

Liu, Jia; Wang, Lian-Tao; Wang, Xiao-Ping; Xue, Wei

2018-05-01

We investigate the prospects of searching dark sector models via exotic Z -boson decay at future e+e- colliders with Giga Z and Tera Z options. Four general categories of dark sector models, Higgs portal dark matter, vector-portal dark matter, inelastic dark matter, and axionlike particles, are considered. Focusing on channels motivated by the dark sector models, we carry out a model-independent study of the sensitivities of Z factories in probing exotic decays. The limits on branching ratios of the exotic Z decay are typically O (10-6- 10-8.5) for the Giga Z and O (10-7.5- 10-11) for the Tera Z , and they are compared with the projection for the high luminosity LHC. We demonstrate that future Z factories can provide its unique and leading sensitivity and highlight the complementarity with other experiments, including the indirect and direct dark matter search limits and the existing collider limits. Future Z factories will play a leading role in uncovering the hidden sector of the Universe in the future.

Future climate data from RCP 4.5 and occurrence of malaria in Korea.

PubMed

Kwak, Jaewon; Noh, Huiseong; Kim, Soojun; Singh, Vijay P; Hong, Seung Jin; Kim, Duckgil; Lee, Keonhaeng; Kang, Narae; Kim, Hung Soo

2014-10-15

Since its reappearance at the Military Demarcation Line in 1993, malaria has been occurring annually in Korea. Malaria is regarded as a third grade nationally notifiable disease susceptible to climate change. The objective of this study is to quantify the effect of climatic factors on the occurrence of malaria in Korea and construct a malaria occurrence model for predicting the future trend of malaria under the influence of climate change. Using data from 2001-2011, the effect of time lag between malaria occurrence and mean temperature, relative humidity and total precipitation was investigated using spectral analysis. Also, a principal component regression model was constructed, considering multicollinearity. Future climate data, generated from RCP 4.5 climate change scenario and CNCM3 climate model, was applied to the constructed regression model to simulate future malaria occurrence and analyze the trend of occurrence. Results show an increase in the occurrence of malaria and the shortening of annual time of occurrence in the future.

Future Climate Data from RCP 4.5 and Occurrence of Malaria in Korea

PubMed Central

Kwak, Jaewon; Noh, Huiseong; Kim, Soojun; Singh, Vijay P.; Hong, Seung Jin; Kim, Duckgil; Lee, Keonhaeng; Kang, Narae; Kim, Hung Soo

2014-01-01

Since its reappearance at the Military Demarcation Line in 1993, malaria has been occurring annually in Korea. Malaria is regarded as a third grade nationally notifiable disease susceptible to climate change. The objective of this study is to quantify the effect of climatic factors on the occurrence of malaria in Korea and construct a malaria occurrence model for predicting the future trend of malaria under the influence of climate change. Using data from 2001–2011, the effect of time lag between malaria occurrence and mean temperature, relative humidity and total precipitation was investigated using spectral analysis. Also, a principal component regression model was constructed, considering multicollinearity. Future climate data, generated from RCP 4.5 climate change scenario and CNCM3 climate model, was applied to the constructed regression model to simulate future malaria occurrence and analyze the trend of occurrence. Results show an increase in the occurrence of malaria and the shortening of annual time of occurrence in the future. PMID:25321875

Mental models accurately predict emotion transitions

PubMed Central

Thornton, Mark A.; Tamir, Diana I.

2017-01-01

Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373

The role of glacier changes and threshold definition in the characterisation of future streamflow droughts in glacierised catchments

NASA Astrophysics Data System (ADS)

Van Tiel, Marit; Teuling, Adriaan J.; Wanders, Niko; Vis, Marc J. P.; Stahl, Kerstin; Van Loon, Anne F.

2018-01-01

Glaciers are essential hydrological reservoirs, storing and releasing water at various timescales. Short-term variability in glacier melt is one of the causes of streamflow droughts, here defined as deficiencies from the flow regime. Streamflow droughts in glacierised catchments have a wide range of interlinked causing factors related to precipitation and temperature on short and long timescales. Climate change affects glacier storage capacity, with resulting consequences for discharge regimes and streamflow drought. Future projections of streamflow drought in glacierised basins can, however, strongly depend on the modelling strategies and analysis approaches applied. Here, we examine the effect of different approaches, concerning the glacier modelling and the drought threshold, on the characterisation of streamflow droughts in glacierised catchments. Streamflow is simulated with the Hydrologiska Byråns Vattenbalansavdelning (HBV-light) model for two case study catchments, the Nigardsbreen catchment in Norway and the Wolverine catchment in Alaska, and two future climate change scenarios (RCP4.5 and RCP8.5). Two types of glacier modelling are applied, a constant and dynamic glacier area conceptualisation. Streamflow droughts are identified with the variable threshold level method and their characteristics are compared between two periods, a historical (1975-2004) and future (2071-2100) period. Two existing threshold approaches to define future droughts are employed: (1) the threshold from the historical period; (2) a transient threshold approach, whereby the threshold adapts every year in the future to the changing regimes. Results show that drought characteristics differ among the combinations of glacier area modelling and thresholds. The historical threshold combined with a dynamic glacier area projects extreme increases in drought severity in the future, caused by the regime shift due to a reduction in glacier area. The historical threshold combined with a constant glacier area results in a drastic decrease of the number of droughts. The drought characteristics between future and historical periods are more similar when the transient threshold is used, for both glacier area conceptualisations. With the transient threshold, factors causing future droughts can be analysed. This study revealed the different effects of methodological choices on future streamflow drought projections and it highlights how the options can be used to analyse different aspects of future droughts: the transient threshold for analysing future drought processes, the historical threshold to assess changes between periods, the constant glacier area to analyse the effect of short-term climate variability on droughts and the dynamic glacier area to model more realistic future discharges under climate change.

Generation Expansion Planning With Large Amounts of Wind Power via Decision-Dependent Stochastic Programming

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

Zhan, Yiduo; Zheng, Qipeng P.; Wang, Jianhui

Power generation expansion planning needs to deal with future uncertainties carefully, given that the invested generation assets will be in operation for a long time. Many stochastic programming models have been proposed to tackle this challenge. However, most previous works assume predetermined future uncertainties (i.e., fixed random outcomes with given probabilities). In several recent studies of generation assets' planning (e.g., thermal versus renewable), new findings show that the investment decisions could affect the future uncertainties as well. To this end, this paper proposes a multistage decision-dependent stochastic optimization model for long-term large-scale generation expansion planning, where large amounts of windmore » power are involved. In the decision-dependent model, the future uncertainties are not only affecting but also affected by the current decisions. In particular, the probability distribution function is determined by not only input parameters but also decision variables. To deal with the nonlinear constraints in our model, a quasi-exact solution approach is then introduced to reformulate the multistage stochastic investment model to a mixed-integer linear programming model. The wind penetration, investment decisions, and the optimality of the decision-dependent model are evaluated in a series of multistage case studies. The results show that the proposed decision-dependent model provides effective optimization solutions for long-term generation expansion planning.« less

Model and Scenario Variations in Predicted Number of Generations of Spodoptera litura Fab. on Peanut during Future Climate Change Scenario

PubMed Central

Srinivasa Rao, Mathukumalli; Swathi, Pettem; Rama Rao, Chitiprolu Anantha; Rao, K. V.; Raju, B. M. K.; Srinivas, Karlapudi; Manimanjari, Dammu; Maheswari, Mandapaka

2015-01-01

The present study features the estimation of number of generations of tobacco caterpillar, Spodoptera litura. Fab. on peanut crop at six locations in India using MarkSim, which provides General Circulation Model (GCM) of future data on daily maximum (T.max), minimum (T.min) air temperatures from six models viz., BCCR-BCM2.0, CNRM-CM3, CSIRO-Mk3.5, ECHams5, INCM-CM3.0 and MIROC3.2 along with an ensemble of the six from three emission scenarios (A2, A1B and B1). This data was used to predict the future pest scenarios following the growing degree days approach in four different climate periods viz., Baseline-1975, Near future (NF) -2020, Distant future (DF)-2050 and Very Distant future (VDF)—2080. It is predicted that more generations would occur during the three future climate periods with significant variation among scenarios and models. Among the seven models, 1–2 additional generations were predicted during DF and VDF due to higher future temperatures in CNRM-CM3, ECHams5 & CSIRO-Mk3.5 models. The temperature projections of these models indicated that the generation time would decrease by 18–22% over baseline. Analysis of variance (ANOVA) was used to partition the variation in the predicted number of generations and generation time of S. litura on peanut during crop season. Geographical location explained 34% of the total variation in number of generations, followed by time period (26%), model (1.74%) and scenario (0.74%). The remaining 14% of the variation was explained by interactions. Increased number of generations and reduction of generation time across the six peanut growing locations of India suggest that the incidence of S. litura may increase due to projected increase in temperatures in future climate change periods. PMID:25671564

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.

Clustering of Global Climate Models outputs as a tool for scenario-based risk assessment

NASA Astrophysics Data System (ADS)

R Pereira, V.; Zullo, J., Jr.; Avila, A. M. H. D.

2016-12-01

The choice of the Global Climate Models (GCMs) future projections outputs for the scenario based risk assessment studies is a challenge for the non-climate models scientists. This study presents a method to select a range of the GCMs scenarios for regional/continental agriculture studies. The technique proposed here is based on grouping the surface air temperature (tas) anomalies in a continental /regional scale - in Brazil-South America - projected by the AR5-CMIP5-GCMs. We run the k-means cluster algorithm and the silhouette method to identify the optimal number and to group the GCMs tas outputs under the rcp 8.5. We applied the delta method to calculate the near future climate change. This method is based on the difference between the future and the baseline in a 30 year running mean periods basis. The future considered here is the 2021-2050 [2030s] and the baseline is the period of 1976-2005 (1980s). As expected, all the models projections showed increases in tas in the near future, ranging from ≅ 3.6 to 0.2 oC. The k-means clustering clearly indicates 5 groups of GCMs tas deltas. The majority of GCMs indicated an intermediate future temperature changes. There is a group of 12 GCMs that is indicating an average change of ≅ 2 oC and another group of 16 indicating ≅ 1 oC. The other two groups with 3 GCMs each indicated a most extreme tas scenario - 0.2 and 3.6 oC respectively. The results were in agreement with previous studies with the AR4 GCMs in which the Miroc5 and HADGEM ES predecessors were classified in different groups of models. The results also allowed us to gradually access the optimist - pessimist groups of 34 GCMs that is a good reference to guide the public policy demands for agriculture under climate change conditions.

Future-year ozone prediction for the United States using updated models and inputs.

PubMed

Collet, Susan; Kidokoro, Toru; Karamchandani, Prakash; Shah, Tejas; Jung, Jaegun

2017-08-01

The relationship between emission reductions and changes in ozone can be studied using photochemical grid models. These models are updated with new information as it becomes available. The primary objective of this study was to update the previous Collet et al. studies by using the most up-to-date (at the time the study was done) modeling emission tools, inventories, and meteorology available to conduct ozone source attribution and sensitivity studies. Results show future-year, 2030, design values for 8-hr ozone concentrations were lower than base-year values, 2011. The ozone source attribution results for selected cities showed that boundary conditions were the dominant contributors to ozone concentrations at the western U.S. locations, and were important for many of the eastern U.S. Point sources were generally more important in the eastern United States than in the western United States. The contributions of on-road mobile emissions were less than 5 ppb at a majority of the cities selected for analysis. The higher-order decoupled direct method (HDDM) results showed that in most of the locations selected for analysis, NOx emission reductions were more effective than VOC emission reductions in reducing ozone levels. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies. The relationship between emission reductions and changes in ozone can be studied using photochemical grid models, which are updated with new available information. This study was to update the previous Collet et al. studies by using the most current, at the time the study was done, models and inventory to conduct ozone source attribution and sensitivity studies. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies.

Assessing future expectations and the two-dimensional model of affect in an Italian population.

PubMed

Corno, Giulia; Molinari, Guadalupe; Baños, Rosa Maria

2017-03-01

Future-directed thinking has been described as part of two underlying systems that integrate dimensions of affect, motivational systems, orientation to the future, and future expectations, which are initiated at the cognitive, affective, biological, behavioral, and motivational levels. The main aim of the present study is to test the two underlying frameworks model and explore future expectations in a general Italian-speaking population (N=345). Therefore, the second aim of the present paper is to confirm the factorial structure of the Subjective Probability Task (SPT; MacLeod et al., 1996), a questionnaire designed to assess specific positive and negative orientations towards the future. Results showed that the SPT has good psychometric properties and it is a reliable instrument to assess future-directed thinking. Moreover, our findings confirmed the role of future expectancies as cognitive correlates of depression and anxiety. Differently from previous studies (Clark and Watson, 1991; MacLeod et al., 1996), our results did not confirm that depression was characterized by low positive affect. We believe this paper contributes to the understanding of future expectancies and their relation with anxiety and depression, and will help to expand the availability of an instrument to assess future directed thinking. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Future shift of the relative roles of precipitation and temperature in controlling annual runoff in the conterminous United States

Treesearch

Kai Duan; Ge Sun; Steven G. McNulty; Peter V. Caldwell; Erika C. Cohen; Shanlei Sun; Heather D. Aldridge; Decheng Zhou; Liangxia Zhang; Yang Zhang

2017-01-01

This study examines the relative roles of cli- matic variables in altering annual runoff in the contermi- nous United States (CONUS) in the 21st century, using a monthly ecohydrological model (the Water Supply Stress In- dex model, WaSSI) driven with historical records and future scenarios constructed from 20 Coupled Model Intercompar- ison Project Phase 5 (CMIP5)...

Future water supply and demand in response to climate change and agricultural expansion in Texas

NASA Astrophysics Data System (ADS)

Lee, K.; Zhou, T.; Gao, H.; Huang, M.

2016-12-01

With ongoing global environmental change and an increasing population, it is challenging (to say the least) to understand the complex interactions of irrigation and reservoir systems. Irrigation is critical to agricultural production and food security, and is a vital component of Texas' agricultural economy. Agricultural irrigation currently accounts for about 60% of total water demand in Texas, and recent occurrences of severe droughts has brought attention to the availability and use of water in the future. In this study, we aim to assess future agricultural irrigation water demand, and to estimate how changes in the fraction of crop irrigated land will affect future water availability in Texas, which has the largest farm area and the highest value of livestock production in the United States. The Variable Infiltration Capacity (VIC) model, which has been calibrated and validated over major Texas river basins during the historical period, is employed for this study. The VIC model, coupling with an irrigation scheme and a reservoir module, is adopted to simulate the water management and regulations. The evolution on agricultural land is also considered in the model as a changing fraction of crop for each grid cell. The reservoir module is calibrated and validated based on the historical (1915-2011) storage records of major reservoirs in Texas. The model is driven by statistically downscaled climate projections from Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The lowest (RCP 2.6) and highest (RC P8.5) greenhouse-gas concentration scenarios are adopted for future projections to provide an estimate of uncertainty bounds. We expect that our results will be helpful to assist decision making related to reservoir operations and agricultural water planning for Texas under future climate and environmental changes.

Importance of vegetation distribution for future carbon balance

NASA Astrophysics Data System (ADS)

Ahlström, A.; Xia, J.; Arneth, A.; Luo, Y.; Smith, B.

2015-12-01

Projections of future terrestrial carbon uptake vary greatly between simulations. Net primary production (NPP), wild fires, vegetation dynamics (including biome shifts) and soil decomposition constitute the main processes governing the response of the terrestrial carbon cycle in a changing climate. While primary production and soil respiration are relatively well studied and implemented in all global ecosystem models used to project the future land sink of CO2, vegetation dynamics are less studied and not always represented in global models. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality and the associated turnover and proven skill in predicting vegetation distribution and succession. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the CMIP5 ensemble under RCP8.5 radiative forcing at year 2085. We exchanged carbon cycle processes between these 13 simulations and investigate the changes predicted by the emulator. This method allowed us to partition the entire ensemble carbon uptake uncertainty into individual processes. We found that NPP, vegetation dynamics (including biome shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33% respectively of uncertainties in modeled global C-uptake. Uncertainty due to vegetation dynamics was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by shifts in vegetation distribution, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

Nitrogen feedbacks increase future terrestrial ecosystem carbon uptake in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Wårlind, D.; Smith, B.; Hickler, T.; Arneth, A.

2014-01-01

Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use the dynamic vegetation model LPJ-GUESS to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one exemplary "business-as-usual" climate scenario). Single factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C-N interactions, compared to the C-only version of the model, as documented in previous studies. Under a RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics until present. However, during the 21st century nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contradicts earlier model results that showed an 8 to 37% decrease in carbon uptake, questioning the often stated assumption that projections of future terrestrial C dynamics from C-only models are too optimistic.

Distributional dynamics of a vulnerable species in response to past and future climate change: a window for conservation prospects

PubMed Central

Bai, Yunjun; Wei, Xueping

2018-01-01

Background The ongoing change in climate is predicted to exert unprecedented effects on Earth’s biodiversity at all levels of organization. Biological conservation is important to prevent biodiversity loss, especially for species facing a high risk of extinction. Understanding the past responses of species to climate change is helpful for revealing response mechanisms, which will contribute to the development of effective conservation strategies in the future. Methods In this study, we modelled the distributional dynamics of a ‘Vulnerable’ species, Pseudolarix amabilis, in response to late Quaternary glacial-interglacial cycles and future 2080 climate change using an ecological niche model (MaxEnt). We also performed migration vector analysis to reveal the potential migration of the population over time. Results Historical modelling indicates that the range dynamics of P. amabilis is highly sensitive to climate change and that its long-distance dispersal ability and potential for evolutionary adaption are limited. Compared to the current climatically suitable areas for this species, future modelling showed significant migration northward towards future potential climatically suitable areas. Discussion In combination with the predicted future distribution, the mechanism revealed by the historical response suggests that this species will not be able to fully occupy the future expanded areas of suitable climate or adapt to the unsuitable climate across the future contraction regions. As a result, we suggest assisted migration as an effective supplementary means of conserving this vulnerable species in the face of the unprecedentedly rapid climate change of the 21st century. As a study case, this work highlights the significance of introducing historical perspectives while researching species conservation, especially for currently vulnerable or endangered taxa that once had a wider distribution in geological time. PMID:29362700

Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

USGS Publications Warehouse

Tillman, Fred D.; Gangopadhyay, Subhrendu; Pruitt, Tom

2017-01-01

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.

Distributional dynamics of a vulnerable species in response to past and future climate change: a window for conservation prospects.

PubMed

Bai, Yunjun; Wei, Xueping; Li, Xiaoqiang

2018-01-01

The ongoing change in climate is predicted to exert unprecedented effects on Earth's biodiversity at all levels of organization. Biological conservation is important to prevent biodiversity loss, especially for species facing a high risk of extinction. Understanding the past responses of species to climate change is helpful for revealing response mechanisms, which will contribute to the development of effective conservation strategies in the future. In this study, we modelled the distributional dynamics of a 'Vulnerable' species, Pseudolarix amabilis , in response to late Quaternary glacial-interglacial cycles and future 2080 climate change using an ecological niche model (MaxEnt). We also performed migration vector analysis to reveal the potential migration of the population over time. Historical modelling indicates that the range dynamics of P. amabilis is highly sensitive to climate change and that its long-distance dispersal ability and potential for evolutionary adaption are limited. Compared to the current climatically suitable areas for this species, future modelling showed significant migration northward towards future potential climatically suitable areas. In combination with the predicted future distribution, the mechanism revealed by the historical response suggests that this species will not be able to fully occupy the future expanded areas of suitable climate or adapt to the unsuitable climate across the future contraction regions. As a result, we suggest assisted migration as an effective supplementary means of conserving this vulnerable species in the face of the unprecedentedly rapid climate change of the 21st century. As a study case, this work highlights the significance of introducing historical perspectives while researching species conservation, especially for currently vulnerable or endangered taxa that once had a wider distribution in geological time.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model.

PubMed

Shafer, Sarah L; Bartlein, Patrick J; Gray, Elizabeth M; Pelltier, Richard T

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0°N latitude by 136.6-103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

When Future Change Matters: Modeling Future Price and Diffusion in Health Technology Assessments of Medical Devices.

PubMed

Grimm, Sabine E; Dixon, Simon; Stevens, John W

Health technology assessments (HTAs) that take account of future price changes have been examined in the literature, but the important issue of price reductions that are generated by the reimbursement decision has been ignored. To explore the impact of future price reductions caused by increasing uptake on HTAs and decision making for medical devices. We demonstrate the use of a two-stage modeling approach to derive estimates of technology price as a consequence of changes in technology uptake over future periods on the basis of existing theory and supported by empirical studies. We explore the impact on cost-effectiveness and expected value of information analysis in an illustrative example on the basis of a technology in development for preterm birth screening. The application of our approach to the case study technology generates smaller incremental cost-effectiveness ratios compared with the commonly used single cohort approach. The extent of this reduction in the incremental cost-effectiveness ratio depends on the magnitude of the modeled price reduction, the speed of diffusion, and the length of the assumed technology life horizon. Results of value of information analysis are affected through changes in the expected net benefit calculation, the addition of uncertain parameters, and the diffusion-adjusted estimate of the affected patient population. Because modeling future changes in price and uptake has the potential to affect HTA outcomes, modeling techniques that can address such changes should be considered for medical devices that may otherwise be rejected. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Benefits of Model Updating: A Case Study Using the Micro-Precision Interferometer Testbed

NASA Technical Reports Server (NTRS)

Neat, Gregory W.; Kissil, Andrew; Joshi, Sanjay S.

1997-01-01

This paper presents a case study on the benefits of model updating using the Micro-Precision Interferometer (MPI) testbed, a full-scale model of a future spaceborne optical interferometer located at JPL.

Projected climate and vegetation changes and potential biotic effects for Fort Benning, Georgia; Fort Hood, Texas; and Fort Irwin, California

USGS Publications Warehouse

Shafer, S.L.; Atkins, J.; Bancroft, B.A.; Bartlein, P.J.; Lawler, J.J.; Smith, B.; Wilsey, C.B.

2012-01-01

The responses of species and ecosystems to future climate changes will present challenges for conservation and natural resource managers attempting to maintain both species populations and essential habitat. This report describes projected future changes in climate and vegetation for three study areas surrounding the military installations of Fort Benning, Georgia, Fort Hood, Texas, and Fort Irwin, California. Projected climate changes are described for the time period 2070–2099 (30-year mean) as compared to 1961–1990 (30-year mean) for each study area using data simulated by the coupled atmosphere-ocean general circulation models CCSM3, CGCM3.1(T47), and UKMO-HadCM3, run under the B1, A1B, and A2 future greenhouse gas emissions scenarios. These climate data are used to simulate potential changes in important components of the vegetation for each study area using LPJ, a dynamic global vegetation model, and LPJ-GUESS, a dynamic vegetation model optimized for regional studies. The simulated vegetation results are compared with observed vegetation data for the study areas. Potential effects of the simulated future climate and vegetation changes for species and habitats of management concern are discussed in each study area, with a particular focus on federally listed threatened and endangered species.

Regional Climate Change Impact on Agricultural Land Use in West Africa

NASA Astrophysics Data System (ADS)

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

2014-12-01

Agriculture is a key element of the human-induced land use land cover change (LULCC) that is influenced by climate and can potentially influence regional climate. Temperature and precipitation directly impact the crop yield (by controlling photosynthesis, respiration and other physiological processes) that then affects agricultural land use pattern. In feedback, the resulting changes in land use and land cover play an important role to determine the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. The assessment of future agricultural land use is, therefore, of great importance in climate change study. In this study, we develop a prototype land use projection model and, using this model, project the changes to land use pattern and future land cover map accounting for climate-induced yield changes for major crops in West Africa. Among the inputs to the land use projection model are crop yield changes simulated by the crop model DSSAT, driven with the climate forcing data from the regional climate model RegCM4.3.4-CLM4.5, which features a projected decrease of future mean crop yield and increase of inter-annual variability. Another input to the land use projection model is the projected changes of food demand in the future. In a so-called "dumb-farmer scenario" without any adaptation, the combined effect of decrease in crop yield and increase in food demand will lead to a significant increase in agricultural land use in future years accompanied by a decrease in forest and grass area. Human adaptation through land use optimization in an effort to minimize agricultural expansion is found to have little impact on the overall areas of agricultural land use. While the choice of the General Circulation Model (GCM) to derive initial and boundary conditions for the regional climate model can be a source of uncertainty in projecting the future LULCC, results from sensitivity experiments indicate that the changes in land use pattern are robust.

Patterns of crop cover under future climates.

PubMed

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

2017-04-01

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

Analyzing Future Flooding under Climate Change Scenario using CMIP5 Streamflow Data

NASA Astrophysics Data System (ADS)

Nyaupane, Narayan; Parajuli, Ranjan; Kalra, Ajay

2017-12-01

Flooding is the most severe and costlier natural hazard in US. The effect of climate change has intensified the scenario in recent years. Flood prevention practice along with proper understanding of flooding event can mitigate the risk of such hazard. The flood plain mapping is one of the technique to quantify the severity of the flooding. Carson City, which is one of the agricultural area in the desert of Nevada has experienced peak flood in recent year. The underlying probability distribution for the area, latest Coupled Model Intercomparison Project (CMIP5) streamflow data of Carson River were analyzed for 27 different statistical distributions. The best fitted distribution underlying was used to forecast the 100yr flood (design flood). The data from 1950-2099 derived from 31 model and total 97 projections were used to predict the future streamflow. Delta change method is adopted to quantify the amount of future (2050-2099) flood. To determine the extent of flooding 3 scenarios (i) historic design flood, (ii) 500yr flood and (iii) future 100yr flood were routed on a HEC-RAS model, prepared using available terrain data. Some of the climate projection shows extreme increase in future design flood. The future design flood could be more than the historic 500yr flood. At the same time, the extent of flooding could go beyond the historic flood of 0.2% annual probability. This study suggests an approach to quantify the future flood and floodplain using climate model projections. The study would provide helpful information to the facility manager, design engineer and stake holders.

Uncertainties in the projection of species distributions related to general circulation models

PubMed Central

Goberville, Eric; Beaugrand, Grégory; Hautekèete, Nina-Coralie; Piquot, Yves; Luczak, Christophe

2015-01-01

Ecological Niche Models (ENMs) are increasingly used by ecologists to project species potential future distribution. However, the application of such models may be challenging, and some caveats have already been identified. While studies have generally shown that projections may be sensitive to the ENM applied or the emission scenario, to name just a few, the sensitivity of ENM-based scenarios to General Circulation Models (GCMs) has been often underappreciated. Here, using a multi-GCM and multi-emission scenario approach, we evaluated the variability in projected distributions under future climate conditions. We modeled the ecological realized niche (sensu Hutchinson) and predicted the baseline distribution of species with contrasting spatial patterns and representative of two major functional groups of European trees: the dwarf birch and the sweet chestnut. Their future distributions were then projected onto future climatic conditions derived from seven GCMs and four emissions scenarios using the new Representative Concentration Pathways (RCPs) developed for the Intergovernmental Panel on Climate Change (IPCC) AR5 report. Uncertainties arising from GCMs and those resulting from emissions scenarios were quantified and compared. Our study reveals that scenarios of future species distribution exhibit broad differences, depending not only on emissions scenarios but also on GCMs. We found that the between-GCM variability was greater than the between-RCP variability for the next decades and both types of variability reached a similar level at the end of this century. Our result highlights that a combined multi-GCM and multi-RCP approach is needed to better consider potential trajectories and uncertainties in future species distributions. In all cases, between-GCM variability increases with the level of warming, and if nothing is done to alleviate global warming, future species spatial distribution may become more and more difficult to anticipate. When future species spatial distributions are examined, we propose to use a large number of GCMs and RCPs to better anticipate potential trajectories and quantify uncertainties. PMID:25798227

Nitrogen feedbacks increase future terrestrial ecosystem carbon uptake in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Wårlind, D.; Smith, B.; Hickler, T.; Arneth, A.

2014-11-01

Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use LPJ-GUESS, a dynamic vegetation model employing a detailed individual- and patch-based representation of vegetation dynamics, to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one representative "business-as-usual" climate scenario). Single-factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C-N interactions, compared to the C-only version of the model as documented in previous studies using other global models. Under an RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics up to the present. However, during the 21st century, nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contrasts with previous results with other global models that have shown an 8 to 37% decrease in carbon uptake relative to modern baseline conditions. Implications for the plausibility of earlier projections of future terrestrial C dynamics based on C-only models are discussed.

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

DOE PAGES

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

2016-01-01

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

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

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

West Coast atmospheric river climatology in CMIP5 climate models

NASA Astrophysics Data System (ADS)

Warner, M.; Mass, C.; Salathe, E. P.

2015-12-01

In recent years, there has been a flurry of research on how atmospheric river events (ARs) will respond to anthropogenic global warming. This study uses 10 CMIP5 RCP 8.5 climate models to focus on changes in AR frequency, seasonality, and synoptic conditions along the west coast of the United States and is a follow-up to previous work by the same authors (Warner et al. 2015) which investigated expected changes in AR intensity in the same region. There are only very slight changes in annual AR climatology from the end of the last century to the end of this century when considering the most extreme integrated water vapor transport (IVT) events (99th percentile). However, when evaluating by the number of future days exceeding a historical threshold, there are significant increases in extreme IVT events in all months, especially during months when the majority of events take place. The peaks in historical and future frequency occur in similar months given the amount of model variability. Extreme IVT events appear to be occurring slightly earlier in the season, particularly along the northern US coast, and these results are similar to other studies. Spatially, 10-model mean historical composites of IVT reveal canonical AR conditions. At locations farther south, there is less model agreement on the spatial extent and intensity of AR events; whereas farther north, the various models are in agreement. Composites of future events indicate very little spatial change from historical events. The location and orientation of AR events in the historical and future time periods are similar, and the upper-level winds change little over that time period (Warner et al. 2015). This suggests little change in synoptic conditions for approaching ARs. The future-historical difference plots highlight the largest changes expected in the future, namely increases in IVT intensity which are primarily associated with thermodynamic changes related to future integrated water vapor increases due to a warming atmosphere.

Modeling Future Land Use Scenarios in South Korea: Applying the IPCC Special Report on Emissions Scenarios and the SLEUTH Model on a Local Scale

NASA Astrophysics Data System (ADS)

Han, Haejin; Hwang, YunSeop; Ha, Sung Ryong; Kim, Byung Sik

2015-05-01

This study developed three scenarios of future land use/land cover on a local level for the Kyung-An River Basin and its vicinity in South Korea at a 30-m resolution based on the two scenario families of the Intergovernmental Panel on Climate Change (IPCC) Special Report Emissions Scenarios (SRES): A2 and B1, as well as a business-as-usual scenario. The IPCC SRES A2 and B1 were used to define future local development patterns and associated land use change. We quantified the population-driven demand for urban land use for each qualitative storyline and allocated the urban demand in geographic space using the SLEUTH model. The model results demonstrate the possible land use/land cover change scenarios for the years from 2000 to 2070 by examining the broad narrative of each SRES within the context of a local setting, such as the Kyoungan River Basin, constructing narratives of local development shifts and modeling a set of `best guess' approximations of the future land use conditions in the study area. This study found substantial differences in demands and patterns of land use changes among the scenarios, indicating compact development patterns under the SRES B1 compared to the rapid and dispersed development under the SRES A2.

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.

Modeling future land use scenarios in South Korea: applying the IPCC special report on emissions scenarios and the SLEUTH model on a local scale.

PubMed

Han, Haejin; Hwang, YunSeop; Ha, Sung Ryong; Kim, Byung Sik

2015-05-01

This study developed three scenarios of future land use/land cover on a local level for the Kyung-An River Basin and its vicinity in South Korea at a 30-m resolution based on the two scenario families of the Intergovernmental Panel on Climate Change (IPCC) Special Report Emissions Scenarios (SRES): A2 and B1, as well as a business-as-usual scenario. The IPCC SRES A2 and B1 were used to define future local development patterns and associated land use change. We quantified the population-driven demand for urban land use for each qualitative storyline and allocated the urban demand in geographic space using the SLEUTH model. The model results demonstrate the possible land use/land cover change scenarios for the years from 2000 to 2070 by examining the broad narrative of each SRES within the context of a local setting, such as the Kyoungan River Basin, constructing narratives of local development shifts and modeling a set of 'best guess' approximations of the future land use conditions in the study area. This study found substantial differences in demands and patterns of land use changes among the scenarios, indicating compact development patterns under the SRES B1 compared to the rapid and dispersed development under the SRES A2.

The Mechanisms of Manual Therapy in the Treatment of Musculoskeletal Pain: A Comprehensive Model

PubMed Central

Bialosky, Joel E; Bishop, Mark D; Price, Don D; Robinson, Michael E; George, Steven Z

2009-01-01

Prior studies suggest manual therapy (MT) as effective in the treatment of musculoskeletal pain; however, the mechanisms through which MT exerts its effects are not established. In this paper we present a comprehensive model to direct future studies in MT. This model provides visualization of potential individual mechanisms of MT that the current literature suggests as pertinent and provides a framework for the consideration of the potential interaction between these individual mechanisms. Specifically, this model suggests that a mechanical force from MT initiates a cascade of neurophysiological responses from the peripheral and central nervous system which are then responsible for the clinical outcomes. This model provides clear direction so that future studies may provide appropriate methodology to account for multiple potential pertinent mechanisms. PMID:19027342

Interactions of changing climate and shifts in forest composition on stand carbon balance

Treesearch

Chiang Jyh-Min; Louis Iverson; Anantha Prasad; Kim Brown

2006-01-01

Given that climate influences forest biogeographic distribution, many researchers have created models predicting shifts in tree species range with future climate change scenarios. The objective of this study is to investigate the forest carbon consequences of shifts in stand species composition with current and future climate scenarios using such a model.

Forecasting Trends in Disability in a Super-Aging Society: Adapting the Future Elderly Model to Japan.

PubMed

Chen, Brian K; Jalal, Hawre; Hashimoto, Hideki; Suen, Sze-Chuan; Eggleston, Karen; Hurley, Michael; Schoemaker, Lena; Bhattacharya, Jay

2016-12-01

Japan has experienced pronounced population aging, and now has the highest proportion of elderly adults in the world. Yet few projections of Japan's future demography go beyond estimating population by age and sex to forecast the complex evolution of the health and functioning of the future elderly. This study estimates a new state-transition microsimulation model - the Japanese Future Elderly Model (FEM) - for Japan. We use the model to forecast disability and health for Japan's future elderly. Our simulation suggests that by 2040, over 27 percent of Japan's elderly will exhibit 3 or more limitations in IADLs and social functioning; almost one in 4 will experience difficulties with 3 or more ADLs; and approximately one in 5 will suffer limitations in cognitive or intellectual functioning. Since the majority of the increase in disability arises from the aging of the Japanese population, prevention efforts that reduce age-specific morbidity can help reduce the burden of disability but may have only a limited impact on reducing the overall prevalence of disability among Japanese elderly. While both age and morbidity contribute to a predicted increase in disability burden among elderly Japanese in the future, our simulation results suggest that the impact of population aging exceeds the effect of age-specific morbidity on increasing disability in Japan's future.

Forecasting the future risk of Barmah Forest virus disease under climate change scenarios in Queensland, Australia.

PubMed

Naish, Suchithra; Mengersen, Kerrie; Hu, Wenbiao; Tong, Shilu

2013-01-01

Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000-2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland.

A Synoptic Weather Typing Approach and Its application to Assess Climate Change Impacts on Extreme Weather Events at Local Scale in South-Central Canada

NASA Astrophysics Data System (ADS)

Shouquan Cheng, Chad; Li, Qian; Li, Guilong

2010-05-01

The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been successfully applied in Environment Canada for several research projects to analyze climatic change impacts on a number of extreme weather events, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the extreme weather events, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projections of changes in frequency and intensity of future extreme weather events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and a number of linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into each of the three parts of the projects. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. The modeled results from these projects found that the frequency and intensity of future extreme weather events are projected to significantly increase under a changing climate in this century. This talk will introduce these research projects and outline the modeling exercise and result verification process. The major findings on future projections from the studies will be summarized in the presentation as well. One of the major conclusions from the studies is that the procedures (including synoptic weather typing) used in the studies are useful for climate change impact analysis on future extreme weather events. The implication of the significant increases in frequency and intensity of future extreme weather events would be useful to be considered when revising engineering infrastructure design standards and developing adaptation strategies and policies.

Modeling Addictive Consumption as an Infectious Disease*

PubMed Central

Alamar, Benjamin; Glantz, Stanton A.

2011-01-01

The dominant model of addictive consumption in economics is the theory of rational addiction. The addict in this model chooses how much they are going to consume based upon their level of addiction (past consumption), the current benefits and all future costs. Several empirical studies of cigarette sales and price data have found a correlation between future prices and consumption and current consumption. These studies have argued that the correlation validates the rational addiction model and invalidates any model in which future consumption is not considered. An alternative to the rational addiction model is one in which addiction spreads through a population as if it were an infectious disease, as supported by the large body of empirical research of addictive behaviors. In this model an individual's probability of becoming addicted to a substance is linked to the behavior of their parents, friends and society. In the infectious disease model current consumption is based only on the level of addiction and current costs. Price and consumption data from a simulation of the infectious disease model showed a qualitative match to the results of the rational addiction model. The infectious disease model can explain all of the theoretical results of the rational addiction model with the addition of explaining initial consumption of the addictive good. PMID:21339848

Systematic Review of Economic Models Used to Compare Techniques for Detecting Peripheral Arterial Disease.

PubMed

Moloney, Eoin; O'Connor, Joanne; Craig, Dawn; Robalino, Shannon; Chrysos, Alexandros; Javanbakht, Mehdi; Sims, Andrew; Stansby, Gerard; Wilkes, Scott; Allen, John

2018-04-23

Peripheral arterial disease (PAD) is a common condition, in which atherosclerotic narrowing in the arteries restricts blood supply to the leg muscles. In order to support future model-based economic evaluations comparing methods of diagnosis in this area, a systematic review of economic modelling studies was conducted. A systematic literature review was performed in June 2017 to identify model-based economic evaluations of diagnostic tests to detect PAD, with six individual databases searched. The review was conducted in accordance with the methods outlined in the Centre for Reviews and Dissemination's guidance for undertaking reviews in healthcare, and appropriate inclusion criteria were applied. Relevant data were extracted, and studies were quality assessed. Seven studies were included in the final review, all of which were published between 1995 and 2014. There was wide variation in the types of diagnostic test compared. The majority of the studies (six of seven) referenced the sources used to develop their model, and all studies stated and justified the structural assumptions. Reporting of the data within the included studies could have been improved. Only one identified study focused on the cost-effectiveness of a test typically used in primary care. This review brings together all applied modelling methods for tests used in the diagnosis of PAD, which could be used to support future model-based economic evaluations in this field. The limited modelling work available on tests typically used for the detection of PAD in primary care, in particular, highlights the importance of future work in this area.

Utilizing Multi-Ensemble of Downscaled CMIP5 GCMs to Investigate Trends and Spatial and Temporal Extent of Drought in Willamette Basin

NASA Astrophysics Data System (ADS)

Ahmadalipour, A.; Beal, B.; Moradkhani, H.

2015-12-01

Changing climate and potential future increases in global temperature are likely to have impacts on drought characteristics and hydrologic cylce. In this study, we analyze changes in temporal and spatial extent of meteorological and hydrological droughts in future, and their trends. Three statistically downscaled datasets from NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), Multivariate Adaptive Constructed Analogs (MACA), and Bias Correction and Spatial Disagregation (BCSD-PSU) each consisting of 10 CMIP5 Global Climate Models (GCM) are utilized for RCP4.5 and RCP8.5 scenarios. Further, Precipitation Runoff Modeling System (PRMS) hydrologic model is used to simulate streamflow from GCM inputs and assess the hydrological drought characteristics. Standard Precipitation Index (SPI) and Streamflow Drought Index (SDI) are the two indexes used to investigate meteorological and hydrological drought, respectively. Study is done for Willamette Basin with a drainage area of 29,700 km2 accommodating more than 3 million inhabitants and 25 dams. We analyze our study for annual time scale as well as three future periods of near future (2010-2039), intermediate future (2040-2069), and far future (2070-2099). Large uncertainty is found from GCM predictions. Results reveal that meteorological drought events are expected to increase in near future. Severe to extreme drought with large areal coverage and several years of occurance is predicted around year 2030 with the likelihood of exceptional drought for both drought types. SPI is usually showing positive trends, while SDI indicates negative trends in most cases.

Integrating model abstraction into monitoring strategies

USDA-ARS?s Scientific Manuscript database

This study was designed and performed to investigate the opportunities and benefits of integrating model abstraction techniques into monitoring strategies. The study focused on future applications of modeling to contingency planning and management of potential and actual contaminant release sites wi...

Impact Assessment of Global Temperature Perturbations on Urban and Regional Ozone Levels in South Texas

NASA Astrophysics Data System (ADS)

Biswas, Jhumoor; John, Kuruvilla; Farooqui, Zuber

The recent Intergovernmental Panel on Climate Change report predicts significant temperature increases over the century which constitutes the pulse of climate variability in a region. A modeling study was performed to identify the potential impact of temperature perturbations on tropospheric ozone concentrations in South Texas. A future case modeling scenario which incorporates appropriate emission reduction strategies without accounting for climatic inconsistencies was used in this study. The photochemical modeling was undertaken for a high ozone episode of 13-20 September 1999, and a future modeling scenario was projected for ozone episode days in 2007 utilizing the meteorological conditions prevalent in the base year. The temperatures were increased uniformly throughout the simulation domain and through the vertical layers by 2°C, 3°C, 4°C, 5°C, and 6°C, respectively in the future year modeling case. These temperature perturbations represented the outcome of extreme climate change within the study region. Significantly large changes in peak ozone concentrations were predicted by the photochemical model. For the 6°C temperature perturbation, the greatest amplification in the maximum 8-h ozone concentrations within urban areas of the modeling domain was approximately 12 ppb. In addition, transboundary flux from major industrialized urban areas played a major role in supplementing the high ozone concentrations during the perturbed temperature scenarios. The Unites States Environmental Protection Agency (USEPA) is currently proposing stricter 8-h ozone standards. The effect of temperature perturbations on ozone exceedances based on current and potential stringent future National Ambient Air Quality Standards (NAAQS) was also studied. Temperatures had an appreciable spatial impact on the 8-h ozone exceedances with a considerable increase in spatial area exceeding the NAAQS for the 8-h ozone levels within the study region for each successive augmentation in temperature. The number of exceedances of the 8-h ozone standard increased significantly with each degree rise of temperature with the problem becoming even more acute in light of stricter future proposed standards of ozone.

Future streamflow droughts in glacierized catchments: the impact of dynamic glacier modelling and changing thresholds

NASA Astrophysics Data System (ADS)

Van Tiel, Marit; Van Loon, Anne; Wanders, Niko; Vis, Marc; Teuling, Ryan; Stahl, Kerstin

2017-04-01

In glacierized catchments, snowpack and glaciers function as an important storage of water and hydrographs of highly glacierized catchments in mid- and high latitudes thus show a clear seasonality with low flows in winter and high flows in summer. Due to the ongoing climate change we expect this type of storage capacity to decrease with resultant consequences for the discharge regime. In this study we focus on streamflow droughts, here defined as below average water availability specifically in the high flow season, and which methods are most suitable to characterize future streamflow droughts as regimes change. Two glacierized catchments, Nigardsbreen (Norway) and Wolverine (Alaska), are used as case study and streamflow droughts are compared between two periods, 1975-2004 and 2071-2100. Streamflow is simulated with the HBV light model, calibrated on observed discharge and seasonal glacier mass balances, for two climate change scenarios (RCP 4.5 & RCP 8.5). In studies on future streamflow drought often the same variable threshold of the past has been applied to the future, but in regions where a regime shift is expected this method gives severe "droughts" in the historic high-flow period. We applied the new alternative transient variable threshold, a threshold that adapts to the changing hydrological regime and is thus better able to cope with this issue, but has never been thoroughly tested in glacierized catchments. As the glacier area representation in the hydrological modelling can also influence the modelled discharge and the derived streamflow droughts, we evaluated in this study both the difference between the historical variable threshold (HVT) and transient variable threshold (TVT) and two different glacier area conceptualisations (constant area (C) and dynamical area (D)), resulting in four scenarios: HVT-C, HVT-D, TVT-C and TVT-D. Results show a drastic decrease in the number of droughts in the HVT-C scenario due to increased glacier melt. The deficit volume is expected to be up to almost eight times larger in the future compared to the historical period (Wolverine, +674%) in the HVT-D scenario, caused by the regime shift. Using the TVT the drought characteristics between the C and D scenarios and between future and historic droughts are more similar. However, when using the TVT, causing factors of future droughts, anomalies in temperature and/or precipitation, can be analysed. This study highlights the different conclusions that may be drawn on future streamflow droughts in glacierized catchments depending on methodological choices. They could be used to answer different questions: the TVT for analysing drought processes in the future, the HVT to assess changes between historical and future periods, the constant area conceptualisation to analyse the effect of short term climate variability and the dynamical glacier area to model realistic future discharges in glacierized catchments.

National facilities study. Volume 3: Mission and requirements model report

NASA Technical Reports Server (NTRS)

1994-01-01

The National Facility Study (NFS) was initiated in 1992 by Daniel S. Goldin, Administrator of NASA as an initiative to develop a comprehensive and integrated long-term plan for future facilities. The resulting, multi-agency NFS consisted of three Task Groups: Aeronautics, Space Operations, and Space Research and Development (R&D) Task Groups. A fourth group, the Engineering and Cost Analysis Task Group, was subsequently added to provide cross-cutting functions, such as assuring consistency in developing an inventory of space facilities. Space facilities decisions require an assessment of current and future needs. Therefore, the two task groups dealing with space developed a consistent model of future space mission programs, operations and R&D. The model is a middle ground baseline constructed for NFS analytical purposes with excursions to cover potential space program strategies. The model includes three major sectors: DOD, civilian government, and commercial space. The model spans the next 30 years because of the long lead times associated with facilities development and usage. This document, Volume 3 of the final NFS report, is organized along the following lines: Executive Summary -- provides a summary view of the 30-year mission forecast and requirements baseline, an overview of excursions from that baseline that were studied, and organization of the report; Introduction -- provides discussions of the methodology used in this analysis; Baseline Model -- provides the mission and requirements model baseline developed for Space Operations and Space R&D analyses; Excursions from the baseline -- reviews the details of variations or 'excursions' that were developed to test the future program projections captured in the baseline; and a Glossary of Acronyms.

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.

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.

Developmental Programming: State-of-the-Science and Future Directions

PubMed Central

Sutton, Elizabeth F.; Gilmore, L. Anne; Dunger, David B.; Heijmans, Bas T.; Hivert, Marie-France; Ling, Charlotte; Martinez, J. Alfredo; Ozanne, Susan E.; Simmons, Rebecca A.; Szyf, Moshe; Waterland, Robert A.; Redman, Leanne M.; Ravussin, Eric

2016-01-01

Objective On December 8–9, 2014, the Pennington Biomedical Research Center convened a scientific symposium to review the state-of-the-science and future directions for the study of developmental programming of obesity and chronic disease. The objectives of the symposium were to discuss: (i) past and current scientific advances in animal models, population-based cohort studies and human clinical trials, (ii) the state-of-the-science of epigenetic-based research, and (iii) considerations for future studies. Results The overarching goal was to provide a comprehensive assessment of the state of the scientific field, to identify research gaps and opportunities for future research in order to identify and understand the mechanisms contributing to the developmental programming of health and disease. Conclusions Identifying the mechanisms which cause or contribute to developmental programming of future generations will be invaluable to the scientific and medical community. The ability to intervene during critical periods of prenatal and early postnatal life to promote lifelong health is the ultimate goal. Considerations for future research including the use of animal models, the study design in human cohorts with considerations about the timing of the intrauterine exposure and the resulting tissue specific epigenetic signature were extensively discussed and are presented in this meeting summary. PMID:27037645

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

PubMed

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

2018-01-01

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

Evaluation of climatic changes in South-Asia

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

Analysis and modelling of surface Urban Heat Island in 20 Canadian cities under climate and land-cover change.

PubMed

Gaur, Abhishek; Eichenbaum, Markus Kalev; Simonovic, Slobodan P

2018-01-15

Surface Urban Heat Island (SUHI) is an urban climate phenomenon that is expected to respond to future climate and land-use land-cover change. It is important to further our understanding of physical mechanisms that govern SUHI phenomenon to enhance our ability to model future SUHI characteristics under changing geophysical conditions. In this study, SUHI phenomenon is quantified and modelled at 20 cities distributed across Canada. By analyzing MODerate Resolution Imaging Spectroradiometer (MODIS) sensed surface temperature at the cities over 2002-2012, it is found that 16 out of 20 selected cities have experienced a positive SUHI phenomenon while 4 cities located in the prairies region and high elevation locations have experienced a negative SUHI phenomenon in the past. A statistically significant relationship between observed SUHI magnitude and city elevation is also recorded over the observational period. A Physical Scaling downscaling model is then validated and used to downscale future surface temperature projections from 3 GCMs and 2 extreme Representative Concentration Pathways in the urban and rural areas of the cities. Future changes in SUHI magnitudes between historical (2006-2015) and future timelines: 2030s (2026-2035), 2050s (2046-2055), and 2090s (2091-2100) are estimated. Analysis of future projected changes indicate that 15 (13) out of 20 cities can be expected to experience increases in SUHI magnitudes in future under RCP 2.6 (RCP 8.5). A statistically significant relationship between projected future SUHI change and current size of the cities is also obtained. The study highlights the role of city properties (i.e. its size, elevation, and surrounding land-cover) towards shaping their current and future SUHI characteristics. The results from this analysis will help decision-makers to manage Canadian cities more efficiently under rapidly changing geophysical and demographical conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Self-Esteem and Future Orientation Predict Adolescents' Risk Engagement

ERIC Educational Resources Information Center

Jackman, Danielle M.; MacPhee, David

2017-01-01

This study's purpose was to examine the relations among future orientation, self-esteem, and later adolescent risk behaviors, and to compare two mediational models involving self-esteem versus future orientation as mediators. An ethnically diverse sample of 12- to 14-year-olds (N = 862, 54% female, 53% ethnic minority) was assessed longitudinally.…

Time perspectives and convenience food consumption among teenagers in Vietnam: The dual role of hedonic and healthy eating values.

PubMed

Olsen, Svein Ottar; Tuu, Ho Huy

2017-09-01

This study uses the subscales of Consideration of Future Consequences (CFC) to explore the effects of future (CFC-future) and immediate (CFC-immediate) on convenience food consumption among teenagers in Vietnam. Furthermore, we investigate the mediating and dual role of hedonic and healthy eating values in the relationships between CFCs and convenience food consumption. Survey data from 451 teenagers in Central Vietnam and structural equation modelling were used to test the relationships in a proposed theoretical model. The results indicate that while CFC-immediate and hedonic eating value has a positive direct effect, CFC-future and healthy eating value has a negative direct effect on convenience food consumption. The findings also reveal that both CFC-immediate and CFC-future have positive effects on hedonic and healthy eating values. However, this study argues and tests the relative importance of the direct (asymmetric) effects of time perspectives on eating values, and finds that while CFC-future dominate in explaining healthy eating values, CFC-immediate dominate in explaining hedonic eating values. Copyright © 2017 Elsevier Ltd. All rights reserved.

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

NASA Technical Reports Server (NTRS)

Viken, Jeff; Dollyhigh, Samuel; Smith, Jeremy; Trani, Antonio; Baik, Hojong; Hinze, Nicholas; Ashiabor, Senanu

2006-01-01

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Electricity Market Games: How Agent-Based Modeling Can Help under High Penetrations of Variable Generation

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

Gallo, Giulia

Integrating increasingly high levels of variable generation in U.S. electricity markets requires addressing not only power system and grid modeling challenges but also an understanding of how market participants react and adapt to them. Key elements of current and future wholesale power markets can be modeled using an agent-based approach, which may prove to be a useful paradigm for researchers studying and planning for power systems of the future.

Current and future groundwater recharge in West Africa as estimated from a range of coupled climate model outputs

NASA Astrophysics Data System (ADS)

Verhoef, Anne; Cook, Peter; Black, Emily; Macdonald, David; Sorensen, James

2017-04-01

This research addresses the terrestrial water balance for West Africa. Emphasis is on the prediction of groundwater recharge and how this may change in the future, which has relevance to the management of surface and groundwater resources. The study was conducted as part of the BRAVE research project, "Building understanding of climate variability into planning of groundwater supplies from low storage aquifers in Africa - Second Phase", funded under the NERC/DFID/ESRC Programme, Unlocking the Potential of Groundwater for the Poor (UPGro). We used model output data of water balance components (precipitation, surface and subsurface run-off, evapotranspiration and soil moisture content) from ERA-Interim/ERA-LAND reanalysis, CMIP5, and high resolution model runs with HadGEM3 (UPSCALE; Mizielinski et al., 2014), for current and future time-periods. Water balance components varied widely between the different models; variation was particularly large for sub-surface runoff (defined as drainage from the bottom-most soil layer of each model). In-situ data for groundwater recharge obtained from the peer-reviewed literature were compared with the model outputs. Separate off-line model sensitivity studies with key land surface models were performed to gain understanding of the reasons behind the model differences. These analyses were centered on vegetation, and soil hydraulic parameters. The modelled current and future recharge time series that had the greatest degree of confidence were used to examine the spatiotemporal variability in groundwater storage. Finally, the implications for water supply planning were assessed. Mizielinski, M.S. et al., 2014. High-resolution global climate modelling: the UPSCALE project, a large-simulation campaign. Geoscientific Model Development, 7(4), pp.1629-1640.

Reservoir Performance Under Future Climate For Basins With Different Hydrologic Sensitivities

NASA Astrophysics Data System (ADS)

Mateus, M. C.; Tullos, D. D.

2013-12-01

In addition to long-standing uncertainties related to variable inflows and market price of power, reservoir operators face a number of new uncertainties related to hydrologic nonstationarity, changing environmental regulations, and rapidly growing water and energy demands. This study investigates the impact, sensitivity, and uncertainty of changing hydrology on hydrosystem performance across different hydrogeologic settings. We evaluate the performance of reservoirs in the Santiam River basin, including a case study in the North Santiam Basin, with high permeability and extensive groundwater storage, and the South Santiam Basin, with low permeability, little groundwater storage and rapid runoff response. The modeling objective is to address the following study questions: (1) for the two hydrologic regimes, how does the flood management, water supply, and environmental performance of current reservoir operations change under future 2.5, 50 and 97.5 percentile streamflow projections; and (2) how much change in inflow is required to initiate a failure to meet downstream minimum or maximum flows in the future. We couple global climate model results with a rainfall-runoff model and a formal Bayesian uncertainty analysis to simulate future inflow hydrographs as inputs to a reservoir operations model. To evaluate reservoir performance under a changing climate, we calculate reservoir refill reliability, changes in flood frequency, and reservoir time and volumetric reliability of meeting minimum spring and summer flow target. Reservoir performance under future hydrology appears to vary with hydrogeology. We find higher sensitivity to floods for the North Santiam Basin and higher sensitivity to minimum flow targets for the South Santiam Basin. Higher uncertainty is related with basins with a more complex hydrologeology. Results from model simulations contribute to understanding of the reliability and vulnerability of reservoirs to a changing climate.

Predicted Water and Carbon Fluxes as well as Vegetation Distribution on the Korean Peninsula in the Future with the Ecosystem Demography Model version 2

NASA Astrophysics Data System (ADS)

Kim, J. B.; Kim, Y.

2017-12-01

This study investigates how the water and carbon fluxes as well as vegetation distribution on the Korean peninsula would vary with climate change. Ecosystem Demography (ED) Model version 2 (ED2) is used in this study, which is an integrated terrestrial biosphere model that can utilize a set of size- and age- structured partial differential equations that track the changing structure and composition of the plant canopy. With using the vegetation distribution data of Jeju Island, located at the southern part of the Korean Peninsula, ED2 is setup and driven for the past 10 years. Then the results of ED2 are evaluated and adjusted with observed forestry data, i.e., growth and mortality, and the flux tower and MODIS satellite data, i.e., evapotranspiration (ET) and gross primary production (GPP). This adjusted ED2 are used to simulate the water and carbon fluxes as well as vegetation dynamics in the Korean Peninsula for the historical period with evaluating the model against the MODIS satellite data. Finally, the climate scenarios of RCP 2.6 and 6.0 are used to predict the fluxes and vegetation distribution of the Korean Peninsula in the future. With using the state-of-art terrestrial ecosystem model, this study would provide us better understanding of the future ecosystem vulnerability of the Korean Peninsula. AcknowledgementsThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800) and by the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180. This work was also supported by the Yonsei University Future-leading Research Initiative of 2015(2016-22-0061).

An empirical study on information spillover effects between the Chinese copper futures market and spot market

NASA Astrophysics Data System (ADS)

Liu, Xiangli; Cheng, Siwei; Wang, Shouyang; Hong, Yongmiao; Li, Yi

2008-02-01

This study employs a parametric approach based on TGARCH and GARCH models to estimate the VaR of the copper futures market and spot market in China. Considering the short selling mechanism in the futures market, the paper introduces two new notions: upside VaR and extreme upside risk spillover. And downside VaR and upside VaR are examined by using the above approach. Also, we use Kupiec’s [P.H. Kupiec, Techniques for verifying the accuracy of risk measurement models, Journal of Derivatives 3 (1995) 73-84] backtest to test the power of our approaches. In addition, we investigate information spillover effects between the futures market and the spot market by employing a linear Granger causality test, and Granger causality tests in mean, volatility and risk respectively. Moreover, we also investigate the relationship between the futures market and the spot market by using a test based on a kernel function. Empirical results indicate that there exist significant two-way spillovers between the futures market and the spot market, and the spillovers from the futures market to the spot market are much more striking.

Prestoration: Using species in restoration that will persist now and into the future

USGS Publications Warehouse

Butterfield, B.J.; Copeland, Stella; Munson, Seth M.; Roybal, C.M.; Wood, Troy E.

2017-01-01

Climate change presents new challenges for selecting species for restoration. If migration fails to keep pace with climate change, as models predict, the most suitable sources for restoration may not occur locally at all. To address this issue we propose a strategy of “prestoration”: utilizing species in restoration for which a site represents suitable habitat now and into the future. Using the Colorado Plateau, USA as a case study, we assess the ability of grass species currently used regionally in restoration to persist into the future using projections of ecological niche models (or climate envelope models) across a suite of climate change scenarios. We then present a technique for identifying new species that best compensate for future losses of suitable habitat by current target species. We found that the current suite of species, selected by a group of experts, is predicted to perform reasonably well in the short-term, but that losses of prestorable habitat by mid-century would approach 40%. Using an algorithm to identify additional species, we found that fewer than ten species could compensate for nearly all of the losses incurred by the current target species. This case study highlights the utility of integrating ecological niche modeling and future climate forecasts to predict the utility of species in restoring under climate change across a wide range of spatial and temporal scales.

Potential effects of climate change on streamflow for seven watersheds in eastern and central Montana

USGS Publications Warehouse

Chase, Katherine J.; Haj, Adel E.; Regan, R. Steven; Viger, Roland J.

2016-01-01

Study regionEastern and central Montana.Study focusFish in Northern Great Plains streams tolerate extreme conditions including heat, cold, floods, and drought; however changes in streamflow associated with long-term climate change may render some prairie streams uninhabitable for current fish species. To better understand future hydrology of these prairie streams, the Precipitation-Runoff Modeling System model and output from the RegCM3 Regional Climate model were used to simulate streamflow for seven watersheds in eastern and central Montana, for a baseline period (water years 1982–1999) and three future periods: water years 2021–2038 (2030 period), 2046–2063 (2055 period), and 2071–2088 (2080 period).New hydrological insights for the regionProjected changes in mean annual and mean monthly streamflow vary by the RegCM3 model selected, by watershed, and by future period. Mean annual streamflows for all future periods are projected to increase (11–21%) for two of the four central Montana watersheds: Middle Musselshell River and Cottonwood Creek. Mean annual streamflows for all future periods are projected to decrease (changes of −24 to −75%) for Redwater River watershed in eastern Montana. Mean annual streamflows are projected to increase slightly (2–15%) for the 2030 period and decrease (changes of −16 to −44%) for the 2080 period for the four remaining watersheds.

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.

A model for interprovincial air pollution control based on futures prices.

PubMed

Zhao, Laijun; Xue, Jian; Gao, Huaizhu Oliver; Li, Changmin; Huang, Rongbing

2014-05-01

Based on the current status of research on tradable emission rights futures, this paper introduces basic market-related assumptions for China's interprovincial air pollution control problem. The authors construct an interprovincial air pollution control model based on futures prices: the model calculated the spot price of emission rights using a classic futures pricing formula, and determined the identities of buyers and sellers for various provinces according to a partitioning criterion, thereby revealing five trading markets. To ensure interprovincial cooperation, a rational allocation result for the benefits from this model was achieved using the Shapley value method to construct an optimal reduction program and to determine the optimal annual decisions for each province. Finally, the Beijing-Tianjin-Hebei region was used as a case study, as this region has recently experienced serious pollution. It was found that the model reduced the overall cost of reducing SO2 pollution. Moreover, each province can lower its cost for air pollution reduction, resulting in a win-win solution. Adopting the model would therefore enhance regional cooperation and promote the control of China's air pollution. The authors construct an interprovincial air pollution control model based on futures prices. The Shapley value method is used to rationally allocate the cooperation benefit. Interprovincial pollution control reduces the overall reduction cost of SO2. Each province can lower its cost for air pollution reduction by cooperation.

Predicting future land cover change and its impact on streamflow and sediment load in a trans-boundary river basin

NASA Astrophysics Data System (ADS)

Wang, Jie; Wang, Hao; Ning, Shaowei; Hiroshi, Ishidaira

2018-06-01

Sediment load can provide very important perspective on erosion of river basin. The changes of human-induced vegetation cover, such as deforestation or afforestation, affect sediment yield process of a catchment. We have already evaluated that climate change and land cover change changed the historical streamflow and sediment yield, and land cover change is the main factor in Red river basin. But future streamflow and sediment yield changes under potential future land cover change scenario still have not been evaluated. For this purpose, future scenario of land cover change is developed based on historical land cover changes and land change model (LCM). In addition, future leaf area index (LAI) is simulated by ecological model (Biome-BGC) based on future land cover scenario. Then future scenarios of land cover change and LAI are used to drive hydrological model and new sediment rating curve. The results of this research provide information that decision-makers need in order to promote water resources planning efforts. Besides that, this study also contributes a basic framework for assessing climate change impacts on streamflow and sediment yield that can be applied in the other basins around the world.

Several thoughts for using new satellite remote sensing and global modeling for aerosol and cloud climate studies

NASA Astrophysics Data System (ADS)

Nakajima, Teruyuki; Hashimoto, Makiko; Takenaka, Hideaki; Goto, Daisuke; Oikawa, Eiji; Suzuki, Kentaroh; Uchida, Junya; Dai, Tie; Shi, Chong

2017-04-01

The rapid growth of satellite remote sensing technologies in the last two decades widened the utility of satellite data for understanding climate impacts of aerosols and clouds. The climate modeling community also has received the benefit of the earth observation and nowadays closed-collaboration of the two communities make us possible to challenge various applications for societal problems, such as for global warming and global-scale air pollution and others. I like to give several thoughts of new algorithm developments, model use of satellite data for climate impact studies and societal applications related with aerosols and clouds. Important issues are 1) Better aerosol detection and solar energy application using expanded observation ability of the third generation geostationary satellites, i.e. Himawari-8, GOES-R and future MTG, 2) Various observation functions by directional, polarimetric, and high resolution near-UV band by MISR, POLDER&PARASOL, GOSAT/CAI and future GOSAT2/CAI2, 3) Various applications of general purpose-imagers, MODIS, VIIRS and future GCOM-C/SGLI, and 4) Climate studies of aerosol and cloud stratification and convection with active and passive sensors, especially climate impact of BC aerosols using CLOUDSAT&CALIPSO and future Earth Explorer/EarthCARE.

Evaluating Behavioral Economic Models of Heavy Drinking Among College Students.

PubMed

Acuff, Samuel F; Soltis, Kathryn E; Dennhardt, Ashley A; Berlin, Kristoffer S; Murphy, James G

2018-05-14

Heavy drinking among college students is a significant public health concern that can lead to profound social and health consequences, including alcohol use disorder. Behavioral economics posits that low future orientation and high valuation of alcohol (alcohol demand) combined with deficits in alternative reinforcement increase the likelihood of alcohol misuse (Bickel et al., 2011). Despite this, no study has examined the incremental utility of all three variables simultaneously in a comprehensive model METHOD: The current study uses structural equation modeling to test the associations between behavioral economic variables - alcohol demand (latent), future orientation (measured with a delay discounting task and the Consideration of Future Consequences (CFC) scale), and proportionate substance-related reinforcement - and alcohol consumption and problems among 393 heavy drinking college students. Two models are tested: 1) an iteration of the reinforcer pathology model that includes an interaction between future orientation and alcohol demand; and 2) an alternative model evaluating the interconnectedness of behavioral economic variables in predicting problematic alcohol use RESULTS: The interaction effects in model 1 were nonsignificant. Model 2 suggests that greater alcohol demand and proportionate substance-related reinforcement is associated with greater alcohol consumption and problems. Further, CFC was associated with alcohol-related problems and lower proportionate substance-related reinforcement but was not significantly associated with alcohol consumption or alcohol demand. Finally, greater proportionate substance-related reinforcement was associated with greater alcohol demand CONCLUSIONS: Our results support the validity of the behavioral economic reinforcer pathology model as applied to young adult heavy drinking. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Simulation of extreme rainfall and projection of future changes using the GLIMCLIM model

NASA Astrophysics Data System (ADS)

Rashid, Md. Mamunur; Beecham, Simon; Chowdhury, Rezaul Kabir

2017-10-01

In this study, the performance of the Generalized LInear Modelling of daily CLImate sequence (GLIMCLIM) statistical downscaling model was assessed to simulate extreme rainfall indices and annual maximum daily rainfall (AMDR) when downscaled daily rainfall from National Centers for Environmental Prediction (NCEP) reanalysis and Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCM) (four GCMs and two scenarios) output datasets and then their changes were estimated for the future period 2041-2060. The model was able to reproduce the monthly variations in the extreme rainfall indices reasonably well when forced by the NCEP reanalysis datasets. Frequency Adapted Quantile Mapping (FAQM) was used to remove bias in the simulated daily rainfall when forced by CMIP5 GCMs, which reduced the discrepancy between observed and simulated extreme rainfall indices. Although the observed AMDR were within the 2.5th and 97.5th percentiles of the simulated AMDR, the model consistently under-predicted the inter-annual variability of AMDR. A non-stationary model was developed using the generalized linear model for local, shape and scale to estimate the AMDR with an annual exceedance probability of 0.01. The study shows that in general, AMDR is likely to decrease in the future. The Onkaparinga catchment will also experience drier conditions due to an increase in consecutive dry days coinciding with decreases in heavy (>long term 90th percentile) rainfall days, empirical 90th quantile of rainfall and maximum 5-day consecutive total rainfall for the future period (2041-2060) compared to the base period (1961-2000).

Cargo Logistics Airlift Systems Study (CLASS). Volume 2: Case study approach and results

NASA Technical Reports Server (NTRS)

Burby, R. J.; Kuhlman, W. H.

1978-01-01

Models of transportation mode decision making were developed. The user's view of the present and future air cargo systems is discussed. Issues summarized include: (1) organization of the distribution function; (2) mode choice decision making; (3) air freight system; and (4) the future of air freight.

Projecting Electricity Demand in 2050

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

Hostick, Donna J.; Belzer, David B.; Hadley, Stanton W.

2014-07-01

This paper describes the development of end-use electricity projections and load curves that were developed for the Renewable Electricity (RE) Futures Study (hereafter RE Futures), which explored the prospect of higher percentages (30% - 90%) of total electricity generation that could be supplied by renewable sources in the United States. As input to RE Futures, two projections of electricity demand were produced representing reasonable upper and lower bounds of electricity demand out to 2050. The electric sector models used in RE Futures required underlying load profiles, so RE Futures also produced load profile data in two formats: 8760 hourly datamore » for the year 2050 for the GridView model, and in 2-year increments for 17 time slices as input to the Regional Energy Deployment System (ReEDS) model. The process for developing demand projections and load profiles involved three steps: discussion regarding the scenario approach and general assumptions, literature reviews to determine readily available data, and development of the demand curves and load profiles.« less

Future orientation in the self-system: possible selves, self-regulation, and behavior.

PubMed

Hoyle, Rick H; Sherrill, Michelle R

2006-12-01

Possible selves are representations of the self in the future. Early theoretical accounts of the construct suggested that possible selves directly influence motivation and behavior. We propose an alternative view of possible selves as a component in self-regulatory processes through which motivation and behavior are influenced. We demonstrate the advantages of this conceptualization in two studies that test predictions generated from theoretical models of self-regulation in which the possible selves construct could be embedded. In one study, we show how viewing possible selves as a source of behavioral standards in a control-process model of self-regulation yields support for a set of predictions about the influence of possible selves on current behavior. In the other study, we examine possible selves in the context of an interpersonal model of self-regulation, showing strong evidence of concern for relational value in freely generated hoped-for and feared selves. These findings suggest that the role of possible selves in motivation and behavior can be profitably studied in models that fully specify the process of self-regulation and that those models can be enriched by a consideration of future-oriented self-representations. We offer additional recommendations for strengthening research on possible selves and self-regulation.

Future trends in computer waste generation in India.

PubMed

Dwivedy, Maheshwar; Mittal, R K

2010-11-01

The objective of this paper is to estimate the future projection of computer waste in India and to subsequently analyze their flow at the end of their useful phase. For this purpose, the study utilizes the logistic model-based approach proposed by Yang and Williams to forecast future trends in computer waste. The model estimates future projection of computer penetration rate utilizing their first lifespan distribution and historical sales data. A bounding analysis on the future carrying capacity was simulated using the three parameter logistic curve. The observed obsolete generation quantities from the extrapolated penetration rates are then used to model the disposal phase. The results of the bounding analysis indicate that in the year 2020, around 41-152 million units of computers will become obsolete. The obsolete computer generation quantities are then used to estimate the End-of-Life outflows by utilizing a time-series multiple lifespan model. Even a conservative estimate of the future recycling capacity of PCs will reach upwards of 30 million units during 2025. Apparently, more than 150 million units could be potentially recycled in the upper bound case. However, considering significant future investment in the e-waste recycling sector from all stakeholders in India, we propose a logistic growth in the recycling rate and estimate the requirement of recycling capacity between 60 and 400 million units for the lower and upper bound case during 2025. Finally, we compare the future obsolete PC generation amount of the US and India. Copyright © 2010 Elsevier Ltd. All rights reserved.

An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change

PubMed Central

Casajus, Nicolas; Périé, Catherine; Logan, Travis; Lambert, Marie-Claude; de Blois, Sylvie; Berteaux, Dominique

2016-01-01

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one. PMID:27015274

An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change.

PubMed

Casajus, Nicolas; Périé, Catherine; Logan, Travis; Lambert, Marie-Claude; de Blois, Sylvie; Berteaux, Dominique

2016-01-01

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.

Assessing the impacts of climate change on future water resources: a methodological approach based on equiratio CDF-matching and vine copula

NASA Astrophysics Data System (ADS)

Pham, Minh Tu; Vernieuwe, Hilde; De Baets, Bernard; Verhoest, Niko E. C.

2016-04-01

In this study, the impacts of climate change on future river discharge are evaluated using equiratio CDF-matching and a stochastic copula-based evapotranspiration generator. In recent years, much effort has been dedicated to improve the performances of RCMs outputs, i.e. the downscaled precipitation and temperature, to use in regional studies. However, these outputs usually suffer from bias due to the fact that many important small-scale processes, e.g. the representations of clouds and convection, are not represented explicitly within the models. To solve this problem, several bias correction techniques are developed. In this study, an advanced quantile bias approach called equiratio cumulative distribution function matching (EQCDF) is applied for the outputs from three RCMs for central Belgium, i.e. daily precipitation, temperature and evapotranspiration, for the current (1961-1990) and future climate (2071-2100). The rescaled precipitation and temperature are then used to simulate evapotranspiration via a stochastic copula-based model in which the statistical dependence between evapotranspiration, temperature and precipitation is described by a three-dimensional vine copula. The simulated precipitation and stochastic evapotranspiration are then used to model discharge under present and future climate. To validate, the observations of daily precipitation, temperature and evapotranspiration during 1961 - 1990 in Uccle, Belgium are used. It is found that under current climate, the basic properties of discharge, e.g. mean and frequency distribution, are well modelled; however there is an overestimation of the extreme discharges with return periods higher than 10 years. For the future climate change, compared with historical events, a considerable increase of the discharge magnitude and the number of extreme events is estimated for the studied area in the time period of 2071-2100.

Forecasting the Future Risk of Barmah Forest Virus Disease under Climate Change Scenarios in Queensland, Australia

PubMed Central

Naish, Suchithra; Mengersen, Kerrie; Hu, Wenbiao; Tong, Shilu

2013-01-01

Background Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. Methods/Principal Findings We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000–2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. Conclusions/Significance We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland. PMID:23690959

Forecasting Trends in Disability in a Super-Aging Society: Adapting the Future Elderly Model to Japan

PubMed Central

Chen, Brian K.; Jalal, Hawre; Hashimoto, Hideki; Suen, Sze-chuan; Eggleston, Karen; Hurley, Michael; Schoemaker, Lena; Bhattacharya, Jay

2016-01-01

Japan has experienced pronounced population aging, and now has the highest proportion of elderly adults in the world. Yet few projections of Japan’s future demography go beyond estimating population by age and sex to forecast the complex evolution of the health and functioning of the future elderly. This study estimates a new state-transition microsimulation model – the Japanese Future Elderly Model (FEM) – for Japan. We use the model to forecast disability and health for Japan’s future elderly. Our simulation suggests that by 2040, over 27 percent of Japan’s elderly will exhibit 3 or more limitations in IADLs and social functioning; almost one in 4 will experience difficulties with 3 or more ADLs; and approximately one in 5 will suffer limitations in cognitive or intellectual functioning. Since the majority of the increase in disability arises from the aging of the Japanese population, prevention efforts that reduce age-specific morbidity can help reduce the burden of disability but may have only a limited impact on reducing the overall prevalence of disability among Japanese elderly. While both age and morbidity contribute to a predicted increase in disability burden among elderly Japanese in the future, our simulation results suggest that the impact of population aging exceeds the effect of age-specific morbidity on increasing disability in Japan’s future. PMID:28580275

Adaptation to floods in future climate: a practical approach

NASA Astrophysics Data System (ADS)

Doroszkiewicz, Joanna; Romanowicz, Renata; Radon, Radoslaw; Hisdal, Hege

2016-04-01

In this study some aspects of the application of the 1D hydraulic model are discussed with a focus on its suitability for flood adaptation under future climate conditions. The Biała Tarnowska catchment is used as a case study. A 1D hydraulic model is developed for the evaluation of inundation extent and risk maps in future climatic conditions. We analyse the following flood indices: (i) extent of inundation area; (ii) depth of water on flooded land; (iii) the flood wave duration; (iv) the volume of a flood wave over the threshold value. In this study we derive a model cross-section geometry following the results of primary research based on a 500-year flood inundation extent. We compare two methods of localisation of cross-sections from the point of view of their suitability to the derivation of the most precise inundation outlines. The aim is to specify embankment heights along the river channel that would protect the river valley in the most vulnerable locations under future climatic conditions. We present an experimental design for scenario analysis studies and uncertainty reduction options for future climate projections obtained from the EUROCORDEX project. Acknowledgements: This work was supported by the project CHIHE (Climate Change Impact on Hydrological Extremes), carried out in the Institute of Geophysics Polish Academy of Sciences, funded by Norway Grants (contract No. Pol-Nor/196243/80/2013). The hydro-meteorological observations were provided by the Institute of Meteorology and Water Management (IMGW), Poland.

Back to "the Future": Evidence of a Bifactor Solution for Scores on the Consideration of Future Consequences Scale.

PubMed

McKay, Michael T; Morgan, Grant B; van Exel, N Job; Worrell, Frank C

2015-01-01

Despite its widespread use, disagreement remains regarding the structure of the Consideration of Future Consequences Scale (CFCS). In particular there is disagreement regarding whether the scale assesses future orientation as a unidimensional or multidimensional (immediate and future) construct. Using 2 samples of high school students in the United Kingdom, 4 models were tested. The totality of results including item loadings, goodness-of-fit indexes, and reliability estimates all supported the bifactor model, suggesting that the 2 hypothesized factors are better understood as grouping or method factors rather than as representative of latent constructs. Accordingly this study supports the unidimensionality of the CFCS and the scoring of all 12 items to produce a global future orientation score. Researchers intending to use the CFCS, and those with existing data, are encouraged to examine a bifactor solution for the scale.

Uncertainties in discharge projections in consequence of climate change

NASA Astrophysics Data System (ADS)

Liebert, J.; Düthmann, D.; Berg, P.; Feldmann, H.; Ihringer, J.; Kunstmann, H.; Merz, B.; Ott, I.; Schädler, G.; Wagner, S.

2012-04-01

The fourth assessment report of the IPCC summarizes possible effects of the global climate change. For Europe an increasing variability of temperature and precipitation is expected. While the increasing temperature is projected almost uniformly for Europe, for precipitation the models indicate partly heterogeneous tendencies. In order to maintain current safety-standards in the infrastructure of our various water management systems, the possible future floods discharges are very often a central question. In the planning and operation of water infrastructure systems uncertainties considerations have an important function. In times of climate change the analyses of measured historical gauge data (normally 30 - 80 years) are not sufficient enough, because even significant trends are only valid in the analyzed time period and extrapolations are exceedingly difficult. Therefore combined climate and hydrological modeling for scenario based projections become more and more popular. Regarding that adaptation measures in water infrastructure are in general very time-consuming and cost intensive qualified questions to the variability and uncertainty of model based results are important as well. The CEDIM-Project "Flood hazards in a changing climate" is focusing on both: future changes in flood discharge and assess the uncertainties that are involved in such model based future predictions. In detail the study bases on an ensemble of hydrological model (HM) simulations in 3 representative small to medium sized German river catchments (Ammer, Mulde and Ruhr). The meteorological Input bases on 2 high resolution (7 km) regional climate models (RCM) driven by 2 global climate models (GCM) for the near future (2021 - 2050) following the A1B emission scenario (SRES). Two of the catchments (Ruhr and Mulde) have sub-mountainous and one (Ammer) has alpine character. Besides analyzing the future changes in discharge in the catchments, the describing and potential quantification of the variability of the results, based on the different driving data, regionalization methods, spatial resolutions and model types, is one main goal of the study and should stay in the focus of the poster. The general result is a large variability in the discharge projection. The identified variabilities are in the annual regime mainly attributable to different causes in the used model chain (GCM-RCM-HM). In winter the global climate models (GCM) bring the main uncertainties in the future projection. In summer the main variability refers to the meteorological downscaling to the regional scale (RCM) in combination with the hydrological modeling (HM). But with an appropriate ensemble statistic are despite the large variabilities mean future tendencies detectable. The Ruhr catchment shows tendencies to future higher flood discharges and in the Ammer and Mulde catchments are no significant changes expected.

Temperature and precipitation in the context of the annual cycle over Asia: Model evaluation and future change

NASA Astrophysics Data System (ADS)

Moon, Suyeon; Ha, Kyung-Ja

2017-05-01

Since the early or late arrival of monsoon rainfall can be devastating to agriculture and economy, the prediction of the onset of monsoon is a very important issue. The Asian monsoon is characterized by a strong annual cycle with rainy summer and dry winter. Nevertheless, most of monsoon studies have focused on the seasonal-mean of temperature and precipitation. The present study aims to evaluate a total of 27 coupled models that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) for projection of the time evolution and the intensity of Asian monsoon on the basis of the annual cycle of temperature and precipitation. And future changes of onset, retreat, and intensity of monsoon are analyzed. Four models for good seasonal-mean (GSM) and good harmonic (GH) groups, respectively, are selected. GSM is based on the seasonal-mean of temperature and precipitation in summer and winter, and GH is based on the annual cycle of temperature and precipitation which represents a characteristic of the monsoon. To compare how well the time evolution of the monsoon is simulated in each group, the onset, retreat, and duration of Asian monsoon are examined. The highest pattern correlation coefficient (PCC) of onset, retreat, and duration between the reanalysis data and model outputs demonstrates that GH models' MME predicts time evolution of monsoon most precisely, with PCC values of 0.80, 0.52, and 0.63, respectively. To predict future changes of the monsoon, the representative concentration pathway 4.5 (RCP 4.5) experiments for the period of 2073-2099 are compared with historical simulations for the period of 1979-2005 from CMIP5 using GH models' MME. The Asian monsoon domain is expanded by 22.6% in the future projection. The onset date in the future is advanced over most parts of Asian monsoon region. The duration of summer Asian monsoon in the future projection will be lengthened by up to 2 pentads over the Asian monsoon region, as a result of advanced onset. The Asian monsoon intensity becomes stronger with the passage of time. This study has important implication for assessment of CMIP5 models in terms of the prediction of time evolution and intensity of Asian monsoon based on the annual cycle of temperature and precipitation.

Exploring triplet-quadruplet fermionic dark matter at the LHC and future colliders

NASA Astrophysics Data System (ADS)

Wang, Jin-Wei; Bi, Xiao-Jun; Xiang, Qian-Fei; Yin, Peng-Fei; Yu, Zhao-Huan

2018-02-01

We study the signatures of the triplet-quadruplet dark matter model at the LHC and future colliders, including the 100 TeV Super Proton-Proton Collider and the 240 GeV Circular Electron Positron Collider. The dark sector in this model contains one fermionic electroweak triplet and two fermionic quadruplets, which have two kinds of Yukawa couplings to the Higgs doublet. Electroweak production signals of the dark sector fermions in the monojet+ ET, disappearing track, and multilepton+ET channels at the LHC and the Super Proton-Proton Collider are investigated. Moreover, we study the loop effects of this model on the Circular Electron Positron Collider precision measurements of e+e-→Z h and h →γ γ . We find that most of the parameter regions allowed by the observed dark matter relic density will be well explored by such direct and indirect searches at future colliders.

The Future Impact of Vietnam Era Veterans on Inpatient Acute Care and Mental Health Product Lines at a Veterans Affairs Medical Center

DTIC Science & Technology

2000-06-20

smoothing and regression which includes curve fitting are two principle forecasting model types utilized in the vast majority of forecasting applications ... model were compared against the VA Office of Policy and Planning forecasting study commissioned with the actuarial firm of Milliman & Robertson (M & R... Application to the Veterans Healthcare System The development of a model to forecast future VEV needs, utilization, and cost of the Acute Care and

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.

Projecting future precipitation and temperature at sites with diverse climate through multiple statistical downscaling schemes

NASA Astrophysics Data System (ADS)

Vallam, P.; Qin, X. S.

2017-10-01

Anthropogenic-driven climate change would affect the global ecosystem and is becoming a world-wide concern. Numerous studies have been undertaken to determine the future trends of meteorological variables at different scales. Despite these studies, there remains significant uncertainty in the prediction of future climates. To examine the uncertainty arising from using different schemes to downscale the meteorological variables for the future horizons, projections from different statistical downscaling schemes were examined. These schemes included statistical downscaling method (SDSM), change factor incorporated with LARS-WG, and bias corrected disaggregation (BCD) method. Global circulation models (GCMs) based on CMIP3 (HadCM3) and CMIP5 (CanESM2) were utilized to perturb the changes in the future climate. Five study sites (i.e., Alice Springs, Edmonton, Frankfurt, Miami, and Singapore) with diverse climatic conditions were chosen for examining the spatial variability of applying various statistical downscaling schemes. The study results indicated that the regions experiencing heavy precipitation intensities were most likely to demonstrate the divergence between the predictions from various statistical downscaling methods. Also, the variance computed in projecting the weather extremes indicated the uncertainty derived from selection of downscaling tools and climate models. This study could help gain an improved understanding about the features of different downscaling approaches and the overall downscaling uncertainty.

Forecasting of future earthquakes in the northeast region of India considering energy released concept

NASA Astrophysics Data System (ADS)

Zarola, Amit; Sil, Arjun

2018-04-01

This study presents the forecasting of time and magnitude size of the next earthquake in the northeast India, using four probability distribution models (Gamma, Lognormal, Weibull and Log-logistic) considering updated earthquake catalog of magnitude Mw ≥ 6.0 that occurred from year 1737-2015 in the study area. On the basis of past seismicity of the region, two types of conditional probabilities have been estimated using their best fit model and respective model parameters. The first conditional probability is the probability of seismic energy (e × 1020 ergs), which is expected to release in the future earthquake, exceeding a certain level of seismic energy (E × 1020 ergs). And the second conditional probability is the probability of seismic energy (a × 1020 ergs/year), which is expected to release per year, exceeding a certain level of seismic energy per year (A × 1020 ergs/year). The logarithm likelihood functions (ln L) were also estimated for all four probability distribution models. A higher value of ln L suggests a better model and a lower value shows a worse model. The time of the future earthquake is forecasted by dividing the total seismic energy expected to release in the future earthquake with the total seismic energy expected to release per year. The epicentre of recently occurred 4 January 2016 Manipur earthquake (M 6.7), 13 April 2016 Myanmar earthquake (M 6.9) and the 24 August 2016 Myanmar earthquake (M 6.8) are located in zone Z.12, zone Z.16 and zone Z.15, respectively and that are the identified seismic source zones in the study area which show that the proposed techniques and models yield good forecasting accuracy.

Long Term Persistence of Preschool Intervention on Children's Mathematical Development: Results from the German Model Project "Kindergarten of the Future in Bavaria"

ERIC Educational Resources Information Center

Lehrl, Simone; Kluczniok, Katharina; Rossbach, Hans-Guenther; Anders, Yvonne

2017-01-01

The present study examines how attending the German model project "Kindergarten of the Future in Bavaria" (KiDZ), which provided 138 children (aged 3 to 6) with traditional preschool stimulation combined with cognitive and domain-specific stimulation, is associated with children's competencies in mathematics over time to age 12 compared…

Future projections of extreme precipitation using Advanced Weather Generator (AWE-GEN) over Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Syafrina, A. H.; Zalina, M. D.; Juneng, L.

2014-09-01

A stochastic downscaling methodology known as the Advanced Weather Generator, AWE-GEN, has been tested at four stations in Peninsular Malaysia using observations available from 1975 to 2005. The methodology involves a stochastic downscaling procedure based on a Bayesian approach. Climate statistics from a multi-model ensemble of General Circulation Model (GCM) outputs were calculated and factors of change were derived to produce the probability distribution functions (PDF). New parameters were obtained to project future climate time series. A multi-model ensemble was used in this study. The projections of extreme precipitation were based on the RCP 6.0 scenario (2081-2100). The model was able to simulate both hourly and 24-h extreme precipitation, as well as wet spell durations quite well for almost all regions. However, the performance of GCM models varies significantly in all regions showing high variability of monthly precipitation for both observed and future periods. The extreme precipitation for both hourly and 24-h seems to increase in future, while extreme of wet spells remain unchanged, up to the return periods of 10-40 years.

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

NASA Technical Reports Server (NTRS)

Viken, Jeff; Dollyhigh, Samuel; Smith, Jeremy; Trani, Antonio; Baik, Hojong; Hinze, Nicholas; Ashiabor, Senanu

2006-01-01

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075

USGS Publications Warehouse

Sohl, Terry L.

2014-01-01

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be "suitable" for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges.

The Relative Impacts of Climate and Land-Use Change on Conterminous United States Bird Species from 2001 to 2075

PubMed Central

Sohl, Terry L.

2014-01-01

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be “suitable” for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges. PMID:25372571

Simulating Future Changes in Spatio-temporal Precipitation by Identifying and Characterizing Individual Rainstorm Events

NASA Astrophysics Data System (ADS)

Chang, W.; Stein, M.; Wang, J.; Kotamarthi, V. R.; Moyer, E. J.

2015-12-01

A growing body of literature suggests that human-induced climate change may cause significant changes in precipitation patterns, which could in turn influence future flood levels and frequencies and water supply and management practices. Although climate models produce full three-dimensional simulations of precipitation, analyses of model precipitation have focused either on time-averaged distributions or on individual timeseries with no spatial information. We describe here a new approach based on identifying and characterizing individual rainstorms in either data or model output. Our approach enables us to readily characterize important spatio-temporal aspects of rainstorms including initiation location, intensity (mean and patterns), spatial extent, duration, and trajectory. We apply this technique to high-resolution precipitation over the continental U.S. both from radar-based observations (NCEP Stage IV QPE product, 1-hourly, 4 km spatial resolution) and from model runs with dynamical downscaling (WRF regional climate model, 3-hourly, 12 km spatial resolution). In the model studies we investigate the changes in storm characteristics under a business-as-usual warming scenario to 2100 (RCP 8.5). We find that in these model runs, rainstorm intensity increases as expected with rising temperatures (approximately 7%/K, following increased atmospheric moisture content), while total precipitation increases by a lesser amount (3%/K), consistent with other studies. We identify for the first time the necessary compensating mechanism: in these model runs, individual precipitation events become smaller. Other aspects are approximately unchanged in the warmer climate. Because these spatio-temporal changes in rainfall patterns would impact regional hydrology, it is important that they be accurately incorporated into any impacts assessment. For this purpose we have developed a methodology for producing scenarios of future precipitation that combine observational data and model-projected changes. We statistically describe the future changes in rainstorm characteristics suggested by the WRF model and apply those changes to observational data. The resulting high spatial and temporal resolution scenarios have immediate applications for impacts assessment and adaptation studies.

Uncertainty of a hydrological climate change impact assessment - Is it really all about climate uncertainty?

NASA Astrophysics Data System (ADS)

Honti, Mark; Reichert, Peter; Scheidegger, Andreas; Stamm, Christian

2013-04-01

Climate change impact assessments have become more and more popular in hydrology since the middle 1980's with another boost after the publication of the IPCC AR4 report. During hundreds of impact studies a quasi-standard methodology emerged, which is mainly shaped by the growing public demand for predicting how water resources management or flood protection should change in the close future. The ``standard'' workflow considers future climate under a specific IPCC emission scenario simulated by global circulation models (GCMs), possibly downscaled by a regional climate model (RCM) and/or a stochastic weather generator. The output from the climate models is typically corrected for bias before feeding it into a calibrated hydrological model, which is run on the past and future meteorological data to analyse the impacts of climate change on the hydrological indicators of interest. The impact predictions are as uncertain as any forecast that tries to describe the behaviour of an extremely complex system decades into the future. Future climate predictions are uncertain due to the scenario uncertainty and the GCM model uncertainty that is obvious on finer resolution than continental scale. Like in any hierarchical model system, uncertainty propagates through the descendant components. Downscaling increases uncertainty with the deficiencies of RCMs and/or weather generators. Bias correction adds a strong deterministic shift to the input data. Finally the predictive uncertainty of the hydrological model ends the cascade that leads to the total uncertainty of the hydrological impact assessment. There is an emerging consensus between many studies on the relative importance of the different uncertainty sources. The prevailing perception is that GCM uncertainty dominates hydrological impact studies. There are only few studies, which found that the predictive uncertainty of hydrological models can be in the same range or even larger than climatic uncertainty. We carried out a climate change impact assessment and estimated the relative importance of the uncertainty sources. The study was performed on 2 small catchments in the Swiss Plateau with a lumped conceptual rainfall runoff model. In the climatic part we applied the standard ensemble approach to quantify uncertainty but in hydrology we used formal Bayesian uncertainty assessment method with 2 different likelihood functions. One was a time-series error model that was able to deal with the complicated statistical properties of hydrological model residuals. The second was a likelihood function for the flow quantiles directly. Due to the better data coverage and smaller hydrological complexity in one of our test catchments we had better performance from the hydrological model and thus could observe that the relative importance of different uncertainty sources varied between sites, boundary conditions and flow indicators. The uncertainty of future climate was important, but not dominant. The deficiencies of the hydrological model were on the same scale, especially for the sites and flow components where model performance for the past observations was further from optimal (Nash-Sutcliffe index = 0.5 - 0.7). The overall uncertainty of predictions was well beyond the expected change signal even for the best performing site and flow indicator.

A Multi-Level Approach to Modeling Rapidly Growing Mega-Regions as a Coupled Human-Natural System

NASA Astrophysics Data System (ADS)

Koch, J. A.; Tang, W.; Meentemeyer, R. K.

2013-12-01

The FUTure Urban-Regional Environment Simulation (FUTURES) integrates information on nonstationary drivers of land change (per capita land area demand, site suitability, and spatial structure of conversion events) into spatial-temporal projections of changes in landscape patterns (Meentemeyer et al., 2013). One striking feature of FUTURES is its patch-growth algorithm that includes feedback effects of former development events across several temporal and spatial scales: cell-level transition events are aggregated into patches of land change and their further growth is based on empirically derived parameters controlling its size, shape, and dispersion. Here, we augment the FUTURES modeling framework by expanding its multilevel structure and its representation of human decision making. The new modeling framework is hierarchically organized as nested subsystems including the latest theory on telecouplings in coupled human-natural systems (Liu et al., 2013). Each subsystem represents a specific level of spatial scale and embraces agents that have decision making authority at a particular level. The subsystems are characterized with regard to their spatial representation and are connected via flows of information (e.g. regulations and policies) or material (e.g. population migration). To provide a modeling framework that is applicable to a wide range of settings and geographical regions and to keep it computationally manageable, we implement a 'zooming factor' that allows to enable or disable subsystems (and hence the represented processes), based on the extent of the study region. The implementation of the FUTURES modeling framework for a specific case study follows the observational modeling approach described in Grimm et al. (2005), starting from the analysis of empirical data in order to capture the processes relevant for specific scales and to allow a rigorous calibration and validation of the model application. In this paper, we give an introduction to the basic concept of our modeling approach and describe its strengths and weaknesses. We furthermore use empirical data for the states of North and South Carolina to demonstrate how the modeling framework can be applied to a large, heterogeneous study system with diverse decision-making agents. Grimm et al. (2005) Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology. Science 310, 987-991. Liu et al. (2013) Framing Sustainability in a Telecoupled World. Ecology and Society 18(2), 26. Meentemeyer et al. (2013) FUTURES: Multilevel Simulations of Merging Urban-Rural Landscape Structure Using a Stochastic Patch-Growing Algorithm. Annals of the Association of American Geographers 103(4), 785-807.

Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

USGS Publications Warehouse

Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

PubMed Central

Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

Electricity Market Manipulation: How Behavioral Modeling Can Help Market Design

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

Gallo, Giulia

The question of how to best design electricity markets to integrate variable and uncertain renewable energy resources is becoming increasingly important as more renewable energy is added to electric power systems. Current markets were designed based on a set of assumptions that are not always valid in scenarios of high penetrations of renewables. In a future where renewables might have a larger impact on market mechanisms as well as financial outcomes, there is a need for modeling tools and power system modeling software that can provide policy makers and industry actors with more realistic representations of wholesale markets. One optionmore » includes using agent-based modeling frameworks. This paper discusses how key elements of current and future wholesale power markets can be modeled using an agent-based approach and how this approach may become a useful paradigm that researchers can employ when studying and planning for power systems of the future.« less

A blueprint for using climate change predictions in an eco-hydrological study

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.

2009-12-01

There is a growing interest to extend climate change predictions to smaller, catchment-size scales and identify their implications on hydrological and ecological processes. Small scale processes are, in fact, expected to mediate climate changes, producing local effects and feedbacks that can interact with the principal consequences of the change. This is particularly applicable, when a complex interaction, such as the inter-relationship between the hydrological cycle and vegetation dynamics, is considered. This study presents a blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the catchment scale. Climate conditions, present or future, are imposed through input hydrometeorological variables for hydrological and eco-hydrological models. These variables are simulated with an hourly weather generator as an outcome of a stochastic downscaling technique. The generator is parameterized to reproduce the climate of southwestern Arizona for present (1961-2000) and future (2081-2100) conditions. The methodology provides the capability to generate ensemble realizations for the future that take into account the heterogeneous nature of climate predictions from different models. The generated time series of meteorological variables for the two scenarios corresponding to the current and mean expected future serve as input to a coupled hydrological and vegetation dynamics model, “Tethys-Chloris”. The hydrological model reproduces essential components of the land-surface hydrological cycle, solving the mass and energy budget equations. The vegetation model parsimoniously parameterizes essential plant life-cycle processes, including photosynthesis, phenology, carbon allocation, and tissue turnover. The results for the two mean scenarios are compared and discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity The need to account for uncertainties in projections of future climate is discussed and a methodology for propagating these uncertainties into the probability density functions of changes in eco-hydrological variables is presented.

Applications of the International Space Station Probabilistic Risk Assessment Model

NASA Technical Reports Server (NTRS)

Grant, Warren; Lutomski, Michael G.

2011-01-01

Recently the International Space Station (ISS) has incorporated more Probabilistic Risk Assessments (PRAs) in the decision making process for significant issues. Future PRAs will have major impact to ISS and future spacecraft development and operations. These PRAs will have their foundation in the current complete ISS PRA model and the current PRA trade studies that are being analyzed as requested by ISS Program stakeholders. ISS PRAs have recently helped in the decision making process for determining reliability requirements for future NASA spacecraft and commercial spacecraft, making crew rescue decisions, as well as making operational requirements for ISS orbital orientation, planning Extravehicular activities (EVAs) and robotic operations. This paper will describe some applications of the ISS PRA model and how they impacted the final decision. This paper will discuss future analysis topics such as life extension, requirements of new commercial vehicles visiting ISS.

Extreme waves from tropical cyclones and climate change in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Appendini, Christian M.; Pedrozo-Acuña, Adrian; Meza-Padilla, Rafael; Torres-Freyermuth, Alec; Cerezo-Mota, Ruth; López-González, José

2017-04-01

Tropical cyclones generate extreme waves that represent a risk to infrastructure and maritime activities. The projection of the tropical cyclones derived wave climate are challenged by the short historical record of tropical cyclones, their low occurrence, and the poor wind field resolution in General Circulation Models. In this study we use synthetic tropical cyclones to overcome such limitations and be able to characterize present and future wave climate associated with tropical cyclones in the Gulf of Mexico. Synthetic events derived from 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 force a third generation wave model to characterize the present and future wave climate under RCP 4.5 and 8.5 escenarios. An increase in wave activity is projected 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.

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.

Prospective Teachers' Future Time Perspective and Professional Plans about Teaching: The Mediating Role of Academic Optimism

ERIC Educational Resources Information Center

Eren, Altay

2012-01-01

This study aimed to examine the mediating role of prospective teachers' academic optimism in the relationship between their future time perspective and professional plans about teaching. A total of 396 prospective teachers voluntarily participated in the study. Correlation, regression, and structural equation modeling analyses were conducted in…

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

Modelling the water energy nexus: should variability in water supply impact on decision making for future energy supply options?

NASA Astrophysics Data System (ADS)

Cullis, James D. S.; Walker, Nicholas J.; Ahjum, Fadiel; Juan Rodriguez, Diego

2018-02-01

Many countries, like South Africa, Australia, India, China and the United States, are highly dependent on coal fired power stations for energy generation. These power stations require significant amounts of water, particularly when fitted with technology to reduce pollution and climate change impacts. As water resources come under stress it is important that spatial variability in water availability is taken into consideration for future energy planning particularly with regards to motivating for a switch from coal fired power stations to renewable technologies. This is particularly true in developing countries where there is a need for increased power production and associated increasing water demands for energy. Typically future energy supply options are modelled using a least cost optimization model such as TIMES that considers water supply as an input cost, but is generally constant for all technologies. Different energy technologies are located in different regions of the country with different levels of water availability and associated infrastructure development and supply costs. In this study we develop marginal cost curves for future water supply options in different regions of a country where different energy technologies are planned for development. These water supply cost curves are then used in an expanded version of the South Africa TIMES model called SATIM-W that explicitly models the water-energy nexus by taking into account the regional nature of water supply availability associated with different energy supply technologies. The results show a significant difference in the optimal future energy mix and in particular an increase in renewables and a demand for dry-cooling technologies that would not have been the case if the regional variability of water availability had not been taken into account. Choices in energy policy, such as the introduction of a carbon tax, will also significantly impact on future water resources, placing additional water demands in some regions and making water available for other users in other regions with a declining future energy demand. This study presents a methodology for modelling the water-energy nexus that could be used to inform the sustainable development planning process in the water and energy sectors for both developed and developing countries.

Carbon Cycle Model of a Hawaiian Barrier Reef under Rising Ocean Acidification and Temperature Conditions of the Anthropocene

NASA Astrophysics Data System (ADS)

Drupp, P. S.; Mackenzie, F. T.; De Carlo, E. H.; Guidry, M.

2015-12-01

A CO2-carbonic acid system biogeochemical box model (CRESCAM, Coral Reef and Sediment Carbonate Model) of the barrier reef flat in Kaneohe Bay, Hawai'i was developed to determine how increasing temperature and dissolved inorganic carbon (DIC) content of open ocean source waters, resulting from rising anthropogenic CO2 emissions and ocean acidification, affect the CaCO3budget of coral reef ecosystems. CRESCAM consists of 17 reservoirs and 59 fluxes, including a surface water column domain, a two-layer permeable sediment domain, and a coral framework domain. Physical, chemical, and biological processes such as advection, carbonate precipitation/dissolution, and net ecosystem production and calcification were modeled. The initial model parameters were constrained by experimental and field data from previous coral reef studies, mostly in Kaneohe Bay over the past 50 years. The field studies include data collected by our research group for both the water column and sediment-porewater system.The model system, initially in a quasi-steady state condition estimated for the early 21st century, was perturbed using future projections to the year 2100 of the Anthropocene of atmospheric CO2 ­concentrations, temperature, and source water DIC. These perturbations were derived from the most recent (2013) IPCC's Representative Concentration Pathway (RCP) scenarios, which predict CO2 atmospheric concentrations and temperature anomalies out to 2100. A series of model case studies were also performed whereby one or more parameters (e.g., coral calcification response to declining surface water pH) were altered to investigate potential future outcomes. Our model simulations predict that although the Kaneohe Bay barrier reef will likely see a significant decline in NEC over the coming century, it is unlikely to reach a state of net erosion - a result contrary to several global coral reef model projections. In addition, we show that depending on the future response of NEP and NEC to OA and rising temperatures, the surface waters could switch from being a present-day source of CO2 to the atmosphere to a future sink. This ecosystem specific model can be applied to any reef system where data are available to constrain the initial model state and is a powerful tool for examining future changes in coral reef carbon budgets.

Plasma Free Amino Acid Profiles Predict Four-Year Risk of Developing Diabetes, Metabolic Syndrome, Dyslipidemia, and Hypertension in Japanese Population

PubMed Central

Yamakado, Minoru; Nagao, Kenji; Imaizumi, Akira; Tani, Mizuki; Toda, Akiko; Tanaka, Takayuki; Jinzu, Hiroko; Miyano, Hiroshi; Yamamoto, Hiroshi; Daimon, Takashi; Horimoto, Katsuhisa; Ishizaka, Yuko

2015-01-01

Plasma free amino acid (PFAA) profile is highlighted in its association with visceral obesity and hyperinsulinemia, and future diabetes. Indeed PFAA profiling potentially can evaluate individuals’ future risks of developing lifestyle-related diseases, in addition to diabetes. However, few studies have been performed especially in Asian populations, about the optimal combination of PFAAs for evaluating health risks. We quantified PFAA levels in 3,701 Japanese subjects, and determined visceral fat area (VFA) and two-hour post-challenge insulin (Ins120 min) values in 865 and 1,160 subjects, respectively. Then, models between PFAA levels and the VFA or Ins120 min values were constructed by multiple linear regression analysis with variable selection. Finally, a cohort study of 2,984 subjects to examine capabilities of the obtained models for predicting four-year risk of developing new-onset lifestyle-related diseases was conducted. The correlation coefficients of the obtained PFAA models against VFA or Ins120 min were higher than single PFAA level. Our models work well for future risk prediction. Even after adjusting for commonly accepted multiple risk factors, these models can predict future development of diabetes, metabolic syndrome, and dyslipidemia. PFAA profiles confer independent and differing contributions to increasing the lifestyle-related disease risks in addition to the currently known factors in a general Japanese population. PMID:26156880

Future impacts of global warming and reforestation on drought patterns over West Africa

NASA Astrophysics Data System (ADS)

Diasso, Ulrich; Abiodun, Babatunde J.

2017-07-01

This study investigates how a large-scale reforestation in Savanna (8-12°N, 20°W-20°E) could affect drought patterns over West Africa in the future (2031-2060) under the RCP4.5 scenario. Simulations from two regional climate models (RegCM4 and WRF) were analyzed for the study. The study first evaluated the performance of both RCMs in simulating the present-day climate and then applied the models to investigate the future impacts of global warming and reforestation on the drought patterns. The simulated and observed droughts were characterized with the Standardized Precipitation and Evapotranspiration Index (SPEI), and the drought patterns were classified using a Self-organizing Map (SOM) technique. The models capture essential features in the seasonal rainfall and temperature fields (including the Saharan Heat Low), but struggle to reproduce the onset and retreat of the West African Monsoon as observed. Both RCMs project a warmer climate (about 1-2 °C) over West Africa in the future. They do not reach a consensus on future change in rainfall, but they agree on a future increase in frequency of severe droughts (by about 2 to 9 events per decade) over the region. They show that reforestation over the Savanna could reduce the future warming by 0.1 to 0.8 °C and increase the precipitation by 0.8 to 1.2 mm per day. However, the impact of reforestation on the frequency of severe droughts is twofold. While reforestation decreases the droughts frequency (by about 1-2 events per decade) over the Savanna and Guinea coast, it increases droughts frequency (by 1 event per decade) over the Sahel, especially in July to September. The results of this study have application in using reforestation to mitigate impacts of climate change in West Africa.

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.

Impact of forest maintenance on water shortages: Hydrologic modeling and effects of climate change.

PubMed

Luo, Pingping; Zhou, Meimei; Deng, Hongzhang; Lyu, Jiqiang; Cao, Wenqiang; Takara, Kaoru; Nover, Daniel; Geoffrey Schladow, S

2018-02-15

The importance of water quantity for domestic and industrial water supply, agriculture, and the economy more broadly has led to the development of many water quantity assessment methods. In this study, surface flow and soil water in the forested upper reaches of the Yoshino River are compared using a distributed hydrological model with Forest Maintenance Module under two scenarios; before and after forest maintenance. We also examine the impact of forest maintenance on these variables during extreme droughts. Results show that surface flow and soil water increased after forest maintenance. In addition, projections of future water resources were estimated using a hydrological model and the output from a 20km mesh Global Climate Model (GCM20). River discharge for the near-future (2015-2039) is similar to that of the present (1979-2003). Estimated river discharge for the future (2075-2099) was found to be substantially more extreme than in the current period, with 12m 3 /s higher peak discharge in August and 7m 3 /s lower in July compared to the discharges of the present period. Soil water for the future is estimated to be lower than for the present and near future in May. The methods discussed in this study can be applied in other regions and the results help elucidate the impact of forests and climate change on water resources. Copyright © 2017 Elsevier B.V. All rights reserved.

A systematic review of transmission dynamic studies of methicillin-resistant Staphylococcus aureus in non-hospital residential facilities.

PubMed

Kwok, Kin On; Read, Jonathan M; Tang, Arthur; Chen, Hong; Riley, Steven; Kam, Kai Man

2018-04-18

Non-hospital residential facilities are important reservoirs for MRSA transmission. However, conclusions and public health implications drawn from the many mathematical models depicting nosocomial MRSA transmission may not be applicable to these settings. Therefore, we reviewed the MRSA transmission dynamics studies in defined non-hospital residential facilities to: (1) provide an overview of basic epidemiology which has been addressed; (2) identify future research direction; and (3) improve future model implementation. A review was conducted by searching related keywords in PUBMED without time restriction as well as internet searches via Google search engine. We included only articles describing the epidemiological transmission pathways of MRSA/community-associated MRSA within and between defined non-hospital residential settings. Among the 10 included articles, nursing homes (NHs) and correctional facilities (CFs) were two settings considered most frequently. Importation of colonized residents was a plausible reason for MRSA outbreaks in NHs, where MRSA was endemic without strict infection control interventions. The importance of NHs over hospitals in increasing nosocomial MRSA prevalence was highlighted. Suggested interventions in NHs included: appropriate staffing level, screening and decolonizing, and hand hygiene. On the other hand, the small population amongst inmates in CFs has no effect on MRSA community transmission. Included models ranged from system-level compartmental models to agent-based models. There was no consensus over the course of disease progression in these models, which were mainly featured with NH residents /CF inmates/ hospital patients as transmission pathways. Some parameters used by these models were outdated or unfit. Importance of NHs has been highlighted from these current studies addressing scattered aspects of MRSA epidemiology. However, the wide variety of non-hospital residential settings suggest that more work is needed before robust conclusions can be drawn. Learning from existing work for hospitals, we identified critical future research direction in this area from infection control, ecological and economic perspectives. From current model deficiencies, we suggest more transmission pathways be specified to depict MRSA transmission, and further empirical studies be stressed to support evidence-based mathematical models of MRSA in non-hospital facilities. Future models should be ready to cope with the aging population structure.

Future projection of Indian summer monsoon variability under climate change scenario: An assessment from CMIP5 climate models

NASA Astrophysics Data System (ADS)

Sharmila, S.; Joseph, S.; Sahai, A. K.; Abhilash, S.; Chattopadhyay, R.

2015-01-01

In this study, the impact of enhanced anthropogenic greenhouse gas emissions on the possible future changes in different aspects of daily-to-interannual variability of Indian summer monsoon (ISM) is systematically assessed using 20 coupled models participated in the Coupled Model Inter-comparison Project Phase 5. The historical (1951-1999) and future (2051-2099) simulations under the strongest Representative Concentration Pathway have been analyzed for this purpose. A few reliable models are selected based on their competence in simulating the basic features of present-climate ISM variability. The robust and consistent projections across the selected models suggest substantial changes in the ISM variability by the end of 21st century indicating strong sensitivity of ISM to global warming. On the seasonal scale, the all-India summer monsoon mean rainfall is likely to increase moderately in future, primarily governed by enhanced thermodynamic conditions due to atmospheric warming, but slightly offset by weakened large scale monsoon circulation. It is projected that the rainfall magnitude will increase over core monsoon zone in future climate, along with lengthening of the season due to late withdrawal. On interannual timescales, it is speculated that severity and frequency of both strong monsoon (SM) and weak monsoon (WM) might increase noticeably in future climate. Substantial changes in the daily variability of ISM are also projected, which are largely associated with the increase in heavy rainfall events and decrease in both low rain-rate and number of wet days during future monsoon. On the subseasonal scale, the model projections depict considerable amplification of higher frequency (below 30 day mode) components; although the dominant northward propagating 30-70 day mode of monsoon intraseasonal oscillations may not change appreciably in a warmer climate. It is speculated that the enhanced high frequency mode of monsoon ISOs due to increased GHG induced warming may notably modulate the ISM rainfall in future climate. Both extreme wet and dry episodes are likely to intensify and regionally extend in future climate with enhanced propensity of short active and long break spells. The SM (WM) could also be more wet (dry) in future due to the increment in longer active (break) spells. However, future changes in the spatial pattern during active/break phase of SM and WM are geographically inconsistent among the models. The results point out the growing climate-related vulnerability over Indian subcontinent, and further suggest the requisite of profound adaptation measures and better policy making in future.

Fire and climate suitability for woody vegetation communities in the south central United States

USGS Publications Warehouse

Stroh, Esther; Struckhoff, Matthew; Stambaugh, Michael C.; Guyette, Richard P.

2018-01-01

using a physical chemistry fire frequency model. We then used the fire probability data with additional climate parameters to construct maximum entropy environmental suitability models for three south central US vegetation communities. The modeled communities included an oak type (dominated by post oak, Quercus stellata Wangenh., and blackjack oak, Q. marilandica Münchh.), a mesquite type (dominated by honey mesquite, Prosopis glandulosa Torr., and velvet mesquite, P. velutina Wooton), and a pinyon−juniper type (dominated by pinyon pine, Pinus edulis Engelm., and Utah juniper, Juniperus osteosperma [Torr.] Little). We mapped baseline and future mean fire-climate suitability using data from three global climate models for 2040 to 2069 and 2070 to 2099; we also mapped future locations of threshold conditions for which all three models agreed on suitability for each community. Future projections included northward, southward, and eastward shifts in suitable conditions for the oaks along a broad path of fire-climate stability; an overall reduction in suitable area for historic mesquite communities coupled with potential expansion to new areas; and constriction and isolation of suitable conditions for pinyon−juniper communities. The inclusion of fire probability adds an important driver of vegetation distribution to climate envelope modeling. The simple models showed good fit, but future projections failed to account for future management activities or land use changes. Results provided information on potential future de-coupling and spatial re-arrangement of environmental conditions under which these communities have historically persisted and been managed. In particular, consensus threshold maps can inform long-term planning for maintenance or restoration of these communities, and they can be used as a potential tool for other communities in fire-prone environments within the study area and beyond its borders.

Tools and Techniques for Basin-Scale Climate Change Assessment

NASA Astrophysics Data System (ADS)

Zagona, E.; Rajagopalan, B.; Oakley, W.; Wilson, N.; Weinstein, P.; Verdin, A.; Jerla, C.; Prairie, J. R.

2012-12-01

The Department of Interior's WaterSMART Program seeks to secure and stretch water supplies to benefit future generations and identify adaptive measures to address climate change. Under WaterSMART, Basin Studies are comprehensive water studies to explore options for meeting projected imbalances in water supply and demand in specific basins. Such studies could be most beneficial with application of recent scientific advances in climate projections, stochastic simulation, operational modeling and robust decision-making, as well as computational techniques to organize and analyze many alternatives. A new integrated set of tools and techniques to facilitate these studies includes the following components: Future supply scenarios are produced by the Hydrology Simulator, which uses non-parametric K-nearest neighbor resampling techniques to generate ensembles of hydrologic traces based on historical data, optionally conditioned on long paleo reconstructed data using various Markov Chain techniuqes. Resampling can also be conditioned on climate change projections from e.g., downscaled GCM projections to capture increased variability; spatial and temporal disaggregation is also provided. The simulations produced are ensembles of hydrologic inputs to the RiverWare operations/infrastucture decision modeling software. Alternative demand scenarios can be produced with the Demand Input Tool (DIT), an Excel-based tool that allows modifying future demands by groups such as states; sectors, e.g., agriculture, municipal, energy; and hydrologic basins. The demands can be scaled at future dates or changes ramped over specified time periods. Resulting data is imported directly into the decision model. Different model files can represent infrastructure alternatives and different Policy Sets represent alternative operating policies, including options for noticing when conditions point to unacceptable vulnerabilities, which trigger dynamically executing changes in operations or other options. The over-arching Study Manager provides a graphical tool to create combinations of future supply scenarios, demand scenarios, infrastructure and operating policy alternatives; each scenario is executed as an ensemble of RiverWare runs, driven by the hydrologic supply. The Study Manager sets up and manages multiple executions on multi-core hardware. The sizeable are typically direct model outputs, or post-processed indicators of performance based on model outputs. Post processing statistical analysis of the outputs are possible using the Graphical Policy Analysis Tool or other statistical packages. Several Basin Studies undertaken have used RiverWare to evaluate future scenarios. The Colorado River Basin Study, the most complex and extensive to date, has taken advantage of these tools and techniques to generate supply scenarios, produce alternative demand scenarios and to set up and execute the many combinations of supplies, demands, policies, and infrastructure alternatives. The tools and techniques will be described with example applications.

Practice Plans of Today's Medical Students.

ERIC Educational Resources Information Center

Rosen, Raye Hudson; And Others

1981-01-01

Students' future practice plans were surveyed by questionnaire at three Michigan medical schools to study future physician productivity and its implications for health manpower planning. Results suggested that the students planned to work less than they thought their role models did. (LB)

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.

Future anthropogenic pollutant emissions in a Mediterranean port city with emphasis on the maritime sector emissions - Study of the impact on the city air quality

NASA Astrophysics Data System (ADS)

Liora, Natalia; Poupkou, Anastasia; Markakis, Konstantinos; Giannaros, Theodoros; Karagiannidis, Athanasios; Melas, Dimitrios

2013-04-01

The aim of this study is the estimation of the future emissions in the area of the large urban center of Thessaloniki (Greece) with emphasis on the emissions originated from the maritime sector within the port area of the city which are presented in detail. In addition, the contribution of the future anthropogenic emissions to atmospheric pollution levels in Thessaloniki focusing on PM levels is studied. A 2km spatial resolution anthropogenic gaseous and particulate matter emission inventory has been compiled for the port city of Thessaloniki for the year 2010 with the anthropogenic emission model MOSESS, developed by Laboratory of Atmospheric Physics of the Aristotle University of Thessaloniki. MOSESS was used for the estimation of emissions from several emission sources (road transport, central heating, industries, maritime sector etc) while the natural emission model NEMO was implemented for the calculation of dust, sea salt and biogenic emissions. Maritime emissions originated from the various processes inside the area of the port (harbor operations such as stockpiles, loading/unloading operations, machineries etc) as well as from the maritime transport sector including passenger ships, cargo shipping, inland waterways vessels (e.g. pleasure crafts) and fish catching ships. Ship emissions were estimated for the three operation modes; cruising, maneuvering and hotelling. For the calculation of maritime emissions, the activity data used were provided by local and national authorities (e.g.Thessaloniki Port Authority S.A.). Pollutant anthropogenic emissions were projected to the year 2020. The emissions from all the anthropogenic sources except for the maritime sector were projected using factors provided by the GAINS model. Future emissions from the maritime activities were estimated on the basis of the future activity data provided by the Port Authority and of the legislation for shipping in the future. Future maritime emissions are determined by the vessels traffic changes as foreseen for the year 2020 by the Port Authority Investment Plan and by the reduction of the sulfur content in fuels used by ships in cruising mode to 0.5% m/m according to a revision of the MARPOL Annex VI. Based on the above, an approximately 60% increase in the future maritime sector PM10 emissions is expected due to the high increase of the traffic of vessels. The impact of future emissions on the air quality of Thessaloniki is examined with the use of the modelling system WRF-CAMx applied with 2km spatial resolution over the study area. Simulations of the modelling system are performed for a summertime (July 2011) and a wintertime (15 November to 15 December 2011) period accounting for present time (scenario A) and future time (scenario B) pollutant emissions. The differences in pollutant levels (mainly PM) between the scenarios examined are presented and discussed.

The future of the North American carbon cycle - projections and associated climate change

NASA Astrophysics Data System (ADS)

Huntzinger, D. N.; Chatterjee, A.; Cooley, S. R.; Dunne, J. P.; Hoffman, F. M.; Luo, Y.; Moore, D. J.; Ohrel, S. B.; Poulter, B.; Ricciuto, D. M.; Tzortziou, M.; Walker, A. P.; Mayes, M. A.

2016-12-01

Approximately half of anthropogenic emissions from the burning of fossil fuels is taken up annually by carbon sinks on the land and in the oceans. However, there are key uncertainties in how carbon uptake by terrestrial, ocean, and freshwater systems will respond to, and interact with, climate into the future. Here, we outline the current state of understanding on the future carbon budget of these major reservoirs within North America and the globe. We examine the drivers of future carbon cycle changes, including carbon-climate feedbacks, atmospheric composition, nutrient availability, and human activity and management decisions. Progress has been made at identifying vulnerabilities in carbon pools, including high-latitude permafrost, peatlands, freshwater and coastal wetlands, and ecosystems subject to disturbance events, such as insects, fire and drought. However, many of these processes/pools are not well represented in current models, and model intercomparison studies have shown a range in carbon cycle response to factors such as climate and CO2 fertilization. Furthermore, as model complexity increases, understanding the drivers of model spread becomes increasingly more difficult. As a result, uncertainties in future carbon cycle projections are large. It is also uncertain how management decisions and policies will impact future carbon stocks and flows. In order to guide policy, a better understanding of the risk and magnitude of North American carbon cycle changes is needed. This requires that future carbon cycle projections be conditioned on current observations and be reported with sufficient confidence and fully specified uncertainties.

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.

Changes in Black-legged Tick Population in New England with Future Climate Change

NASA Astrophysics Data System (ADS)

Krishnan, S.; Huber, M.

2015-12-01

Lyme disease is one of the most frequently reported vector-borne diseases in the United States. In the Northeastern United States, vector transmission is maintained in a horizontal transmission cycle between the vector, the black-legged ticks, and the vertebrate reservoir hosts, which include white-tailed deer, rodents and other medium to large sized mammals. Predicting how vector populations change with future climate change is critical to understanding disease spread in the future, and for developing suitable regional adaptation strategies. For the United States, these predictions have mostly been made using regressions based on field and lab studies, or using spatial suitability studies. However, the relation between tick populations at various life-cycle stages and climate variables are complex, necessitating a mechanistic approach. In this study, we present a framework for driving a mechanistic tick population model with high-resolution regional climate modeling projections. The goal is to estimate changes in black-legged tick populations in New England for the 21st century. The tick population model used is based on the mechanistic approach of Ogden et al., (2005) developed for Canada. Dynamically downscaled climate projections at a 3-kms resolution using the Weather and Research Forecasting Model (WRF) are used to drive the tick population model.

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

NASA Technical Reports Server (NTRS)

Ahmed, Kazi Farzan; Wang, Guiling; Silander, John; Wilson, Adam M.; Allen, Jenica M.; Horton, Radley; Anyah, Richard

2013-01-01

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1/8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

Scenario-based projections of future urban inundation within a coupled hydrodynamic model framework: A case study in Dongguan City, China

NASA Astrophysics Data System (ADS)

Wu, Xushu; Wang, Zhaoli; Guo, Shenglian; Liao, Weilin; Zeng, Zhaoyang; Chen, Xiaohong

2017-04-01

One major threat to cities at present is the increased inundation hazards owing to changes in climate and accelerated human activity. Future evolution of urban inundation is still an unsolved issue, given large uncertainties in future environmental conditions within urbanized areas. Developing model techniques and urban inundation projections are essential for inundation management. In this paper, we proposed a 2D hydrodynamic inundation model by coupling SWMM and LISFLOOD-FP models, and revealed how future urban inundation would evolve for different storms, sea level rise and subsidence scenarios based on the developed model. The Shiqiao Creek District (SCD) in Dongguan City was used as the case study. The model ability was validated against the June 13th, 2008 inundation event, which occurred in SCD, and proved capable of simulating dynamic urban inundation. Scenario analyses revealed a high degree of consistency in the inundation patterns among different storms, with larger magnitudes corresponding to greater return periods. Inundations across SCD generally vary as a function of storm intensity, but for lowlands or regions without drainage facilities inundations tend to aggravate over time. In riverfronts, inundations would exacerbate with sea level rise or subsidence; however, the inland inundations are seemingly insensitive to both factors. For the combined scenario of 100-yr storm, 0.5 m subsidence and 0.7 m sea level rise, the riverside inundations would occur much in advance, whilst catastrophic inundations sweep across SCD. Furthermore, the optimal low-impact development found for this case study includes 0.2 km2 of permeable pavements, 0.1 km2 of rain barrels and 0.7 km2 of green roofs.

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

Suitable areas of Phakopsora pachyrhizi, Spodoptera exigua, and their host plant Phaseolus vulgaris are projected to reduce and shift due to climate change

NASA Astrophysics Data System (ADS)

Ramirez-Cabral, Nadiezhda Yakovleva Zitz; Kumar, Lalit; Shabani, Farzin

2018-01-01

Worldwide, crop pests (CPs) such as pathogens and insects affect agricultural production detrimentally. Species distribution models can be used for projecting current and future suitability of CPs and host crop localities. Our study overlays the distribution of two CPs (Asian soybean rust and beet armyworm) and common bean, a potential host of them, in order to determine their current and future levels of coexistence. This kind of modeling approach has rarely been performed previously in climate change studies. The soybean rust and beet armyworm model projections herein show a reduction of the worldwide area with high and medium suitability of both CPs and a movement of them away from the Equator, in 2100 more pronounced than in 2050. Most likely, heat and dry stress will be responsible for these changes. Heat and dry stress will greatly reduce and shift the future suitable cultivation area of common bean as well, in a similar manner. The most relevant findings of this study were the reduction of the suitable areas for the CPs, the reduction of the risk under future scenarios, and the similarity of trends for the CPs and host. The current results highlight the relation between and the coevolution of host and pathogens.

Refining climate change projections for organisms with low dispersal abilities: a case study of the Caspian whip snake.

PubMed

Sahlean, Tiberiu C; Gherghel, Iulian; Papeş, Monica; Strugariu, Alexandru; Zamfirescu, Ştefan R

2014-01-01

Climate warming is one of the most important threats to biodiversity. Ectothermic organisms such as amphibians and reptiles are especially vulnerable as climatic conditions affect them directly. Ecological niche models (ENMs) are increasingly popular in ecological studies, but several drawbacks exist, including the limited ability to account for the dispersal potential of the species. In this study, we use ENMs to explore the impact of global climate change on the Caspian whip snake (Dolichophis caspius) as model for organisms with low dispersal abilities and to quantify dispersal to novel areas using GIS techniques. Models generated using Maxent 3.3.3 k and GARP for current distribution were projected on future climatic scenarios. A cost-distance analysis was run in ArcGIS 10 using geomorphological features, ecological conditions, and human footprint as "costs" to dispersal of the species to obtain a Maximum Dispersal Range (MDR) estimate. All models developed were statistically significant (P<0.05) and recovered the currently known distribution of D. caspius. Models projected on future climatic conditions using Maxent predicted a doubling of suitable climatic area, while GARP predicted a more conservative expansion. Both models agreed on an expansion of suitable area northwards, with minor decreases at the southern distribution limit. The MDR area calculated using the Maxent model represented a third of the total area of the projected model. The MDR based on GARP models recovered only about 20% of the total area of the projected model. Thus, incorporating measures of species' dispersal abilities greatly reduced estimated area of potential future distributions.

Development of an Integrated Agricultural Planning Model Considering Climate Change

NASA Astrophysics Data System (ADS)

Santikayasa, I. P.

2016-01-01

The goal of this study is to develop an agriculture planning model in order to sustain the future water use under the estimation of crop water requirement, water availability and future climate projection. For this purpose, the Citarum river basin which is located in West Java - Indonesia is selected as the study area. Two emission scenarios A2 and B2 were selected. For the crop water requirement estimation, the output of HadCM3 AOGCM is statistically downscale using SDSM and used as the input for WEAP model developed by SEI (Stockholm Environmental Institute). The reliability of water uses is assessed by comparing the irrigation water demand and the water allocation for the irrigation area. The water supply resources are assessed using the water planning tool. This study shows that temperature and precipitation over the study area are projected to increase in the future. The water availability was projected to increase under both A2 and B2 emission scenarios in the future. The irrigation water requirement is expected to decrease in the future under A2 and B2 scenarios. By comparing the irrigation water demand and water allocation for irrigation, the reliability of agriculture water use is expected to change in the period of 2050s and 2080s while the reliability will not change in 2020s. The reliability under A2 scenario is expected to be higher than B2 scenario. The combination of WEAP and SDSM is significance to use in assessing and allocating the water resources in the region.

Stream Discharge and Evapotranspiration Responses to Climate Change and Their Associated Uncertainties in a Large Semi-Arid Basin

NASA Astrophysics Data System (ADS)

Bassam, S.; Ren, J.

2017-12-01

Predicting future water availability in watersheds is very important for proper water resources management, especially in semi-arid regions with scarce water resources. Hydrological models have been considered as powerful tools in predicting future hydrological conditions in watershed systems in the past two decades. Streamflow and evapotranspiration are the two important components in watershed water balance estimation as the former is the most commonly-used indicator of the overall water budget estimation, and the latter is the second biggest component of water budget (biggest outflow from the system). One of the main concerns in watershed scale hydrological modeling is the uncertainties associated with model prediction, which could arise from errors in model parameters and input meteorological data, or errors in model representation of the physics of hydrological processes. Understanding and quantifying these uncertainties are vital to water resources managers for proper decision making based on model predictions. In this study, we evaluated the impacts of different climate change scenarios on the future stream discharge and evapotranspiration, and their associated uncertainties, throughout a large semi-arid basin using a stochastically-calibrated, physically-based, semi-distributed hydrological model. The results of this study could provide valuable insights in applying hydrological models in large scale watersheds, understanding the associated sensitivity and uncertainties in model parameters, and estimating the corresponding impacts on interested hydrological process variables under different climate change scenarios.

Projections of Future Summertime Ozone over the U.S.

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

Pfister, G. G.; Walters, Stacy; Lamarque, J. F.

This study uses a regional fully coupled chemistry-transport model to assess changes in surface ozone over the summertime U.S. between present and a 2050 future time period at high spatial resolution (12 km grid spacing) under the SRES A2 climate and RCP8.5 anthropogenic pre-cursor emission scenario. The impact of predicted changes in climate and global background ozone is estimated to increase surface ozone over most of the U.S; the 5th - 95th percentile range for daily 8-hour maximum surface ozone increases from 31-79 ppbV to 30-87 ppbV between the present and future time periods. The analysis of a set ofmore » meteorological drivers suggests that these mostly will add to increasing ozone, but the set of simulations conducted does not allow to separate this effect from that through enhanced global background ozone. Statistically the most robust positive feedbacks are through increased temperature, biogenic emissions and solar radiation. Stringent emission controls can counteract these feedbacks and if considered, we estimate large reductions in surface ozone with the 5th-95th percentile reduced to 27-55 ppbV. A comparison of the high-resolution projections to global model projections shows that even though the global model is biased high in surface ozone compared to the regional model and compared to observations, both the global and the regional model predict similar changes in ozone between the present and future time periods. However, on smaller spatial scales, the regional predictions show more pronounced changes between urban and rural regimes that cannot be resolved at the coarse resolution of global model. In addition, the sign of the changes in overall ozone mixing ratios can be different between the global and the regional predictions in certain regions, such as the Western U.S. This study confirms the key role of emission control strategies in future air quality predictions and demonstrates the need for considering degradation of air quality with future climate change in emission policy making. It also illustrates the need for high resolution modeling when the objective is to address regional and local air quality or establish links to human health and society.« less

Spatial analysis of plague in California: niche modeling predictions of the current distribution and potential response to climate change

PubMed Central

Holt, Ashley C; Salkeld, Daniel J; Fritz, Curtis L; Tucker, James R; Gong, Peng

2009-01-01

Background Plague, caused by the bacterium Yersinia pestis, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi) as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC) statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans) samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance. Results Models of plague activity in California ground squirrels, based on recent climate conditions, accurately identified case locations (AUC of 0.913 to 0.948) and were significantly correlated with coyote samples. The final models were used to identify potential plague risk areas based on an ensemble of six future climate scenarios. These models suggest that by 2050, climate conditions may reduce plague risk in the southern parts of California and increase risk along the northern coast and Sierras. Conclusion Because different modeling approaches can yield substantially different results, care should be taken when interpreting future model predictions. Nonetheless, niche modeling can be a useful tool for exploring and mapping the potential response of plague activity to climate change. The final models in this study were used to identify potential plague risk areas based on an ensemble of six future climate scenarios, which can help public managers decide where to allocate surveillance resources. In addition, Maxent model results were significantly correlated with coyote samples, indicating that carnivore surveillance programs will continue to be important for tracking the response of plague to future climate conditions. PMID:19558717

Associations Among Individuals’ Perceptions of Future Time, Individual Resources, and Subjective Well-Being in Old Age

PubMed Central

Hoppmann, Christiane A.; Infurna, Frank J.; Ram, Nilam; Gerstorf, Denis

2015-01-01

Objectives Perceptions of future time are of key interest to aging research because of their implications for subjective well-being. Interestingly, perceptions about future time are only moderately associated with age, pointing to a vast heterogeneity in future time perceptions among older adults. We examine associations between future time perceptions, age, and subjective well-being across two studies, including moderations by individual resources. Method Using data from the Berlin Aging Study (N = 516; Mage = 85 years), we link one operationalization (subjective nearness to death) and age to subjective well-being. Using Health and Retirement Study data (N = 2,596; Mage = 77 years), we examine associations of another future time perception indicator (subjective future life expectancy) and age with subjective well-being. Results Consistent across studies, perceptions of limited time left were associated with poorer subjective well-being (lower life satisfaction and positive affect; more negative affect and depressive symptoms). Importantly, individual resources moderated future time perception–subjective well-being associations with those of better health exhibiting reduced future time perception–subjective well-being associations. Discussion We discuss our findings in the context of the Model of Strength and Vulnerability Integration. PMID:26437862

Uncertainties of statistical downscaling from predictor selection: Equifinality and transferability

NASA Astrophysics Data System (ADS)

Fu, Guobin; Charles, Stephen P.; Chiew, Francis H. S.; Ekström, Marie; Potter, Nick J.

2018-05-01

The nonhomogeneous hidden Markov model (NHMM) statistical downscaling model, 38 catchments in southeast Australia and 19 general circulation models (GCMs) were used in this study to demonstrate statistical downscaling uncertainties caused by equifinality to and transferability. That is to say, there could be multiple sets of predictors that give similar daily rainfall simulation results for both calibration and validation periods, but project different amounts (or even directions of change) of rainfall changing in the future. Results indicated that two sets of predictors (Set 1 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and specific humidity at 700 hPa and Set 2 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and dewpoint temperature depression at 850 hPa) as inputs to the NHMM produced satisfactory results of seasonal rainfall in comparison with observations. For example, during the model calibration period, the relative errors across the 38 catchments ranged from 0.48 to 1.76% with a mean value of 1.09% for the predictor Set 1, and from 0.22 to 2.24% with a mean value of 1.16% for the predictor Set 2. However, the changes of future rainfall from NHMM projections based on 19 GCMs produced projections with a different sign for these two different sets of predictors: Set 1 predictors project an increase of future rainfall with magnitudes depending on future time periods and emission scenarios, but Set 2 predictors project a decline of future rainfall. Such divergent projections may present a significant challenge for applications of statistical downscaling as well as climate change impact studies, and could potentially imply caveats in many existing studies in the literature.

Evaluating impacts of climate change on future water scarcity in an intensively managed semi-arid region using a coupled model of biophysical processes and water rights

NASA Astrophysics Data System (ADS)

Han, B.; Flores, A. N.; Benner, S. G.

2017-12-01

In semiarid and arid regions where water supply is intensively managed, future water scarcity is a product of complex interactions between climate change and human activities. Evaluating future water scarcity under alternative scenarios of climate change, therefore, necessitates modeling approaches that explicitly represent the coupled biophysical and social processes responsible for the redistribution of water in these regions. At regional scales a particular challenge lies in adequately capturing not only the central tendencies of change in projections of climate change, but also the associated plausible range of variability in those projections. This study develops a framework that combines a stochastic weather generator, historical climate observations, and statistically downscaled General Circulation Model (GCM) projections. The method generates a large ensemble of daily climate realizations, avoiding deficiencies of using a few or mean values of individual GCM realizations. Three climate change scenario groups reflecting the historical, RCP4.5, and RCP8.5 future projections are developed. Importantly, the model explicitly captures the spatiotemporally varying irrigation activities as constrained by local water rights in a rapidly growing, semi-arid human-environment system in southwest Idaho. We use this modeling framework to project water use and scarcity patterns under the three future climate change scenarios. The model is built using the Envision alternative futures modeling framework. Climate projections for the region show future increases in both precipitation and temperature, especially under the RCP8.5 scenario. The increase of temperature has a direct influence on the increase of the irrigation water use and water scarcity, while the influence of increased precipitation on water use is less clear. The predicted changes are potentially useful in identifying areas in the watershed particularly sensitive to water scarcity, the relative importance of changes in precipitation versus temperature as a driver of scarcity, and potential shortcomings of the current water management framework in the region.

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

Osteoporotic Animal Models of Bone Healing: Advantages and Pitfalls.

PubMed

Calciolari, Elena; Donos, Nikolaos; Mardas, Nikos

2017-10-01

The aim of this review was to summarize the advantages and pitfalls of the available osteoporotic animal models of bone healing. A thorough literature search was performed in MEDLINE via OVID and EMBASE to identify animal studies investigating the effect of experimental osteoporosis on bone healing and bone regeneration. The osteotomy model in the proximal tibia is the most popular osseous defect model to study the bone healing process in osteoporotic-like conditions, although other well-characterized models, such as the post-extraction model, might be taken into consideration by future studies. The regenerative potential of osteoporotic bone and its response to biomaterials/regenerative techniques has not been clarified yet, and the critical size defect model might be an appropriate tool to serve this purpose. Since an ideal animal model for simulating osteoporosis does not exist, the type of bone remodeling, the animal lifespan, the age of peak bone mass, and the economic and ethical implications should be considered in our selection process. Furthermore, the influence of animal species, sex, age, and strain on the outcome measurement should be taken into account. In order to make future studies meaningful, standardized international guidelines for osteoporotic animal models of bone healing need to be set up.

Application of Multi-Model CMIP5 Analysis in Future Drought Adaptation Strategies

NASA Astrophysics Data System (ADS)

Casey, M.; Luo, L.; Lang, Y.

2014-12-01

Drought influences the efficacy of numerous natural and artificial systems including species diversity, agriculture, and infrastructure. Global climate change raises concerns that extend well beyond atmospheric and hydrological disciplines - as climate changes with time, the need for system adaptation becomes apparent. Drought, as a natural phenomenon, is typically defined relative to the climate in which it occurs. Typically a 30-year reference time frame (RTF) is used to determine the severity of a drought event. This study investigates the projected future droughts over North America with different RTFs. Confidence in future hydroclimate projection is characterized by the agreement of long term (2005-2100) multi-model precipitation (P) and temperature (T) projections within the Coupled model Intercomparison Project Phase 5 (CMIP5). Drought severity and the propensity of extreme conditions are measured by the multi-scalar, probabilistic, RTF-based Standard Precipitation Index (SPI) and Standard Precipitation Evapotranspiration Index (SPEI). SPI considers only P while SPEI incorporates Evapotranspiration (E) via T; comparing the two reveals the role of temperature change in future hydroclimate change. Future hydroclimate conditions, hydroclimate extremity, and CMIP5 model agreement are assessed for each Representative Concentration Pathway (RCP 2.6, 4.5, 6.0, 8.5) in regions throughout North America for the entire year and for the boreal seasons. In addition, multiple time scales of SPI and SPEI are calculated to characterize drought at time scales ranging from short to long term. The study explores a simple, standardized method for considering adaptation in future drought assessment, which provides a novel perspective to incorporate adaptation with climate change. The result of the analysis is a multi-dimension, probabilistic summary of the hydrological (P, E) environment a natural or artificial system must adapt to over time. Studies similar to this with specified criteria (SPI/SPEI value, time scale, RCP, etc.) can provide professionals in a variety of disciplines with necessary climatic insight to develop adaptation strategies.

Climate change impact on soil erosion in the Mandakini River Basin, North India

NASA Astrophysics Data System (ADS)

Khare, Deepak; Mondal, Arun; Kundu, Sananda; Mishra, Prabhash Kumar

2017-09-01

Correct estimation of soil loss at catchment level helps the land and water resources planners to identify priority areas for soil conservation measures. Soil erosion is one of the major hazards affected by the climate change, particularly the increasing intensity of rainfall resulted in increasing erosion, apart from other factors like landuse change. Changes in climate have an adverse effect with increasing rainfall. It has caused increasing concern for modeling the future rainfall and projecting future soil erosion. In the present study, future rainfall has been generated with the downscaling of GCM (Global Circulation Model) data of Mandakini river basin, a hilly catchment in the state of Uttarakhand, India, to obtain future impact on soil erosion within the basin. The USLE is an erosion prediction model designed to predict the long-term average annual soil loss from specific field slopes in specified landuse and management systems (i.e., crops, rangeland, and recreational areas) using remote sensing and GIS technologies. Future soil erosion has shown increasing trend due to increasing rainfall which has been generated from the statistical-based downscaling method.

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…

The Future of Low-Wage Jobs: Case Studies in the Retail Industry. IEE Working Paper No. 10.

ERIC Educational Resources Information Center

Bernhardt, Annette

The future of low-wage jobs is examined through a case study of firm restructuring in the retail industry. The study confirms that the retailing sector has come to be dominated by the Wal-Mart model, which emphasizes an efficient technology-driven inventory management system and a human resource approach that includes the following elements:…

Climate Change Impact Assessment of Hydro-Climate in Southern Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Ercan, A.; Ishida, K.; Kavvas, M. L.; Chen, Z. R.; Jang, S.; Amin, M. Z. M.; Shaaban, A. J.

2017-12-01

Impacts of climate change on the hydroclimate of the coastal region in the south of Peninsular Malaysia in the 21st century was assessed by means of a regional climate model utilizing an ensemble of 15 different future climate realizations. Coarse resolution Global Climate Models' future projections covering four emission scenarios based on Coupled Model Intercomparison Project phase 3 (CMIP3) datasets were dynamically downscaled to 6 km resolution over the study area. The analyses were made in terms of rainfall, air temperature, evapotranporation, and soil water storage.

Development of the Coastal Storm Modeling System (CoSMoS) for predicting the impact of storms on high-energy, active-margin coasts

USGS Publications Warehouse

Barnard, Patrick; Maarten van Ormondt,; Erikson, Li H.; Jodi Eshleman,; Hapke, Cheryl J.; Peter Ruggiero,; Peter Adams,; Foxgrover, Amy C.

2014-01-01

The Coastal Storm Modeling System (CoSMoS) applies a predominantly deterministic framework to make detailed predictions (meter scale) of storm-induced coastal flooding, erosion, and cliff failures over large geographic scales (100s of kilometers). CoSMoS was developed for hindcast studies, operational applications (i.e., nowcasts and multiday forecasts), and future climate scenarios (i.e., sea-level rise + storms) to provide emergency responders and coastal planners with critical storm hazards information that may be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. The prototype system, developed for the California coast, uses the global WAVEWATCH III wave model, the TOPEX/Poseidon satellite altimetry-based global tide model, and atmospheric-forcing data from either the US National Weather Service (operational mode) or Global Climate Models (future climate mode), to determine regional wave and water-level boundary conditions. These physical processes are dynamically downscaled using a series of nested Delft3D-WAVE (SWAN) and Delft3D-FLOW (FLOW) models and linked at the coast to tightly spaced XBeach (eXtreme Beach) cross-shore profile models and a Bayesian probabilistic cliff failure model. Hindcast testing demonstrates that, despite uncertainties in preexisting beach morphology over the ~500 km alongshore extent of the pilot study area, CoSMoS effectively identifies discrete sections of the coast (100s of meters) that are vulnerable to coastal hazards under a range of current and future oceanographic forcing conditions, and is therefore an effective tool for operational and future climate scenario planning.

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.

Non-resonant collider signatures of a singlet-driven electroweak phase transition

NASA Astrophysics Data System (ADS)

Chen, Chien-Yi; Kozaczuk, Jonathan; Lewis, Ian M.

2017-08-01

We analyze the collider signatures of the real singlet extension of the Standard Model in regions consistent with a strong first-order electroweak phase transition and a singlet-like scalar heavier than the Standard Model-like Higgs. A definitive correlation exists between the strength of the phase transition and the trilinear coupling of the Higgs to two singlet-like scalars, and hence between the phase transition and non-resonant scalar pair production involving the singlet at colliders. We study the prospects for observing these processes at the LHC and a future 100 TeV pp collider, focusing particularly on double singlet production. We also discuss correlations between the strength of the electroweak phase transition and other observables at hadron and future lepton colliders. Searches for non-resonant singlet-like scalar pair production at 100 TeV would provide a sensitive probe of the electroweak phase transition in this model, complementing resonant di-Higgs searches and precision measurements. Our study illustrates a strategy for systematically exploring the phenomenologically viable parameter space of this model, which we hope will be useful for future work.

Non-resonant collider signatures of a singlet-driven electroweak phase transition

DOE PAGES

Chen, Chien-Yi; Kozaczuk, Jonathan; Lewis, Ian M.

2017-08-22

We analyze the collider signatures of the real singlet extension of the Standard Model in regions consistent with a strong first-order electroweak phase transition and a singlet-like scalar heavier than the Standard Model-like Higgs. A definitive correlation exists between the strength of the phase transition and the trilinear coupling of the Higgs to two singlet-like scalars, and hence between the phase transition and non-resonant scalar pair production involving the singlet at colliders. We study the prospects for observing these processes at the LHC and a future 100 TeV pp collider, focusing particularly on double singlet production. We also discuss correlationsmore » between the strength of the electroweak phase transition and other observables at hadron and future lepton colliders. Searches for non-resonant singlet-like scalar pair production at 100 TeV would provide a sensitive probe of the electroweak phase transition in this model, complementing resonant di-Higgs searches and precision measurements. Our study illustrates a strategy for systematically exploring the phenomenologically viable parameter space of this model, which we hope will be useful for future work.« less

Development and application of downscaled hydroclimatic predictor variables for use in climate vulnerability and assessment studies

USGS Publications Warehouse

Thorne, James; Boynton, Ryan; Flint, Lorraine; Flint, Alan; N'goc Le, Thuy

2012-01-01

This paper outlines the production of 270-meter grid-scale maps for 14 climate and derivative hydrologic variables for a region that encompasses the State of California and all the streams that flow into it. The paper describes the Basin Characterization Model (BCM), a map-based, mechanistic model used to process the hydrological variables. Three historic and three future time periods of 30 years (1911–1940, 1941–1970, 1971–2000, 2010–2039, 2040–2069, and 2070–2099) were developed that summarize 180 years of monthly historic and future climate values. These comprise a standardized set of fine-scale climate data that were shared with 14 research groups, including the U.S. National Park Service and several University of California groups as part of this project. We present three analyses done with the outputs from the Basin Characterization Model: trends in hydrologic variables over baseline, the most recent 30-year period; a calibration and validation effort that uses measured discharge values from 139 streamgages and compares those to Basin Characterization Model-derived projections of discharge for the same basins; and an assessment of the trends of specific hydrological variables that links historical trend to projected future change under four future climate projections. Overall, increases in potential evapotranspiration dominate other influences in future hydrologic cycles. Increased potential evapotranspiration drives decreasing runoff even under forecasts with increased precipitation, and drives increased climatic water deficit, which may lead to conversion of dominant vegetation types across large parts of the study region as well as have implications for rain-fed agriculture. The potential evapotranspiration is driven by air temperatures, and the Basin Characterization Model permits it to be integrated with a water balance model that can be derived for landscapes and summarized by watershed. These results show the utility of using a process-based model with modules representing different hydrological pathways that can be inter-linked.

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.

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.

Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis.

PubMed

Till, Kevin; Jones, Ben L; Cobley, Stephen; Morley, David; O'Hara, John; Chapman, Chris; Cooke, Carlton; Beggs, Clive B

2016-01-01

Prediction of adult performance from early age talent identification in sport remains difficult. Talent identification research has generally been performed using univariate analysis, which ignores multivariate relationships. To address this issue, this study used a novel higher-dimensional model to orthogonalize multivariate anthropometric and fitness data from junior rugby league players, with the aim of differentiating future career attainment. Anthropometric and fitness data from 257 Under-15 rugby league players was collected. Players were grouped retrospectively according to their future career attainment (i.e., amateur, academy, professional). Players were blindly and randomly divided into an exploratory (n = 165) and validation dataset (n = 92). The exploratory dataset was used to develop and optimize a novel higher-dimensional model, which combined singular value decomposition (SVD) with receiver operating characteristic analysis. Once optimized, the model was tested using the validation dataset. SVD analysis revealed 60 m sprint and agility 505 performance were the most influential characteristics in distinguishing future professional players from amateur and academy players. The exploratory dataset model was able to distinguish between future amateur and professional players with a high degree of accuracy (sensitivity = 85.7%, specificity = 71.1%; p<0.001), although it could not distinguish between future professional and academy players. The validation dataset model was able to distinguish future professionals from the rest with reasonable accuracy (sensitivity = 83.3%, specificity = 63.8%; p = 0.003). Through the use of SVD analysis it was possible to objectively identify criteria to distinguish future career attainment with a sensitivity over 80% using anthropometric and fitness data alone. As such, this suggests that SVD analysis may be a useful analysis tool for research and practice within talent identification.

Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis

PubMed Central

Till, Kevin; Jones, Ben L.; Cobley, Stephen; Morley, David; O'Hara, John; Chapman, Chris; Cooke, Carlton; Beggs, Clive B.

2016-01-01

Prediction of adult performance from early age talent identification in sport remains difficult. Talent identification research has generally been performed using univariate analysis, which ignores multivariate relationships. To address this issue, this study used a novel higher-dimensional model to orthogonalize multivariate anthropometric and fitness data from junior rugby league players, with the aim of differentiating future career attainment. Anthropometric and fitness data from 257 Under-15 rugby league players was collected. Players were grouped retrospectively according to their future career attainment (i.e., amateur, academy, professional). Players were blindly and randomly divided into an exploratory (n = 165) and validation dataset (n = 92). The exploratory dataset was used to develop and optimize a novel higher-dimensional model, which combined singular value decomposition (SVD) with receiver operating characteristic analysis. Once optimized, the model was tested using the validation dataset. SVD analysis revealed 60 m sprint and agility 505 performance were the most influential characteristics in distinguishing future professional players from amateur and academy players. The exploratory dataset model was able to distinguish between future amateur and professional players with a high degree of accuracy (sensitivity = 85.7%, specificity = 71.1%; p<0.001), although it could not distinguish between future professional and academy players. The validation dataset model was able to distinguish future professionals from the rest with reasonable accuracy (sensitivity = 83.3%, specificity = 63.8%; p = 0.003). Through the use of SVD analysis it was possible to objectively identify criteria to distinguish future career attainment with a sensitivity over 80% using anthropometric and fitness data alone. As such, this suggests that SVD analysis may be a useful analysis tool for research and practice within talent identification. PMID:27224653

Future vegetation ecosystem response to warming climate over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Bao, Y.; Gao, Y.; Wang, Y.

2017-12-01

The amplified vegetation response to climate variability has been found over the Tibetan Plateau (TP) in recent decades. In this study, the potential impacts of 21st century climate change on the vegetation ecosystem over the TP are assessed based on the dynamic vegetation outputs of models from Coupled Model Intercomparison Project Phase 5 (CMIP5), and the sensitivity of the TP vegetation in response to warming climate was investigated. Models project a continuous and accelerating greening in future, especially in the eastern TP, which closely associates with the plant type upgrade due to the pronouncing warming in growing season.Vegetation leaf area index (LAI) increase well follows the global warming, suggesting the warming climate instead of co2 fertilization controlls the future TP plant growth. The warming spring may advance the start of green-up day and extend the growing season length. More carbon accumulation in vegetation and soil will intensify the TP carbon cycle and will keep it as a carbon sink in future. Keywords: Leaf Area Index (LAI), Climate Change, Global Dynamic Vegetation Models (DGVMs), CMIP5, Tibetan Plateau (TP)

Responses of calcification of massive and encrusting corals to past, present, and near-future ocean carbon dioxide concentrations.

PubMed

Iguchi, Akira; Kumagai, Naoki H; Nakamura, Takashi; Suzuki, Atsushi; Sakai, Kazuhiko; Nojiri, Yukihiro

2014-12-15

In this study, we report the acidification impact mimicking the pre-industrial, the present, and near-future oceans on calcification of two coral species (Porites australiensis, Isopora palifera) by using precise pCO2 control system which can produce acidified seawater under stable pCO2 values with low variations. In the analyses, we performed Bayesian modeling approaches incorporating the variations of pCO2 and compared the results between our modeling approach and classical statistical one. The results showed highest calcification rates in pre-industrial pCO2 level and gradual decreases of calcification in the near-future ocean acidification level, which suggests that ongoing and near-future ocean acidification would negatively impact coral calcification. In addition, it was expected that the variations of parameters of carbon chemistry may affect the inference of the best model on calcification responses to these parameters between Bayesian modeling approach and classical statistical one even under stable pCO2 values with low variations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling climate change impacts on water trading.

PubMed

Luo, Bin; Maqsood, Imran; Gong, Yazhen

2010-04-01

This paper presents a new method of evaluating the impacts of climate change on the long-term performance of water trading programs, through designing an indicator to measure the mean of periodic water volume that can be released by trading through a water-use system. The indicator is computed with a stochastic optimization model which can reflect the random uncertainty of water availability. The developed method was demonstrated in the Swift Current Creek watershed of Prairie Canada under two future scenarios simulated by a Canadian Regional Climate Model, in which total water availabilities under future scenarios were estimated using a monthly water balance model. Frequency analysis was performed to obtain the best probability distributions for both observed and simulated water quantity data. Results from the case study indicate that the performance of a trading system is highly scenario-dependent in future climate, with trading effectiveness highly optimistic or undesirable under different future scenarios. Trading effectiveness also largely depends on trading costs, with high costs resulting in failure of the trading program. (c) 2010 Elsevier B.V. All rights reserved.

Current and future carbon budget at Takayama site, Japan, evaluated by a regional climate model and a process-based terrestrial ecosystem model.

PubMed

Kuribayashi, Masatoshi; Noh, Nam-Jin; Saitoh, Taku M; Ito, Akihiko; Wakazuki, Yasutaka; Muraoka, Hiroyuki

2017-06-01

Accurate projection of carbon budget in forest ecosystems under future climate and atmospheric carbon dioxide (CO 2 ) concentration is important to evaluate the function of terrestrial ecosystems, which serve as a major sink of atmospheric CO 2 . In this study, we examined the effects of spatial resolution of meteorological data on the accuracies of ecosystem model simulation for canopy phenology and carbon budget such as gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) of a deciduous forest in Japan. Then, we simulated the future (around 2085) changes in canopy phenology and carbon budget of the forest by incorporating high-resolution meteorological data downscaled by a regional climate model. The ecosystem model overestimated GPP and ER when we inputted low-resolution data, which have warming biases over mountainous landscape. But, it reproduced canopy phenology and carbon budget well, when we inputted high-resolution data. Under the future climate, earlier leaf expansion and delayed leaf fall by about 10 days compared with the present state was simulated, and also, GPP, ER and NEP were estimated to increase by 25.2%, 23.7% and 35.4%, respectively. Sensitivity analysis showed that the increase of NEP in June and October would be mainly caused by rising temperature, whereas that in July and August would be largely attributable to CO 2 fertilization. This study suggests that the downscaling of future climate data enable us to project more reliable carbon budget of forest ecosystem in mountainous landscape than the low-resolution simulation due to the better predictions of leaf expansion and shedding.

Future Changes in Major Stratospheric Warmings in CCMI Models

NASA Technical Reports Server (NTRS)

Ayarzaguena, B.; Langematz, U.; Polvani, L. M; Abalichin, J.; Akiyoshi, H.; Klekociuk, A.; Michou, M.; Morgenstern, O.; Oman, L.

2015-01-01

Major stratospheric warmings (MSWs) are one of the most important phenomena of wintertime Arctic stratospheric variability. They consist of a warming of the Arctic stratosphere and a deceleration of the polar night jet, triggered by an anomalously high injection of tropospheric wave activity into the stratosphere. Due to the relevance and the impact of MSWs on the tropospheric circulation, several model studies have investigated their potential responses to climate change. However, a wide range of results has been obtained, extending from a future increase in the frequency of MSWs to a decrease. These discrepancies might be explained by different factors such as a competition of radiative and dynamical contributors with opposite effects on the Arctic polar vortex, biases of models to reproduce the related processes, or the metric chosen for the identification of MSWs. In this study, future changes in wintertime Arctic stratospheric variability are examined in order to obtaina more precise picture of future changes in the occurrence of MSWs. In particular, transient REFC2 simulations of different CCMs involved in the Chemistry Climate Model Initiative (CCMI) are used. These simulations extend from 1960 to 2100 and include forcings by halogens and greenhouse gases following the specifications of the CCMI-REF-C2 scenario. Sea surface temperatures (SSTs) and sea-ice distributions are either prescribed from coupled climate model integrations or calculated internally in the case of fully coupled atmosphere-ocean CCMs. Potential changes in the frequency and main characteristics of MSWs in the future are investigated with special focus on the dependence of the results on the criterion for the identification of MSWs and the tropospheric forcing of these phenomena.

Predicting future protection of respirator users: Statistical approaches and practical implications.

PubMed

Hu, Chengcheng; Harber, Philip; Su, Jing

2016-01-01

The purpose of this article is to describe a statistical approach for predicting a respirator user's fit factor in the future based upon results from initial tests. A statistical prediction model was developed based upon joint distribution of multiple fit factor measurements over time obtained from linear mixed effect models. The model accounts for within-subject correlation as well as short-term (within one day) and longer-term variability. As an example of applying this approach, model parameters were estimated from a research study in which volunteers were trained by three different modalities to use one of two types of respirators. They underwent two quantitative fit tests at the initial session and two on the same day approximately six months later. The fitted models demonstrated correlation and gave the estimated distribution of future fit test results conditional on past results for an individual worker. This approach can be applied to establishing a criterion value for passing an initial fit test to provide reasonable likelihood that a worker will be adequately protected in the future; and to optimizing the repeat fit factor test intervals individually for each user for cost-effective testing.

Assessment of the present and future offshore wind power potential: a case study in a target territory of the Baltic Sea near the Latvian coast.

PubMed

Lizuma, Lita; Avotniece, Zanita; Rupainis, Sergejs; Teilans, Artis

2013-01-01

Offshore wind energy development promises to be a significant domestic renewable energy source in Latvia. The reliable prediction of present and future wind resources at offshore sites is crucial for planning and selecting the location for wind farms. The overall goal of this paper is the assessment of offshore wind power potential in a target territory of the Baltic Sea near the Latvian coast as well as the identification of a trend in the future wind energy potential for the study territory. The regional climate model CLM and High Resolution Limited Area Model (Hirlam) simulations were used to obtain the wind climatology data for the study area. The results indicated that offshore wind energy is promising for expanding the national electricity generation and will continue to be a stable resource for electricity generation in the region over the 21st century.

Distance Education and Organizational Environment

ERIC Educational Resources Information Center

East, Jean F.; LaMendola, Walter; Alter, Catherine

2014-01-01

As distance education models in social work education continue to grow, this study addresses prevalence and type of models in graduate social work programs and the perceptions of deans about the future of e-learning models of curriculum delivery. The study was an exploratory sequential mixed-methods design including a national survey of 121…

Learning from Higgs physics at future Higgs factories

NASA Astrophysics Data System (ADS)

Gu, Jiayin; Li, Honglei; Liu, Zhen; Su, Shufang; Su, Wei

2017-12-01

Future Higgs factories can reach impressive precision on Higgs property measurements. In this paper, instead of conventional focus of Higgs precision in certain interaction bases, we explore its sensitivity to new physics models at the electron-positron colliders. In particular, we study two categories of new physics models, Standard Model (SM) with a real scalar singlet extension, and Two Higgs Double Model (2HDM) as examples of weakly-interacting models, Minimal Composite Higgs Model (MCHM) and three typical patterns of the more general operator counting for strong interacting models as examples of strong dynamics. We perform a global fit to various Higgs search channels to obtain the 95% C.L. constraints on the model parameter space. In the SM with a singlet extension, we obtain the limits on the singlet-doublet mixing angle sin θ, as well as the more general Wilson coefficients of the induced higher dimensional operators. In the 2HDM, we analyze tree level effects in tan β vs. cos( β - α) plane, as well as the one-loop contributions from the heavy Higgs bosons in the alignment limit to obtain the constraints on heavy Higgs masses for different types of 2HDM. In strong dynamics models, we obtain lower limits on the strong dynamics scale. In addition, once deviations of Higgs couplings are observed, they can be used to distinguish different models. We also compare the sensitivity of various future Higgs factories, namely Circular Electron Positron Collider (CEPC), Future Circular Collider (FCC)-ee and International Linear Collider (ILC).

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...

Double elementary Goldstone Higgs boson production in future linear colliders

NASA Astrophysics Data System (ADS)

Guo, Yu-Chen; Yue, Chong-Xing; Liu, Zhi-Cheng

2018-03-01

The Elementary Goldstone Higgs (EGH) model is a perturbative extension of the Standard Model (SM), which identifies the EGH boson as the observed Higgs boson. In this paper, we study pair production of the EGH boson in future linear electron positron colliders. The cross-sections in the TeV region can be changed to about ‑27%, 163% and ‑34% for the e+e‑→ Zhh, e+e‑→ νν¯hh and e+e‑→ tt¯hh processes with respect to the SM predictions, respectively. According to the expected measurement precisions, such correction effects might be observed in future linear colliders. In addition, we compare the cross-sections of double SM-like Higgs boson production with the predictions in other new physics models.

Optimized ISRU Propellants for Propulsion and Power Needs for Future Mars Colonization

NASA Astrophysics Data System (ADS)

Rice, Eric E.; Gustafson, Robert J.; Gramer, Daniel J.; Chiaverini, Martin J.; Teeter, Ronald R.; White, Brant C.

2003-01-01

In recent studies (Rice, 2000, 2002) conducted by ORBITEC for the NASA Institute for Advanced Concepts (NIAC), we conceptualized systems and an evolving optimized architecture for producing and utilizing Mars-based in-situ space resources utilization (ISRU) propellant combinations for future Mars colonization. The propellants are to be used to support the propulsion and power systems for ground and flight vehicles. The key aspect of the study was to show the benefits of ISRU, develop an analysis methodology, as well as provide guidance to propellant system choices in the future based upon what is known today about Mars. The study time frame included an early unmanned and manned exploration period (through 2040) and two colonization scenarios that are postulated to occur from 2040 to 2090. As part of this feasibility study, ORBITEC developed two different Mars colonization scenarios: a low case that ends with a 100-person colony (an Antarctica analogy) and a high case that ends with a 10,000-person colony (a Mars terraforming scenario). A population growth model, mission traffic model, and infrastructure model were developed for each scenario to better understand the requirements of future Mars colonies. Additionally, propellant and propulsion systems design concepts were developed. Cost models were also developed to allow comparison of the different ISRU propellant approaches. This paper summarizes the overall results of the study. ISRU proved to be a key enabler for these colonization missions. Carbon monoxide and oxygen, proved to be the most cost-effective ISRU propellant combination. The entire final reports Phase I and II) and all the details can be found at the NIAC website www.niac.usra.edu.

The futures of climate engineering

NASA Astrophysics Data System (ADS)

Low, Sean

2017-01-01

This piece examines the need to interrogate the role of the conceptions of the future, as embedded in academic papers, policy documents, climate models, and other artifacts that serve as currencies of the science-society interface, in shaping scientific and policy agendas in climate engineering. Growing bodies of work on framings, metaphors, and models in the past decade serve as valuable starting points, but can benefit from integration with science and technology studies work on the sociology of expectations, imaginaries, and visions. Potentially valuable branches of work to come might be the anticipatory use of the future: the design of experimental spaces for exploring the future of an engineered climate in service of responsible research and innovation, and the integration of this work within the unfolding context of the Paris Agreement.

A Positive Model for Reducing and Preventing School Burnout in High School Students

ERIC Educational Resources Information Center

Aypay, Ayse

2017-01-01

This study aims to develop and test the validity of a model limited to attitude towards the future and subjective well-being for reducing and preventing the school burnout that high school students can experience. The study is designed as a relational screening model conducted over 389 high school students. The data in this study are analyzed…

AnnAGNPS Model Application for the Future Midwest Landscape Study

EPA Science Inventory

The Future Midwest Landscape (FML) project is part of the US Environmental Protection Agency (EPA)’s new Ecosystem Services Research Program, undertaken to examine the variety of ways in which landscapes that include crop lands, conservation areas, wetlands, lakes, and streams af...

Future travel demand and its implications for transportation infrastructure investments in the Texas Triangle.

DOT National Transportation Integrated Search

2009-03-01

This study takes a megaregion approach to project future travel demand and choice of transport : modes in the Texas Triangle, which is encompassed by four major metropolitan areas, Dallas-Fort : Worth, Houston, San Antonio, and Austin. The model was ...

Paradigm Shifts Towards Understanding the Full Story of Mars, a Possible Future

NASA Astrophysics Data System (ADS)

Diniega, S.; Zurek, R.

2017-02-01

A new phase of Mars and planetary science exploration has opened that studies Mars through a holistic lens. We describe the advances needed for achieving this future: in measurement characteristic and type; in technology and access; and in model development.

Determining the impacts of climate change and catchment development on future water availability in Tasmania, Australia

NASA Astrophysics Data System (ADS)

Post, David

2010-05-01

In a water-scarce country such as Australia, detailed, accurate and reliable assessments of current and future water availability are essential in order to adequately manage the limited water resource. This presentation describes a recently completed study which provided an assessment of current water availability in Tasmania, Australia, and also determined how this water availability would be impacted by climate change and proposed catchment development by the year 2030. The Tasmania Sustainable Yields Project (http://www.csiro.au/partnerships/TasSY.html) assessed current water availability through the application of rainfall-runoff models, river models, and recharge and groundwater models. These were calibrated to streamflow records and parameterised using estimates of current groundwater and surface water extractions and use. Having derived a credible estimate of current water availability, the impacts of future climate change on water availability were determined through deriving changes in rainfall and potential evapotranspiration from 15 IPCC AR4 global climate models. These changes in rainfall were then dynamically downscaled using the CSIRO-CCAM model over the relatively small study area (50,000 square km). A future climate sequence was derived by modifying the historical 84-year climate sequence based on these changes in rainfall and potential evapotranspiration. This future climate sequence was then run through the rainfall-runoff, river, recharge and groundwater models to give an estimate of water availability under future climate. To estimate the impacts of future catchment development on water availability, the models were modified and re-run to reflect projected increases in development. Specifically, outputs from the rainfall-runoff and recharge models were reduced over areas of projected future plantation forestry. Conversely, groundwater recharge was increased over areas of new irrigated agriculture and new extractions of water for irrigation were implemented in the groundwater and river models. Results indicate that historical average water availability across the project area was 21,815 GL/year. Of this, 636 GL/year of surface water and 38 GL/year of groundwater are currently extracted for use. By 2030, rainfall is projected to decrease by an average of 3% over the project area. This decrease in rainfall and concurrent increase in potential evapotranspiration leads to a decrease in water availability of 5% by 2030. As a result of lower streamflows, under current cease-to-take rules, currently licensed extractions are projected to decrease by 3% (19 GL/year). This however is offset by an additional 120 GL/year of extractions for proposed new irrigated agriculture. These new extractions, along with the increase in commercial forest plantations lead to a reduction in total surface water of 1% in addition to the 5% reduction due to climate change. Results from this study are being used by the Tasmanian and Australian governments to guide the development of a sustainable irrigated agriculture industry in Tasmania. In part, this is necessary to offset the loss of irrigated agriculture from the southern Murray-Darling Basin where climate change induced reductions in rainfall are projected to be far worse.

Xanthos – A Global Hydrologic Model

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

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.

Xanthos is an open-source hydrologic model, written in Python, designed to quantify and analyse global water availability. Xanthos simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos was designed to be extensible and used by scientists that study global water supply and work with the Global Change Assessment Model (GCAM). Xanthos uses a user-defined configuration file to specify model inputs, outputs and parameters. Xanthos has been tested using actual global data sets and the model is able to provide historical observations and future estimates of renewable freshwater resourcesmore » in the form of total runoff.« less

Xanthos – A Global Hydrologic Model

DOE PAGES

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...

2017-09-11

Xanthos is an open-source hydrologic model, written in Python, designed to quantify and analyse global water availability. Xanthos simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos was designed to be extensible and used by scientists that study global water supply and work with the Global Change Assessment Model (GCAM). Xanthos uses a user-defined configuration file to specify model inputs, outputs and parameters. Xanthos has been tested using actual global data sets and the model is able to provide historical observations and future estimates of renewable freshwater resourcesmore » in the form of total runoff.« less

The Future of Cell Biology: Emerging Model Organisms.

PubMed

Goldstein, Bob; King, Nicole

2016-11-01

Most current research in cell biology uses just a handful of model systems including yeast, Arabidopsis, Drosophila, Caenorhabditis elegans, zebrafish, mouse, and cultured mammalian cells. And for good reason - for many biological questions, the best system for the question is likely to be found among these models. However, in some cases, and particularly as the questions that engage scientists broaden, the best system for a question may be a little-studied organism. Modern research tools are facilitating a renaissance for unusual and interesting organisms as emerging model systems. As a result, we predict that an ever-expanding breadth of model systems may be a hallmark of future cell biology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Patient-Clinician Communication About Pain: A Conceptual Model and Narrative Review.

PubMed

Henry, Stephen G; Matthias, Marianne S

2018-02-01

Productive patient-clinician communication is an important component of effective pain management, but we know little about how patients and clinicians actually talk about pain in clinical settings and how it might be improved to produce better patient outcomes. The objective of this review was to create a conceptual model of patient-clinician communication about noncancer pain, review and synthesize empirical research in this area, and identify priorities for future research. A conceptual model was developed that drew on existing pain and health communication research. CINAHL, EMBASE, and PubMed were searched to find studies reporting empirical data on patient-clinician communication about noncancer pain; results were supplemented with manual searches. Studies were categorized and analyzed to identify crosscutting themes and inform model development. The conceptual model comprised the following components: contextual factors, clinical interaction, attitudes and beliefs, and outcomes. Thirty-nine studies met inclusion criteria and were analyzed based on model components. Studies varied widely in quality, methodology, and sample size. Two provisional conclusions were identified: contrary to what is often reported in the literature, discussions about analgesics are most frequently characterized by patient-clinician agreement, and self-presentation during patient-clinician interactions plays an important role in communication about pain and opioids. Published studies on patient-clinician communication about noncancer pain are few and diverse. The conceptual model presented here can help to identify knowledge gaps and guide future research on communication about pain. Investigating the links between communication and pain-related outcomes is an important priority for future research. © 2018 American Academy of Pain Medicine. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Consistency of climate change projections from multiple global and regional model intercomparison projects

NASA Astrophysics Data System (ADS)

Fernández, J.; Frías, M. D.; Cabos, W. D.; Cofiño, A. S.; Domínguez, M.; Fita, L.; Gaertner, M. A.; García-Díez, M.; Gutiérrez, J. M.; Jiménez-Guerrero, P.; Liguori, G.; Montávez, J. P.; Romera, R.; Sánchez, E.

2018-03-01

We present an unprecedented ensemble of 196 future climate projections arising from different global and regional model intercomparison projects (MIPs): CMIP3, CMIP5, ENSEMBLES, ESCENA, EURO- and Med-CORDEX. This multi-MIP ensemble includes all regional climate model (RCM) projections publicly available to date, along with their driving global climate models (GCMs). We illustrate consistent and conflicting messages using continental Spain and the Balearic Islands as target region. The study considers near future (2021-2050) changes and their dependence on several uncertainty sources sampled in the multi-MIP ensemble: GCM, future scenario, internal variability, RCM, and spatial resolution. This initial work focuses on mean seasonal precipitation and temperature changes. The results show that the potential GCM-RCM combinations have been explored very unevenly, with favoured GCMs and large ensembles of a few RCMs that do not respond to any ensemble design. Therefore, the grand-ensemble is weighted towards a few models. The selection of a balanced, credible sub-ensemble is challenged in this study by illustrating several conflicting responses between the RCM and its driving GCM and among different RCMs. Sub-ensembles from different initiatives are dominated by different uncertainty sources, being the driving GCM the main contributor to uncertainty in the grand-ensemble. For this analysis of the near future changes, the emission scenario does not lead to a strong uncertainty. Despite the extra computational effort, for mean seasonal changes, the increase in resolution does not lead to important changes.

Understanding the joint behavior of temperature and precipitation for climate change impact studies

NASA Astrophysics Data System (ADS)

Rana, Arun; Moradkhani, Hamid; Qin, Yueyue

2017-07-01

The multiple downscaled scenario products allow us to assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Probabilistic assessments of both climatic variables help better understand the interdependence of the two and thus, in turn, help in assessing the future with confidence. In the present study, we use ensemble of statistically downscaled precipitation and temperature from various models. The dataset used is multi-model ensemble of 10 global climate models (GCMs) downscaled product from CMIP5 daily dataset using the Bias Correction and Spatial Downscaling (BCSD) technique, generated at Portland State University. The multi-model ensemble of both precipitation and temperature is evaluated for dry and wet periods for 10 sub-basins across Columbia River Basin (CRB). Thereafter, copula is applied to establish the joint distribution of two variables on multi-model ensemble data. The joint distribution is then used to estimate the change in trends of said variables in future, along with estimation of the probabilities of the given change. The joint distribution trends vary, but certainly positive, for dry and wet periods in sub-basins of CRB. Dry season, generally, is indicating a higher positive change in precipitation than temperature (as compared to historical) across sub-basins with wet season inferring otherwise. Probabilities of changes in future, as estimated from the joint distribution, indicate varied degrees and forms during dry season whereas the wet season is rather constant across all the sub-basins.

Analysis of snow-glacial historical and projected flows in Olivares river basin. Comparison between DHSVM and WEAP models.

NASA Astrophysics Data System (ADS)

Cepeda, Javier; Vargas, Ximena

2017-04-01

In the Andes Mountains, in central Chile, glaciers are a key element to both environment and economy, since they contribute highly to streamflow during the summer season. Many studies have been performed in order to understand the actual contribution of glacial-based streamflow and the expected response of glaciers to climatological alterations such as climate change. This work studies and analyses the historical and future streamflow on the Olivares river basin, located close to Chile's capital city, Santiago, under climatic change scenario RCP8.5. For this, we use two hydrological models with different topology, to have more consistency in the results, and analysing the differences because of the conceptualization of the processes and its spatial scale. DHSVM is a distributed, physically based model, while WEAP is a semi-distributed model that represents some processes conceptually and others physically based. Both models are calibrated considering streamflow and snow cover data from the period 2001-2012 at a daily scale. Additionally, comparisons between the modelled glacier area variations and LANDSAT images are performed to strengthen the calibration process. Climate change projections are obtained from five Global Circulation Models (GCM) under RCP8.5 scenario. Changes in glacier area, volume and glacial streamflow contribution to basin discharge are analysed, comparing two future time lapses, near-future period (2015-2044) and far-future (2045-2074), to a baseline period (1985-2004). The basin has an area of 543 km2, with elevations ranging from 1,528 to 6,024 m.a.s.l. and an important glacier presence. According to the National Glacier Cadastre developed by Chile Water Authority (DGA) in 2012, there are 80 uncovered glaciers within the basin, the most important being Juncal Sur, Olivares Alfa, Beta and Gamma. Glacier area represented 17% of the basin in 1985, while they made up only to 11% in 2015.The glaciers are located at altitudes ranging from 3,500 to 6,000 m.a.s.l., most on the vicinity of 4,500 m.a.s.l. Analysing variations in meteorological information between baseline, for the near and far future periods we obtain an increase of 1.3°C and 2.9°C respectively. Analogously, a decrease of 33.6 mm and 93.2 mm for the annual precipitation is projected for the same corresponding periods. Results from both models show that most of the glacial area will have melted away by the end of the far-future period, with only 1.2 km2 and 6.8 km2 remaining, according to DHSVM and WEAP models respectively. Also for the far future period, total streamflow decreases respect to baseline period between 15 and 46%, while glacier streamflow decreases between 53 and 85% in far future, depending of the GCM and hydrological model used.

Impact of future urban growth on regional climate changes in the Seoul Metropolitan Area, Korea.

PubMed

Kim, Hyunsu; Kim, Yoo-Keun; Song, Sang-Keun; Lee, Hwa Woon

2016-11-15

The influence of changes in future urban growth (e.g., land use changes) on the future climate variability in the Seoul metropolitan area (SMA), Korea was evaluated using the WRF model and an urban growth model (SLEUTH). The land use changes in the study area were simulated using the SLEUTH model under three different urban growth scenarios: (1) current development trends scenario (SC 1), (2) managed development scenario (SC 2) and (3) ecological development scenario (SC 3). The maximum difference in the ratio of urban growth between SC 1 and SC 3 (SC 1 - SC 3) for 50years (2000-2050) was approximately 6.72%, leading to the largest differences (0.01°C and 0.03ms(-1), respectively) in the mean air temperature at 2m (T2) and wind speed at 10m (WS10). From WRF-SLEUTH modeling, the effects of future urban growth (or future land use changes) in the SMA are expected to result in increases in the spatial mean T2 and WS10 of up to 1.15°C and 0.03ms(-1), respectively, possibly due to thermal circulation caused by the thermal differences between urban and rural regions. Copyright © 2016 Elsevier B.V. All rights reserved.

Future Changes to ENSO Temperature and Precipitation Teleconnections Under Warming

NASA Astrophysics Data System (ADS)

Perry, S.; McGregor, S.; Sen Gupta, A.; England, M. H.

2016-12-01

As the dominant mode of interannual climate variability, the El Niño-Southern Oscillation (ENSO) modulates temperature and rainfall globally, additionally contributing to weather extremes. Anthropogenic climate change has the potential to alter the strength and frequency of ENSO and may also alter ENSO-driven atmospheric teleconnections, affecting ecosystems and human activity in regions far removed from the tropical Pacific. State-of-art climate models exhibit considerable disagreement in projections of future changes in ENSO sea surface temperature variability. Despite this uncertainty, recent model studies suggest that the precipitation response to ENSO will be enhanced in the tropical Pacific under future warming, and as such the societal impacts of ENSO will increase. Here we use temperature and precipitation data from an ensemble of 41 CMIP5 models to show where ENSO teleconnections are being enhanced and dampened in a high-emission future scenario (RCP8.5) focusing on the changes that are occurring over land areas globally. Although there is some spread between the model projections, robust changes with strong ensemble agreement are found in certain locations, including amplification of teleconnections in southeast Australia, South America and the Maritime Continent. Our results suggest that in these regions future ENSO events will lead to more extreme temperature and rainfall responses.

Moisture fluxes towards Switzerland: investigating future changes in CMIP5 climate models

NASA Astrophysics Data System (ADS)

Fazan, Valerie; Martius, Olivia; Martynov, Andrey; Panziera, Luca

2017-04-01

High integrated vapor transport (IVT) in the atmosphere directed perpendicular to the orography is an important proxy for flood related precipitation in many mountainous areas around the world. Here we focus on flood related IVT and its changes in a warmer climate in Switzerland, where most high-impact floods events in the past 30 years were connected to exceptional IVT upstream of the mountains. Our study aims at investigating how these critical IVT values are projected to evolve in the future in a changing climate. The IVT is computed from 15 CMIP5 climate models for the past (1950-2005) and the future (2006-2100) under the RCP 8.5 scenario ("business as usual"). In order to check the accuracy of the models and the effect of the varying resolution, present day IVT from the CMIP5 models is compared with the ERA-Interim reanalysis data (period 1979-2015). A quantile mapping technique is then used to correct biases. The same bias corrections are applied to the future (2006-2100) IVT data. Finally, future changes in extreme IVT are investigated. This includes an analysis of changes in the magnitude and direction of the moisture flux in the different seasons for different regions in Switzerland.

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.

From Mental Game to Cultural Praxis: A Cultural Studies Model's Implications for the Future of Sport Psychology

ERIC Educational Resources Information Center

Ryba, Tatiana V.; Wright, Handel Kashope

2005-01-01

This paper explores the implications of a cultural studies as praxis heuristic "model: for transforming sport psychology". It provides a brief introduction to both cultural studies and sport psychology and discusses a cultural studies intersection with sport studies and sport psychology. Cultural studies, it asserts, provides one of several…

Future Orientation, Impulsivity, and Problem Behaviors: A Longitudinal Moderation Model

ERIC Educational Resources Information Center

Chen, Pan; Vazsonyi, Alexander T.

2011-01-01

In the current study, based on a sample of 1,873 adolescents between 11.4 and 20.9 years of age from the first 3 waves of the National Longitudinal Study of Adolescent Health, we investigated the longitudinal effects of future orientation on levels of and developmental changes in problem behaviors, while controlling for the effects by impulsivity;…

Scenario studies as a synthetic and integrative research activity for Long-Term Ecological Research

Treesearch

Jonathan R. Thompson; Arnim Wiek; Frederick J. Swanson; Stephen R. Carpenter; Nancy Fresco; Teresa Hollingsworth; Thomas A. Spies; David R. Foster

2012-01-01

Scenario studies have emerged as a powerful approach for synthesizing diverse forms of research and for articulating and evaluating alternative socioecological futures. Unlike predictive modeling, scenarios do not attempt to forecast the precise or probable state of any variable at a given point in the future. Instead, comparisons among a set of contrasting scenarios...

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

Mounting for Fabrication, Metrology, and Assembly of Full Shell Grazing Incidence Optics

NASA Technical Reports Server (NTRS)

Roche, Jacqueline M.; Gubarev, Mikhail V.; O'Dell, Stephen L.; Kolodziejczak, Jeffery; Weisskopf, Martin C.; Ramsey, Brian D.; Elsner, Ronald F.

2014-01-01

Future x-ray telescopes will likely require lightweight mirrors to attain the large collecting areas needed to accomplish the science objectives. Understanding and demonstrating processes now is critical to achieving sub-arcsecond performance in the future. Consequently, designs not only of the mirrors but of fixtures for supporting them during fabrication, metrology, handling, assembly, and testing must be adequately modeled and verified. To this end, MSFC is using finite-element modeling to study the effects of mounting on full-shell grazing-incidence mirrors, during all processes leading to flight mirror assemblies. Here we report initial results of this study.

Climate model biases and statistical downscaling for application in hydrologic model

USDA-ARS?s Scientific Manuscript database

Climate change impact studies use global climate model (GCM) simulations to define future temperature and precipitation. The best available bias-corrected GCM output was obtained from Coupled Model Intercomparison Project phase 5 (CMIP5). CMIP5 data (temperature and precipitation) are available in d...

Future climate and land uses effects on flow and nutrient loads of a Mediterranean catchment in South Australia.

PubMed

Shrestha, Manoj K; Recknagel, Friedrich; Frizenschaf, Jacqueline; Meyer, Wayne

2017-07-15

Mediterranean catchments experience already high seasonal variability alternating between dry and wet periods, and are more vulnerable to future climate and land use changes. Quantification of catchment response under future changes is particularly crucial for better water resources management. This study assessed the combined effects of future climate and land use changes on water yield, total nitrogen (TN) and total phosphorus (TP) loads of the Mediterranean Onkaparinga catchment in South Australia by means of the eco-hydrological model SWAT. Six different global climate models (GCMs) under two representative concentration pathways (RCPs) and a hypothetical land use change were used for future simulations. The climate models suggested a high degree of uncertainty, varying seasonally, in both flow and nutrient loads; however, a decreasing trend was observed. Average monthly TN and TP load decreased up to -55% and -56% respectively and were found to be dependent on flow magnitude. The annual and seasonal water yield and nutrient loads may only slightly be affected by envisaged land uses, but significantly altered by intermediate and high emission scenarios, predominantly during the spring season. The combined scenarios indicated the possibility of declining flow in future but nutrient enrichment in summer months, originating mainly from the land use scenario, that may elevate the risk of algal blooms in downstream drinking water reservoir. Hence, careful planning of future water resources in a Mediterranean catchment requires the assessment of combined effects of multiple climate models and land use scenarios on both water quantity and quality. Copyright © 2017 Elsevier B.V. All rights reserved.

Projecting future grassland performance in the Greater Platte River Basin to assess sustainability for potential biofuel feedstock areas

NASA Astrophysics Data System (ADS)

Gu, Y.; Wylie, B. K.; Phuyal, K.

2012-12-01

In previous studies, we used vegetation condition information from archival records of satellite data (i.e., 10-year time series of Normalized Difference Vegetation Index (NDVI) data), site geophysical and biophysical features (e.g., elevation, slope and aspect, and soils), and weather and climate drivers to build ecosystem performance (EP) models to dynamically monitor EP (DMEP) in the Greater Platte River Basin (GPRB). Ecosystem performance is a surrogate approach for measuring ecosystem productivity. We estimated ecosystem site potentials (i.e., long-term ecosystem productivities), weather-based expected EP (EEP), and rangeland conditions based on these EP models. Validation of the EP results using ground observations (e.g., percentage of bare soil, LANDFIRE maps, stocking rate, and crop yield data) demonstrated the reliability of these EP models. We used this DMEP method to identify grasslands that are potentially suitable for cellulosic biofuel feedstock (e.g., switchgrass) development in the GPRB. The objectives of this study are to (1) project the future grassland EP; (2) assess the changes and trends of the future EP; and (3) examine the future sustainability of the identified biofuel feedstock areas in the GPRB. We used the EP models and future climate projections to estimate future (e.g., 2050 and 2099) climate-based projections of grassland performance in the GPRB. The future climate data were derived from the National Center for Atmospheric Research (NCAR) Community Climate System Model 3.0 (CCSM3) "SRES A1B" (a "middle" emissions path) obtained from the "Bias Corrected and Downscaled WCRP CMIP3 Climate Projections" archive (http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections). Results show that, under climate scenario A1B, the potential biofuel feedstock areas in the more mesic Eastern part of the GPRB will remain productive in the future (the spatially averaged EPs for these areas are 3335 kg ha-1 year-1, 3355 kg ha-1 year-1, and 3341 kg ha-1 year-1 for the site potential, the 2050 EEP, and the 2099 EEP, respectively). Therefore, the identified potential biofuel feedstock areas will continue to be sustainable for future biofuel development. On the other hand, the identified non-biofuel grasslands in the drier Western part of the GPRB would be expected to stay unproductive, with a slight decline in the EP trend in the future (spatially averaged EPs are 1983 kg ha-1 year-1, 1977 kg ha-1 year-1, and 1964 kg ha-1 year-1 for the site potential, the 2050 EEP, and the 2099 EEP, respectively). Thus, these areas will continue to be unsuitable for biofuel feedstock development in the future. The resulting future grassland EEP maps can be used as a reference by land managers to assess the future sustainability and feasibility of the potential biofuel feedstock areas.

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.

Analysis of Science and Technology Trend Based on Word Usage in Digitized Books

NASA Astrophysics Data System (ADS)

Yun, Jinhyuk; Kim, Pan-Jun; Jeong, Hawoong

2013-03-01

Throughout mankind's history, forecasting and predicting future has been a long-lasting interest to our society. Many fortune-tellers have tried to forecast the future by ``divine'' items. Sci-fi writers have also imagined what the future would look like. However most of them have been illogical and unscientific. Meanwhile, scientists have also attempted to discover future trend of science. Many researchers have used quantitative models to study how new ideas are used and spread. Besides the modeling works, in the early 21st century, the rise of data science has provided another prospect of forecasting future. However many studies have focused on very limited set of period or age, due to the limitations of dataset. Hence, many questions still remained unanswered. Fortunately, Google released a new dataset named ``Google N-Gram Dataset.'' This dataset provides us with 5 million words worth of literature dating from 1520 to 2008, and this is nearly 4% of publications ever printed. With this new time-varying dataset, we studied the spread and development of technologies by searching ``Science and Technology'' related words from 1800 to 2000. By statistical analysis, some general scaling laws were discovered. And finally, we determined factors that strongly affect the lifecycle of a word.

Testing three pathways to substance use and delinquency among low-income African American adolescents☆

PubMed Central

Marotta, Phillip L.; Voisin, Dexter R.

2017-01-01

Objective Mounting literature suggests that parental monitoring, risky peer norms, and future orientation correlate with illicit drug use and delinquency. However, few studies have investigated these constructs simultaneously in a single statistical model with low income African American youth. This study examined parental monitoring, peer norms and future orientation as primary pathways to drug use and delinquent behaviors in a large sample of African American urban adolescents. Methods A path model tested direct paths from peer norms, parental monitoring, and future orientation to drug use and delinquency outcomes after adjusting for potential confounders such as age, socioeconomic, and sexual orientation in a sample of 541 African American youth. Results Greater scores on measures of risky peer norms were associated with heightened risk of delinquency with an effect size that was twice in magnitude compared to the protective effects of future orientation. Regarding substance use, greater perceived risky peer norms correlated with the increased likelihood of substance use with a standardized effect size 3.33 times in magnitude compared to the protective effects of parental monitoring. Conclusions Findings from this study suggest that interventions targeting risky peer norms among adolescent African American youth may correlate with a greater impact on reductions in substance use and delinquency than exclusively targeting parental monitoring or future orientation. PMID:28974824

Testing three pathways to substance use and delinquency among low-income African American adolescents.

PubMed

Marotta, Phillip L; Voisin, Dexter R

2017-04-01

Mounting literature suggests that parental monitoring, risky peer norms, and future orientation correlate with illicit drug use and delinquency. However, few studies have investigated these constructs simultaneously in a single statistical model with low income African American youth. This study examined parental monitoring, peer norms and future orientation as primary pathways to drug use and delinquent behaviors in a large sample of African American urban adolescents. A path model tested direct paths from peer norms, parental monitoring, and future orientation to drug use and delinquency outcomes after adjusting for potential confounders such as age, socioeconomic, and sexual orientation in a sample of 541 African American youth. Greater scores on measures of risky peer norms were associated with heightened risk of delinquency with an effect size that was twice in magnitude compared to the protective effects of future orientation. Regarding substance use, greater perceived risky peer norms correlated with the increased likelihood of substance use with a standardized effect size 3.33 times in magnitude compared to the protective effects of parental monitoring. Findings from this study suggest that interventions targeting risky peer norms among adolescent African American youth may correlate with a greater impact on reductions in substance use and delinquency than exclusively targeting parental monitoring or future orientation.

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.

Future Defence Budget Constraints: Challenges and Opportunities (Contraintes futures sur les budgets de defense: Defis et opportunites)

DTIC Science & Technology

2016-12-01

collaborative effort is addressed by six Technical Panels who manage a wide range of scientific research activities, a Group specialising in modelling and...HFM Human Factors and Medicine Panel • IST Information Systems Technology Panel • NMSG NATO Modelling and Simulation Group • SAS System Analysis...and Studies Panel • SCI Systems Concepts and Integration Panel • SET Sensors and Electronics Technology Panel These Panels and Group are the

The Non-Human Primate Experimental Glaucoma Model

PubMed Central

Burgoyne, Claude F.

2015-01-01

The purpose of this report is to summarize the current strengths and weaknesses of the non-human primate (NHP) experimental glaucoma (EG) model through sections devoted to its history, methods, important findings, alternative optic neuropathy models and future directions. NHP EG has become well established for studying human glaucoma in part because the NHP optic nerve head (ONH) shares a close anatomic association with the human ONH and because it provides the only means of systematically studying the very earliest visual system responses to chronic IOP elevation, i.e. the conversion from ocular hypertension to glaucomatous damage. However, NHPs are impractical for studies that require large animal numbers, demonstrate spontaneous glaucoma only rarely, do not currently provide a model of the neuropathy at normal levels of IOP, and cannot easily be genetically manipulated, except through tissue-specific, viral vectors. The goal of this summary is to direct NHP EG and non-NHP EG investigators to the previous, current and future accomplishment of clinically relevant knowledge in this model. PMID:26070984

Sensitivity of Regional Hydropower Generation to the Projected Changes in Future Watershed Hydrology

NASA Astrophysics Data System (ADS)

Kao, S. C.; Naz, B. S.; Gangrade, S.

2015-12-01

Hydropower is a key contributor to the renewable energy portfolio due to its established development history and the diverse benefits it provides to the electric power systems. With the projected change in the future watershed hydrology, including shift of snowmelt timing, increasing occurrence of extreme precipitation, and change in drought frequencies, there is a need to investigate how the regional hydropower generation may change correspondingly. To evaluate the sensitivity of watershed storage and hydropower generation to future climate change, a lumped Watershed Runoff-Energy Storage (WRES) model is developed to simulate the annual and seasonal hydropower generation at various hydropower areas in the United States. For each hydropower study area, the WRES model use the monthly precipitation and naturalized (unregulated) runoff as inputs to perform a runoff mass balance calculation for the total monthly runoff storage in all reservoirs and retention facilities in the watershed, and simulate the monthly regulated runoff release and hydropower generation through the system. The WRES model is developed and calibrated using the historic (1980-2009) monthly precipitation, runoff, and generation data, and then driven by a large set of dynamically- and statistically-downscaled Coupled Model Intercomparison Project Phase 5 climate projections to simulate the change of watershed storage and hydropower generation under different future climate scenarios. The results among different hydropower regions, storage capacities, emission scenarios, and timescales are compared and discussed in this study.

Regeneration of three pine species in a Mediterranean forest: A study to test predictions from species distribution models under changing climates.

PubMed

Tíscar, P A; Candel-Pérez, D; Estrany, J; Balandier, P; Gómez, R; Lucas-Borja, M E

2017-04-15

The study tested the hypothesis that future changes in the composition of tree communities, as predicted by species distribution models, could already be apparent in the current regeneration patterns of three pine species (Pinus pinaster, P. nigra and P. sylvestris)inhabiting the central-eastern mountains of Spain. We carried out both an observational study and a seed-sowing experiment to analyze, along an altitudinal and latitudinal gradient, whether recent recruitment patterns indicate an expansion of P. pinaster forests to the detriment of P. nigra ones in the low-altitude southern sites of these mountains; or whether P. sylvestris is being replaced by P. nigra in the high-altitude sites from the same area. The observational study gathered data from 561 plots of the Spanish National Forest Inventory. The seed-sowing experiment tested the effects of irrigation and stand basal area on seedling emergence and survival. Data were analyzed by means of Generalized Linear Models and Generalized Linear Mixed Models. Regeneration of the three pine species responded similarly to the explicative factors studied, but the density of tree seedlings and saplings exhibited a wide spatial heterogeneity. This result suggested that a mosaic of site- and species-specific responses to climate change might mislead model projections on the future forest occupancy of tree species. Yet, we found no indications of neither an expansion nor a contraction of the near future forest occupancy of the tree species studied. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Mathematical Models for Immunology: Current State of the Art and Future Research Directions.

PubMed

Eftimie, Raluca; Gillard, Joseph J; Cantrell, Doreen A

2016-10-01

The advances in genetics and biochemistry that have taken place over the last 10 years led to significant advances in experimental and clinical immunology. In turn, this has led to the development of new mathematical models to investigate qualitatively and quantitatively various open questions in immunology. In this study we present a review of some research areas in mathematical immunology that evolved over the last 10 years. To this end, we take a step-by-step approach in discussing a range of models derived to study the dynamics of both the innate and immune responses at the molecular, cellular and tissue scales. To emphasise the use of mathematics in modelling in this area, we also review some of the mathematical tools used to investigate these models. Finally, we discuss some future trends in both experimental immunology and mathematical immunology for the upcoming years.

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.

A comparative assessment of projected meteorological and hydrological droughts: Elucidating the role of temperature

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Moradkhani, Hamid; Demirel, Mehmet C.

2017-10-01

The changing climate and the associated future increases in temperature are expected to have impacts on drought characteristics and hydrologic cycle. This paper investigates the projected changes in spatiotemporal characteristics of droughts and their future attributes over the Willamette River Basin (WRB) in the Pacific Northwest U.S. The analysis is performed using two subsets of downscaled CMIP5 global climate models (GCMs) each consisting of 10 models from two future scenarios (RCP4.5 and RCP8.5) for 30 years of historical period (1970-1999) and 90 years of future projections (2010-2099). Hydrologic modeling is conducted using the Precipitation Runoff Modeling System (PRMS) as a robust distributed hydrologic model with lower computational cost compared to other models. Meteorological and hydrological droughts are studied using three drought indices (i.e. Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, Standardized Streamflow Index). Results reveal that the intensity and duration of hydrological droughts are expected to increase over the WRB, albeit the annual precipitation is expected to increase. On the other hand, the intensity of meteorological droughts do not indicate an aggravation for most cases. We explore the changes of hydrometeolorogical variables over the basin in order to understand the causes for such differences and to discover the controlling factors of drought. Furthermore, the uncertainty of projections are quantified for model, scenario, and downscaling uncertainty.

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.

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.

Fatty Acid Synthase Activity as a Target for c-Met Driven Prostate Cancer

DTIC Science & Technology

2013-07-01

to aid future studies. Identification is a highly significant finding with regard to the potential for future therapeutic development targeted at...Met trafficking, stability, and ultimately oncogenic potential . Palmitoylation defective mutants will be used in animal models of c-Met driven tumor...growth (Aim 2). In addition, future work toward identifying the enzyme responsible for palmitoylation of c- Met will provide a new specific target

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.

Present, Future, and Novel Bioclimates of the San Francisco, California Region

PubMed Central

Torregrosa, Alicia; Taylor, Maxwell D.; Flint, Lorraine E.; Flint, Alan L.

2013-01-01

Bioclimates are syntheses of climatic variables into biologically relevant categories that facilitate comparative studies of biotic responses to climate conditions. Isobioclimates, unique combinations of bioclimatic indices (continentality, ombrotype, and thermotype), were constructed for northern California coastal ranges based on the Rivas-Martinez worldwide bioclimatic classification system for the end of the 20th century climatology (1971–2000) and end of the 21st century climatology (2070–2099) using two models, Geophysical Fluid Dynamics Laboratory (GFDL) model and the Parallel Climate Model (PCM), under the medium-high A2 emission scenario. The digitally mapped results were used to 1) assess the relative redistribution of isobioclimates and their magnitude of change, 2) quantify the loss of isobioclimates into the future, 3) identify and locate novel isobioclimates projected to appear, and 4) explore compositional change in vegetation types among analog isobioclimate patches. This study used downscaled climate variables to map the isobioclimates at a fine spatial resolution −270 m grid cells. Common to both models of future climate was a large change in thermotype. Changes in ombrotype differed among the two models. The end of 20th century climatology has 83 isobioclimates covering the 63,000 km2 study area. In both future projections 51 of those isobioclimates disappear over 40,000 km2. The ordination of vegetation-bioclimate relationships shows very strong correlation of Rivas-Martinez indices with vegetation distribution and composition. Comparisons of vegetation composition among analog patches suggest that vegetation change will be a local rearrangement of species already in place rather than one requiring long distance dispersal. The digitally mapped results facilitate comparison with other Mediterranean regions. Major remaining challenges include predicting vegetation composition of novel isobioclimates and developing metrics to compare differences in climate space. PMID:23526985

Present, future, and novel bioclimates of the San Francisco, California region

USGS Publications Warehouse

Torregrosa, Alicia; Taylor, Maxwell D.; Flint, Lorraine E.; Flint, Alan L.

2013-01-01

Bioclimates are syntheses of climatic variables into biologically relevant categories that facilitate comparative studies of biotic responses to climate conditions. Isobioclimates, unique combinations of bioclimatic indices (continentality, ombrotype, and thermotype), were constructed for northern California coastal ranges based on the Rivas-Martinez worldwide bioclimatic classification system for the end of the 20th century climatology (1971–2000) and end of the 21st century climatology (2070–2099) using two models, Geophysical Fluid Dynamics Laboratory (GFDL) model and the Parallel Climate Model (PCM), under the medium-high A2 emission scenario. The digitally mapped results were used to 1) assess the relative redistribution of isobioclimates and their magnitude of change, 2) quantify the loss of isobioclimates into the future, 3) identify and locate novel isobioclimates projected to appear, and 4) explore compositional change in vegetation types among analog isobioclimate patches. This study used downscaled climate variables to map the isobioclimates at a fine spatial resolution −270 m grid cells. Common to both models of future climate was a large change in thermotype. Changes in ombrotype differed among the two models. The end of 20th century climatology has 83 isobioclimates covering the 63,000 km2 study area. In both future projections 51 of those isobioclimates disappear over 40,000 km2. The ordination of vegetation-bioclimate relationships shows very strong correlation of Rivas-Martinez indices with vegetation distribution and composition. Comparisons of vegetation composition among analog patches suggest that vegetation change will be a local rearrangement of species already in place rather than one requiring long distance dispersal. The digitally mapped results facilitate comparison with other Mediterranean regions. Major remaining challenges include predicting vegetation composition of novel isobioclimates and developing metrics to compare differences in climate space.

Future orientation, impulsivity, and problem behaviors: a longitudinal moderation model.

PubMed

Chen, Pan; Vazsonyi, Alexander T

2011-11-01

In the current study, based on a sample of 1,873 adolescents between 11.4 and 20.9 years of age from the first 3 waves of the National Longitudinal Study of Adolescent Health, we investigated the longitudinal effects of future orientation on levels of and developmental changes in problem behaviors, while controlling for the effects by impulsivity; we also tested the moderating effects by future orientation on the impulsivity-problem behaviors link over time. Additionally, we examined future orientation operationalized by items measuring education, marriage, and life domains. Findings based on growth curve analyses provided evidence of longitudinal effects by education and life future orientation on both levels of and developmental changes in problem behaviors; the effect of marriage future orientation was not significant for either test. In addition, only life future orientation moderated the effect by impulsivity on levels of problem behaviors over time. More specifically, impulsivity had a weaker effect on levels of problem behaviors over time for adolescents who reported higher levels of life future orientation.

Cognitive bias in back pain patients attending osteopathy: testing the enmeshment model in reference to future thinking.

PubMed

Read, Jessica; Pincus, Tamar

2004-12-01

Depressive symptoms are common in chronic pain. Previous research has found differences in information-processing biases in depressed pain patients and depressed people without pain. The schema enmeshment model of pain (SEMP) has been proposed to explain chronic pain patients' information-processing biases. Negative future thinking is common in depression but has not been explored in relation to chronic pain and information-processing models. The study aimed to test the SEMP with reference to future thinking. An information-processing paradigm compared endorsement and recall bias between depressed and non-depressed chronic low back pain patients and control participants. Twenty-five depressed and 35 non-depressed chronic low back pain patients and 25 control participants (student osteopaths) were recruited from an osteopathy practice. Participants were asked to endorse positive and negative ill-health, depression-related, and neutral (control) adjectives, encoded in reference to either current or future time-frame. Incidental recall of the adjectives was then tested. While the expected hypothesis of a recall bias by depressed pain patients towards ill-health stimuli in the current condition was confirmed, the recall bias was not present in the future condition. Additionally, patterns of endorsement and recall bias differed. Results extend understanding of future thinking in chronic pain within the context of the SEMP.

The sensitivity of the ESA DELTA model

NASA Astrophysics Data System (ADS)

Martin, C.; Walker, R.; Klinkrad, H.

Long-term debris environment models play a vital role in furthering our understanding of the future debris environment, and in aiding the determination of a strategy to preserve the Earth orbital environment for future use. By their very nature these models have to make certain assumptions to enable informative future projections to be made. Examples of these assumptions include the projection of future traffic, including launch and explosion rates, and the methodology used to simulate break-up events. To ensure a sound basis for future projections, and consequently for assessing the effectiveness of various mitigation measures, it is essential that the sensitivity of these models to variations in key assumptions is examined. The DELTA (Debris Environment Long Term Analysis) model, developed by QinetiQ for the European Space Agency, allows the future projection of the debris environment throughout Earth orbit. Extensive analyses with this model have been performed under the auspices of the ESA Space Debris Mitigation Handbook and following the recent upgrade of the model to DELTA 3.0. This paper draws on these analyses to present the sensitivity of the DELTA model to changes in key model parameters and assumptions. Specifically the paper will address the variation in future traffic rates, including the deployment of satellite constellations, and the variation in the break-up model and criteria used to simulate future explosion and collision events.

Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations

NASA Astrophysics Data System (ADS)

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

2018-01-01

As China becomes increasingly urbanised, flooding has become a regular occurrence in its major cities. Assessing the effects of future climate change on urban flood volumes is crucial to informing better management of such disasters given the severity of the devastating impacts of flooding (e.g. the 2016 flooding events across China). Although recent studies have investigated the impacts of future climate change on urban flooding, the effects of both climate change mitigation and adaptation have rarely been accounted for together in a consistent framework. In this study, we assess the benefits of mitigating climate change by reducing greenhouse gas (GHG) emissions and locally adapting to climate change by modifying drainage systems to reduce urban flooding under various climate change scenarios through a case study conducted in northern China. The urban drainage model - Storm Water Management Model - was used to simulate urban flood volumes using current and two adapted drainage systems (i.e. pipe enlargement and low-impact development, LID), driven by bias-corrected meteorological forcing from five general circulation models in the Coupled Model Intercomparison Project Phase 5 archive. Results indicate that urban flood volume is projected to increase by 52 % over 2020-2040 compared to the volume in 1971-2000 under the business-as-usual scenario (i.e. Representative Concentration Pathway (RCP) 8.5). The magnitudes of urban flood volumes are found to increase nonlinearly with changes in precipitation intensity. On average, the projected flood volume under RCP 2.6 is 13 % less than that under RCP 8.5, demonstrating the benefits of global-scale climate change mitigation efforts in reducing local urban flood volumes. Comparison of reduced flood volumes between climate change mitigation and local adaptation (by improving drainage systems) scenarios suggests that local adaptation is more effective than climate change mitigation in reducing future flood volumes. This has broad implications for the research community relative to drainage system design and modelling in a changing environment. This study highlights the importance of accounting for local adaptation when coping with future urban floods.

Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations

DOE PAGES

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

2018-01-15

As China becomes increasingly urbanised, flooding has become a regular occurrence in its major cities. Assessing the effects of future climate change on urban flood volumes is crucial to informing better management of such disasters given the severity of the devastating impacts of flooding (e.g. the 2016 flooding events across China). Although recent studies have investigated the impacts of future climate change on urban flooding, the effects of both climate change mitigation and adaptation have rarely been accounted for together in a consistent framework. In this study, we assess the benefits of mitigating climate change by reducing greenhouse gas (GHG)more » emissions and locally adapting to climate change by modifying drainage systems to reduce urban flooding under various climate change scenarios through a case study conducted in northern China. The urban drainage model – Storm Water Management Model – was used to simulate urban flood volumes using current and two adapted drainage systems (i.e. pipe enlargement and low-impact development, LID), driven by bias-corrected meteorological forcing from five general circulation models in the Coupled Model Intercomparison Project Phase 5 archive. Results indicate that urban flood volume is projected to increase by 52 % over 2020–2040 compared to the volume in 1971–2000 under the business-as-usual scenario (i.e. Representative Concentration Pathway (RCP) 8.5). The magnitudes of urban flood volumes are found to increase nonlinearly with changes in precipitation intensity. On average, the projected flood volume under RCP 2.6 is 13 % less than that under RCP 8.5, demonstrating the benefits of global-scale climate change mitigation efforts in reducing local urban flood volumes. Comparison of reduced flood volumes between climate change mitigation and local adaptation (by improving drainage systems) scenarios suggests that local adaptation is more effective than climate change mitigation in reducing future flood volumes. This has broad implications for the research community relative to drainage system design and modelling in a changing environment. Furthermore, this study highlights the importance of accounting for local adaptation when coping with future urban floods.« less

Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations

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

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

As China becomes increasingly urbanised, flooding has become a regular occurrence in its major cities. Assessing the effects of future climate change on urban flood volumes is crucial to informing better management of such disasters given the severity of the devastating impacts of flooding (e.g. the 2016 flooding events across China). Although recent studies have investigated the impacts of future climate change on urban flooding, the effects of both climate change mitigation and adaptation have rarely been accounted for together in a consistent framework. In this study, we assess the benefits of mitigating climate change by reducing greenhouse gas (GHG)more » emissions and locally adapting to climate change by modifying drainage systems to reduce urban flooding under various climate change scenarios through a case study conducted in northern China. The urban drainage model – Storm Water Management Model – was used to simulate urban flood volumes using current and two adapted drainage systems (i.e. pipe enlargement and low-impact development, LID), driven by bias-corrected meteorological forcing from five general circulation models in the Coupled Model Intercomparison Project Phase 5 archive. Results indicate that urban flood volume is projected to increase by 52 % over 2020–2040 compared to the volume in 1971–2000 under the business-as-usual scenario (i.e. Representative Concentration Pathway (RCP) 8.5). The magnitudes of urban flood volumes are found to increase nonlinearly with changes in precipitation intensity. On average, the projected flood volume under RCP 2.6 is 13 % less than that under RCP 8.5, demonstrating the benefits of global-scale climate change mitigation efforts in reducing local urban flood volumes. Comparison of reduced flood volumes between climate change mitigation and local adaptation (by improving drainage systems) scenarios suggests that local adaptation is more effective than climate change mitigation in reducing future flood volumes. This has broad implications for the research community relative to drainage system design and modelling in a changing environment. Furthermore, this study highlights the importance of accounting for local adaptation when coping with future urban floods.« less

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

PubMed

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

2018-01-01

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate. © 2017 John Wiley & Sons Ltd.

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

USGS Publications Warehouse

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

2018-01-01

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

FBI fingerprint identification automation study: AIDS 3 evaluation report. Volume 6: Environmental analysis

NASA Technical Reports Server (NTRS)

Mulhall, B. D. L.

1980-01-01

The results of the analysis of the external environment of the FBI Fingerprint Identification Division are presented. Possible trends in the future environment of the Division that may have an effect on the work load were projected to determine if future work load will lie within the capability range of the proposed new system, AIDS 3. Two working models of the environment were developed, the internal and external model, and from these scenarios the projection of possible future work load volume and mixture was developed. Possible drivers of work load change were identified and assessed for upper and lower bounds of effects. Data used for the study were derived from historical information, analysis of the current situation and from interviews with various agencies who are users of or stakeholders in the present system.

Characterizing the EPODE logic model: unravelling the past and informing the future.

PubMed

Van Koperen, T M; Jebb, S A; Summerbell, C D; Visscher, T L S; Romon, M; Borys, J M; Seidell, J C

2013-02-01

EPODE ('Ensemble Prévenons l'Obésité De Enfants' or 'Together let's Prevent Childhood Obesity') is a large-scale, centrally coordinated, capacity-building approach for communities to implement effective and sustainable strategies to prevent childhood obesity. Since 2004, EPODE has been implemented in over 500 communities in six countries. Although based on emergent practice and scientific knowledge, EPODE, as many community programs, lacks a logic model depicting key elements of the approach. The objective of this study is to gain insight in the dynamics and key elements of EPODE and to represent these in a schematic logic model. EPODE's process manuals and documents were collected and interviews were held with professionals involved in the planning and delivery of EPODE. Retrieved data were coded, themed and placed in a four-level logic model. With input from international experts, this model was scaled down to a concise logic model covering four critical components: political commitment, public and private partnerships, social marketing and evaluation. The EPODE logic model presented here can be used as a reference for future and follow-up research; to support future implementation of EPODE in communities; as a tool in the engagement of stakeholders; and to guide the construction of a locally tailored evaluation plan. © 2012 The Authors. obesity reviews © 2012 International Association for the Study of Obesity.

Future efficiency of run of the river hydropower schemes based on climate change scenarios: case study in UK catchments

NASA Astrophysics Data System (ADS)

Pasten Zapata, Ernesto; Moggridge, Helen; Jones, Julie; Widmann, Martin

2017-04-01

Run-of-the-River (ROR) hydropower schemes are expected to be importantly affected by climate change as they rely in the availability of river flow to generate energy. As temperature and precipitation are expected to vary in the future, the hydrological cycle will also undergo changes. Therefore, climate models based on complex physical atmospheric interactions have been developed to simulate future climate scenarios considering the atmosphere's greenhouse gas concentrations. These scenarios are classified according to the Representative Concentration Pathways (RCP) that are generated according to the concentration of greenhouse gases. This study evaluates possible scenarios for selected ROR hydropower schemes within the UK, considering three different RCPs: 2.6, 4.5 and 8.5 W/m2 for 2100 relative to pre-industrial values. The study sites cover different climate, land cover, topographic and hydropower scheme characteristics representative of the UK's heterogeneity. Precipitation and temperature outputs from state-of-the-art Regional Climate Models (RCMs) from the Euro-CORDEX project are used as input for a HEC-HMS hydrological model to simulate the future river flow available. Both uncorrected and bias-corrected RCM simulations are analyzed. The results of this project provide an insight of the possible effects of climate change towards the generation of power from the ROR hydropower schemes according to the different RCP scenarios and contrasts the results obtained from uncorrected and bias-corrected RCMs. This analysis can aid on the adaptation to climate change as well as the planning of future ROR schemes in the region.

Incorporating Cold-Air Pooling into Downscaled Climate Models Increases Potential Refugia for Snow-Dependent Species within the Sierra Nevada Ecoregion, CA

PubMed Central

Curtis, Jennifer A.; Flint, Lorraine E.; Flint, Alan L.; Lundquist, Jessica D.; Hudgens, Brian; Boydston, Erin E.; Young, Julie K.

2014-01-01

We present a unique water-balance approach for modeling snowpack under historic, current and future climates throughout the Sierra Nevada Ecoregion. Our methodology uses a finer scale (270 m) than previous regional studies and incorporates cold-air pooling, an atmospheric process that sustains cooler temperatures in topographic depressions thereby mitigating snowmelt. Our results are intended to support management and conservation of snow-dependent species, which requires characterization of suitable habitat under current and future climates. We use the wolverine (Gulo gulo) as an example species and investigate potential habitat based on the depth and extent of spring snowpack within four National Park units with proposed wolverine reintroduction programs. Our estimates of change in spring snowpack conditions under current and future climates are consistent with recent studies that generally predict declining snowpack. However, model development at a finer scale and incorporation of cold-air pooling increased the persistence of April 1st snowpack. More specifically, incorporation of cold-air pooling into future climate projections increased April 1st snowpack by 6.5% when spatially averaged over the study region and the trajectory of declining April 1st snowpack reverses at mid-elevations where snow pack losses are mitigated by topographic shading and cold-air pooling. Under future climates with sustained or increased precipitation, our results indicate a high likelihood for the persistence of late spring snowpack at elevations above approximately 2,800 m and identify potential climate refugia sites for snow-dependent species at mid-elevations, where significant topographic shading and cold-air pooling potential exist. PMID:25188379

Incorporating cold-air pooling into downscaled climate models increases potential refugia for snow-dependent species within the Sierra Nevada Ecoregion, CA

USGS Publications Warehouse

Curtis, Jennifer A.; Flint, Lorraine E.; Flint, Alan L.; Lundquist, Jessica D.; Hudgens, Brian; Boydston, Erin E.; Young, Julie K.

2014-01-01

We present a unique water-balance approach for modeling snowpack under historic, current and future climates throughout the Sierra Nevada Ecoregion. Our methodology uses a finer scale (270 m) than previous regional studies and incorporates cold-air pooling, an atmospheric process that sustains cooler temperatures in topographic depressions thereby mitigating snowmelt. Our results are intended to support management and conservation of snow-dependent species, which requires characterization of suitable habitat under current and future climates. We use the wolverine (Gulo gulo) as an example species and investigate potential habitat based on the depth and extent of spring snowpack within four National Park units with proposed wolverine reintroduction programs. Our estimates of change in spring snowpack conditions under current and future climates are consistent with recent studies that generally predict declining snowpack. However, model development at a finer scale and incorporation of cold-air pooling increased the persistence of April 1st snowpack. More specifically, incorporation of cold-air pooling into future climate projections increased April 1st snowpack by 6.5% when spatially averaged over the study region and the trajectory of declining April 1st snowpack reverses at mid-elevations where snow pack losses are mitigated by topographic shading and cold-air pooling. Under future climates with sustained or increased precipitation, our results indicate a high likelihood for the persistence of late spring snowpack at elevations above approximately 2,800 m and identify potential climate refugia sites for snow-dependent species at mid-elevations, where significant topographic shading and cold-air pooling potential exist.

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...

Pedagogy and Process: A Case Study of Writing in a Hybrid Learning Model

ERIC Educational Resources Information Center

Keiner, Jason F.

2017-01-01

This qualitative case study explored the perceived experiences and outcomes of writing in a hybrid model of instruction in a large suburban high school. In particular, the impact of a hybrid model on the writing process and on future writing performance were examined. In addition, teacher expectation and teacher attitude and their impact upon…

Three essays on agricultural price volatility and the linkages between agricultural and energy markets

NASA Astrophysics Data System (ADS)

Wu, Feng

This dissertation contains three essays. In the first essay I use a volatility spillover model to find evidence of significant spillovers from crude oil prices to corn cash and futures prices, and that these spillover effects are time-varying. Results reveal that corn markets have become much more connected to crude oil markets after the introduction of the Energy Policy Act of 2005. Furthermore, crude oil prices transmit positive volatility spillovers into corn prices and movements in corn prices become more energy-driven as the ethanol gasoline consumption ratio increases. Based on this strong volatility link between crude oil and corn prices, a new cross hedging strategy for managing corn price risk using oil futures is examined and its performance studied. Results show that this cross hedging strategy provides only slightly better hedging performance compared to traditional hedging in corn futures markets alone. The implication is that hedging corn price risk in corn futures markets alone can still provide relatively satisfactory performance in the biofuel era. The second essay studies the spillover effect of biofuel policy on participation in the Conservation Reserve Program. Landowners' participation decisions are modeled using a real options framework. A novel aspect of the model is that it captures the structural change in agriculture caused by rising biofuel production. The resulting model is used to simulate the spillover effect under various conditions. In particular, I simulate how increased growth in agricultural returns, persistence of the biofuel production boom, and the volatility surrounding agricultural returns, affect conservation program participation decisions. Policy implications of these results are also discussed. The third essay proposes a methodology to construct a risk-adjusted implied volatility measure that removes the forecasting bias of the model-free implied volatility measure. The risk adjustment is based on a closed-form relationship between the expectation of future volatility and the model-free implied volatility assuming a jump-diffusion model. I use a GMM estimation framework to identify the key model parameters needed to apply the model. An empirical application to corn futures implied volatility is used to illustrate the methodology and demonstrate differences between my approach and the model-free implied volatility using observed corn option prices. I compare the risk-adjusted forecast with the unadjusted forecast as well as other alternatives; and results suggest that the risk-adjusted volatility is unbiased, informationally more efficient, and has superior predictive power over the alternatives considered.

Future Climate Change in the Baltic Sea Area

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Renewable Electricity Futures. Operational Analysis of the Western Interconnection at Very High Renewable Penetrations

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

Brinkman, Gregory

2015-09-01

The Renewable Electricity Futures Study (RE Futures)--an analysis of the costs and grid impacts of integrating large amounts of renewable electricity generation into the U.S. power system--examined renewable energy resources, technical issues regarding the integration of these resources into the grid, and the costs associated with high renewable penetration scenarios. These scenarios included up to 90% of annual generation from renewable sources, although most of the analysis was focused on 80% penetration scenarios. Hourly production cost modeling was performed to understand the operational impacts of high penetrations. One of the conclusions of RE Futures was that further work was necessarymore » to understand whether the operation of the system was possible at sub-hourly time scales and during transient events. This study aimed to address part of this by modeling the operation of the power system at sub-hourly time scales using newer methodologies and updated data sets for transmission and generation infrastructure. The goal of this work was to perform a detailed, sub-hourly analysis of very high penetration scenarios for a single interconnection (the Western Interconnection). It focused on operational impacts, and it helps verify that the operational results from the capacity expansion models are useful. The primary conclusion of this study is that sub-hourly operation of the grid is possible with renewable generation levels between 80% and 90%.« less

A test of the vulnerability model: temperament and temperament change as predictors of future mental disorders - the TRAILS study.

PubMed

Laceulle, Odilia M; Ormel, Johan; Vollebergh, Wilma A M; van Aken, Marcel A G; Nederhof, Esther

2014-03-01

This study aimed to test the vulnerability model of the relationship between temperament and mental disorders using a large sample of adolescents from the TRacking Adolescents Individual Lives' Survey (TRAILS). The vulnerability model argues that particular temperaments can place individuals at risk for the development of mental health problems. Importantly, the model may imply that not only baseline temperament predicts mental health problems prospectively, but additionally, that changes in temperament predict corresponding changes in risk for mental health problems. Data were used from 1195 TRAILS participants. Adolescent temperament was assessed both at age 11 and at age 16. Onset of mental disorders between age 16 and 19 was assessed at age 19, by means of the World Health Organization Composite International Diagnostic Interview (WHO CIDI). Results showed that temperament at age 11 predicted future mental disorders, thereby providing support for the vulnerability model. Moreover, temperament change predicted future mental disorders above and beyond the effect of basal temperament. For example, an increase in frustration increased the risk of mental disorders proportionally. This study confirms, and extends, the vulnerability model. Consequences of both temperament and temperament change were general (e.g., changes in frustration predicted both internalizing and externalizing disorders) as well as dimension specific (e.g., changes in fear predicted internalizing but not externalizing disorders). These findings confirm previous studies, which showed that mental disorders have both unique and shared underlying temperamental risk factors. © 2013 The Authors. Journal of Child Psychology and Psychiatry © 2013 Association for Child and Adolescent Mental Health.

Characteristic density contrasts in the evolution of superclusters. The case of A2142 supercluster

NASA Astrophysics Data System (ADS)

Gramann, Mirt; Einasto, Maret; Heinämäki, Pekka; Teerikorpi, Pekka; Saar, Enn; Nurmi, Pasi; Einasto, Jaan

2015-09-01

Context. The formation and evolution of the cosmic web in which galaxy superclusters are the largest relatively isolated objects is governed by a gravitational attraction of dark matter and antigravity of dark energy (cosmological constant). Aims: We study the characteristic density contrasts in the spherical collapse model for several epochs in the supercluster evolution and their dynamical state. Methods: We analysed the density contrasts for the turnaround, future collapse, and zero gravity in different ΛCDM models and applied them to study the dynamical state of the supercluster A2142 with an almost spherical main body, making it a suitable test object to apply a model that assumes sphericity. Results: We present characteristic density contrasts in the spherical collapse model for different cosmological parameters. The analysis of the supercluster A2142 shows that its high-density core has already started to collapse. The zero-gravity line outlines the outer region of the main body of the supercluster. In the course of future evolution, the supercluster may split into several collapsing systems. Conclusions: The various density contrasts presented in our study and applied to the supercluster A2142 offer a promising way to characterise the dynamical state and expected future evolution of galaxy superclusters.

Uncertainties in Past and Future Global Water Availability

NASA Astrophysics Data System (ADS)

Sheffield, J.; Kam, J.

2014-12-01

Understanding how water availability changes on inter-annual to decadal time scales and how it may change in the future under climate change are a key part of understanding future stresses on water and food security. Historic evaluations of water availability on regional to global scales are generally based on large-scale model simulations with their associated uncertainties, in particular for long-term changes. Uncertainties are due to model errors and missing processes, parameter uncertainty, and errors in meteorological forcing data. Recent multi-model inter-comparisons and impact studies have highlighted large differences for past reconstructions, due to different simplifying assumptions in the models or the inclusion of physical processes such as CO2 fertilization. Modeling of direct anthropogenic factors such as water and land management also carry large uncertainties in their physical representation and from lack of socio-economic data. Furthermore, there is little understanding of the impact of uncertainties in the meteorological forcings that underpin these historic simulations. Similarly, future changes in water availability are highly uncertain due to climate model diversity, natural variability and scenario uncertainty, each of which dominates at different time scales. In particular, natural climate variability is expected to dominate any externally forced signal over the next several decades. We present results from multi-land surface model simulations of the historic global availability of water in the context of natural variability (droughts) and long-term changes (drying). The simulations take into account the impact of uncertainties in the meteorological forcings and the incorporation of water management in the form of reservoirs and irrigation. The results indicate that model uncertainty is important for short-term drought events, and forcing uncertainty is particularly important for long-term changes, especially uncertainty in precipitation due to reduced gauge density in recent years. We also discuss uncertainties in future projections from these models as driven by bias-corrected and downscaled CMIP5 climate projections, in the context of the balance between climate model robustness and climate model diversity.

Intraday price dynamics in spot and derivatives markets

NASA Astrophysics Data System (ADS)

Kim, Jun Sik; Ryu, Doojin

2014-01-01

This study examines intraday relationships among the spot index, index futures, and the implied volatility index based on the VAR(1)-asymmetric BEKK-MGARCH model. Analysis of a high-frequency dataset from the Korean financial market confirms that there is a strong intraday market linkage between the spot index, KOSPI200 futures, and VKOSPI and that asymmetric volatility behaviour is clearly present in the Korean market. The empirical results indicate that the futures return shock affects the spot market more severely than the spot return shock affects the futures market, though there is a bi-directional causal relationship between the spot and futures markets. Our results, based on a high-quality intraday dataset, satisfy both the positive risk-return relationship and asymmetric volatility effect, which are not reconciled in the frameworks of previous studies.

Streamflow Bias Correction for Climate Change Impact Studies: Harmless Correction or Wrecking Ball?

NASA Astrophysics Data System (ADS)

Nijssen, B.; Chegwidden, O.

2017-12-01

Projections of the hydrologic impacts of climate change rely on a modeling chain that includes estimates of future greenhouse gas emissions, global climate models, and hydrologic models. The resulting streamflow time series are used in turn as input to impact studies. While these flows can sometimes be used directly in these impact studies, many applications require additional post-processing to remove model errors. Water resources models and regulation studies are a prime example of this type of application. These models rely on specific flows and reservoir levels to trigger reservoir releases and diversions and do not function well if the unregulated streamflow inputs are significantly biased in time and/or amount. This post-processing step is typically referred to as bias-correction, even though this step corrects not just the mean but the entire distribution of flows. Various quantile-mapping approaches have been developed that adjust the modeled flows to match a reference distribution for some historic period. Simulations of future flows are then post-processed using this same mapping to remove hydrologic model errors. These streamflow bias-correction methods have received far less scrutiny than the downscaling and bias-correction methods that are used for climate model output, mostly because they are less widely used. However, some of these methods introduce large artifacts in the resulting flow series, in some cases severely distorting the climate change signal that is present in future flows. In this presentation, we discuss our experience with streamflow bias-correction methods as part of a climate change impact study in the Columbia River basin in the Pacific Northwest region of the United States. To support this discussion, we present a novel way to assess whether a streamflow bias-correction method is merely a harmless correction or is more akin to taking a wrecking ball to the climate change signal.

Simulating the Interactions Among Land Use, Transportation, and Economy to Inform Light Rail Transit Decisions

EPA Science Inventory

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...

Simulating the Interactions Among Land Use, Transportation, and Economy to Inform Light Rail Transit Decisions (proceedings)

EPA Science Inventory

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...

Composition and carbon dynamics of forests in northeastern North America in a future, warmer world

Treesearch

Jacqueline E. Mohan; Roger M. Cox; Louis R. Iverson

2009-01-01

Increasing temperatures, precipitation extremes, and other anthropogenic influences (pollutant deposition, increasing carbon dioxide) will influence future forest composition and productivity in the northeastern United States and eastern Canada. This synthesis of empirical and modeling studies includes tree DNA evidence suggesting tree...

AnnAGNPS Model Application for Nitrogen Loading Assessment for the Future Midwest Landscape Study

EPA Science Inventory

The Future Midwest Landscape (FML) project is part of the US Environmental Protection Agency (EPA)’s new Ecosystem Services Research Program, undertaken to examine the variety of ways in which landscapes that include crop lands, conservation areas, wetlands, lakes, and streams af...

Future-Oriented Coping and Job Hunting among College Students

ERIC Educational Resources Information Center

Hu, Yueqin; Gan, Yiqun

2011-01-01

Using a sample of Chinese college students (n = 216), the present study showed that future-oriented coping negatively correlated with perceived pressure and positively correlated with successful job hunting. The relationship between proactive coping and preventive coping was also explored. Structural equation modeling suggested that a sequence…

The Career Futures Inventory-Revised: Measuring Dimensions of Career Adaptability

ERIC Educational Resources Information Center

Rottinghaus, Patrick J.; Buelow, Kristine L.; Matyja, Anna; Schneider, Madalyn R.

2012-01-01

This study reports the development and initial validation of the "Career Futures Inventory-Revised" (CFI-R) in two large samples of university students. The 28-item CFI-R assesses aspects of career adaptability, including positive career planning attitudes, general outcome expectations, and components of Parsons' tripartite model and…

Understanding the Association Between School Climate and Future Orientation.

PubMed

Lindstrom Johnson, Sarah; Pas, Elise; Bradshaw, Catherine P

2016-08-01

Promoting students' future orientation is inherently a goal of the educational system. Recently, it has received more explicit attention given the increased focus on career readiness. This study aimed to examine the association between school climate and adolescents' report of future orientation using data from youth (N = 27,698; 49.4 % female) across 58 high schools. Three-level hierarchical linear models indicated that perceptions of available emotional and service supports, rules and consequences, and parent engagement were positively related to adolescents' future orientation. Additionally, the school-level average future orientation was significantly related to individuals' future orientation, indicating a potential influence of contextual effects on this construct. Taken together, these findings suggest that interventions targeting school climate may hold promise for promoting future orientation.

Assessing economic impacts to coastal recreation and tourism from oil and gas development in the Oregon and Washington Outer Continental Shelf. Inventory and evaluation of Washington and Oregon coastal recreation resources

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

Ellis, G.M.; Johnson, N.S.; Chapman, D.

The purpose of the three-part study was to assist Materials Management Service (MMS) planners in evaluation of the anticipated social impact of proposed oil and gas development on the environment. The purpose of the report is primarily to analyze the econometric models of the Dornbusch study. The authors examine, in detail, key aspects of the gravity, consumer surplus, and economic effects (input-output) models. The purpose is two-fold. First, the authors evaluate the performance of the model in satisfying the objective for which it was developed: analyzing economic impacts of OCS oil and gas development in California. Second, the authors evaluatemore » the applicability of the modeling approach employed in the Dornbusch study for analyzing potential OCS development impacts in Washington and Oregon. At the end of the report, the authors offer suggestions for any future study of economic impacts of OCS development in Washington and Oregon. The recommendations concern future data gathering procedures and alternative modeling approaches for measuring economic impacts.« less

Forecasting distributions of an aquatic invasive species (Nitellopsis obtusa) under future climate scenarios

PubMed Central

Varela, Sara; Larkin, Daniel J.; Phelps, Nicholas B. D.

2017-01-01

Starry stonewort (Nitellopsis obtusa) is an alga that has emerged as an aquatic invasive species of concern in the United States. Where established, starry stonewort can interfere with recreational uses of water bodies and potentially have ecological impacts. Incipient invasion of starry stonewort in Minnesota provides an opportunity to predict future expansion in order to target early detection and strategic management. We used ecological niche models to identify suitable areas for starry stonewort in Minnesota based on global occurrence records and present-day and future climate conditions. We assessed sensitivity of forecasts to different parameters, using four emission scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6, and RCP 8.5) from five future climate models (i.e., CCSM, GISS, IPSL, MIROC, and MRI). From our niche model analyses, we found that (i) occurrences from the entire range, instead of occurrences restricted to the invaded range, provide more informed models; (ii) default settings in Maxent did not provide the best model; (iii) the model calibration area and its background samples impact model performance; (iv) model projections to future climate conditions should be restricted to analogous environments; and (v) forecasts in future climate conditions should include different future climate models and model calibration areas to better capture uncertainty in forecasts. Under present climate, the most suitable areas for starry stonewort are predicted to be found in central and southeastern Minnesota. In the future, suitable areas for starry stonewort are predicted to shift in geographic range under some future climate models and to shrink under others, with most permutations indicating a net decrease of the species’ suitable range. Our suitability maps can serve to design short-term plans for surveillance and education, while future climate models suggest a plausible reduction of starry stonewort spread in the long-term if the trends in climate warming remain. PMID:28704433

Forecasting distributions of an aquatic invasive species (Nitellopsis obtusa) under future climate scenarios.

PubMed

Romero-Alvarez, Daniel; Escobar, Luis E; Varela, Sara; Larkin, Daniel J; Phelps, Nicholas B D

2017-01-01

Starry stonewort (Nitellopsis obtusa) is an alga that has emerged as an aquatic invasive species of concern in the United States. Where established, starry stonewort can interfere with recreational uses of water bodies and potentially have ecological impacts. Incipient invasion of starry stonewort in Minnesota provides an opportunity to predict future expansion in order to target early detection and strategic management. We used ecological niche models to identify suitable areas for starry stonewort in Minnesota based on global occurrence records and present-day and future climate conditions. We assessed sensitivity of forecasts to different parameters, using four emission scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6, and RCP 8.5) from five future climate models (i.e., CCSM, GISS, IPSL, MIROC, and MRI). From our niche model analyses, we found that (i) occurrences from the entire range, instead of occurrences restricted to the invaded range, provide more informed models; (ii) default settings in Maxent did not provide the best model; (iii) the model calibration area and its background samples impact model performance; (iv) model projections to future climate conditions should be restricted to analogous environments; and (v) forecasts in future climate conditions should include different future climate models and model calibration areas to better capture uncertainty in forecasts. Under present climate, the most suitable areas for starry stonewort are predicted to be found in central and southeastern Minnesota. In the future, suitable areas for starry stonewort are predicted to shift in geographic range under some future climate models and to shrink under others, with most permutations indicating a net decrease of the species' suitable range. Our suitability maps can serve to design short-term plans for surveillance and education, while future climate models suggest a plausible reduction of starry stonewort spread in the long-term if the trends in climate warming remain.

Progress and Prospects for Genetic Modification of Nonhuman Primate Models in Biomedical Research

PubMed Central

Chan, Anthony W. S.

2013-01-01

The growing interest of modeling human diseases using genetically modified (transgenic) nonhuman primates (NHPs) is a direct result of NHPs (rhesus macaque, etc.) close relation to humans. NHPs share similar developmental paths with humans in their anatomy, physiology, genetics, and neural functions; and in their cognition, emotion, and social behavior. The NHP model within biomedical research has played an important role in the development of vaccines, assisted reproductive technologies, and new therapies for many diseases. Biomedical research has not been the primary role of NHPs. They have mainly been used for safety evaluation and pharmacokinetics studies, rather than determining therapeutic efficacy. The development of the first transgenic rhesus macaque (2001) revolutionized the role of NHP models in biomedicine. Development of the transgenic NHP model of Huntington's disease (2008), with distinctive clinical features, further suggested the uniqueness of the model system; and the potential role of the NHP model for human genetic disorders. Modeling human genetic diseases using NHPs will continue to thrive because of the latest advances in molecular, genetic, and embryo technologies. NHPs rising role in biomedical research, specifically pre-clinical studies, is foreseeable. The path toward the development of transgenic NHPs and the prospect of transgenic NHPs in their new role in future biomedicine needs to be reviewed. This article will focus on the advancement of transgenic NHPs in the past decade, including transgenic technologies and disease modeling. It will outline new technologies that may have significant impact in future NHP modeling and will conclude with a discussion of the future prospects of the transgenic NHP model. PMID:24174443

Flow regime alterations under changing climate in two river basins: Implications for freshwater ecosystems

USGS Publications Warehouse

Gibson, C.A.; Meyer, J.L.; Poff, N.L.; Hay, L.E.; Georgakakos, A.

2005-01-01

We examined impacts of future climate scenarios on flow regimes and how predicted changes might affect river ecosystems. We examined two case studies: Cle Elum River, Washington, and Chattahoochee-Apalachicola River Basin, Georgia and Florida. These rivers had available downscaled global circulation model (GCM) data and allowed us to analyse the effects of future climate scenarios on rivers with (1) different hydrographs, (2) high future water demands, and (3) a river-floodplain system. We compared observed flow regimes to those predicted under future climate scenarios to describe the extent and type of changes predicted to occur. Daily stream flow under future climate scenarios was created by either statistically downscaling GCMs (Cle Elum) or creating a regression model between climatological parameters predicted from GCMs and stream flow (Chattahoochee-Apalachicola). Flow regimes were examined for changes from current conditions with respect to ecologically relevant features including the magnitude and timing of minimum and maximum flows. The Cle Elum's hydrograph under future climate scenarios showed a dramatic shift in the timing of peak flows and lower low flow of a longer duration. These changes could mean higher summer water temperatures, lower summer dissolved oxygen, and reduced survival of larval fishes. The Chattahoochee-Apalachicola basin is heavily impacted by dams and water withdrawals for human consumption; therefore, we made comparisons between pre-large dam conditions, current conditions, current conditions with future demand, and future climate scenarios with future demand to separate climate change effects and other anthropogenic impacts. Dam construction, future climate, and future demand decreased the flow variability of the river. In addition, minimum flows were lower under future climate scenarios. These changes could decrease the connectivity of the channel and the floodplain, decrease habitat availability, and potentially lower the ability of the river to assimilate wastewater treatment plant effluent. Our study illustrates the types of changes that river ecosystems might experience under future climates. Copyright ?? 2005 John Wiley & Sons, Ltd.

Fluid reasoning predicts future mathematics among children and adolescents

PubMed Central

Green, Chloe T.; Bunge, Silvia A.; Chiongbian, Victoria Briones; Barrow, Maia; Ferrer, Emilio

2017-01-01

The aim of this longitudinal study was to determine whether fluid reasoning (FR) plays a significant role in the acquisition of mathematics skills, above and beyond the effects of other cognitive and numerical abilities. Using a longitudinal cohort sequential design, we examined how FR measured at three assessment occasions, spaced approximately 1.5 years apart, predicted math outcomes for a group of 69 participants between ages 6 and 21 across all three assessment occasions. We used structural equation modeling (SEM) to examine the direct and indirect relations between children's prior cognitive abilities and their future math achievement. A model including age, FR, vocabulary, and spatial skills accounted for 90% of the variance in future math achievement. In this model, FR was the only significant predictor of future math achievement; neither age, vocabulary, nor spatial skills were significant predictors. Thus, FR was the only predictor of future math achievement across a wide age range that spanned primary and secondary school. These findings build on Cattell's conceptualization of FR (Cattell, 1987) as a scaffold for learning, showing that this domain-general ability supports the acquisition of rudimentary math skills as well as the ability to solve more complex mathematical problems. PMID:28152390

Urbanization Impacts on Flooding in the Kansas River Basin and Evaluation of Wetlands as a Mitigation Measure

EPA Science Inventory

This study evaluates the impacts of future land use changes on flooding in the Kansas River Basin. It also studies the impacts of wetlands on flood reduction. The study presents Hydrologic Engineering Centers-Hydrologic Modeling System (HEC-HMS) based runoff modeling and River A...

Ultrasonic Phased Array Simulations of Welded Components at NASA

NASA Technical Reports Server (NTRS)

Roth, D. J.; Tokars, R. P.; Martin, R. E.; Rauser, R. W.; Aldrin, J. C.

2009-01-01

Comprehensive and accurate inspections of welded components have become of increasing importance as NASA develops new hardware such as Ares rocket segments for future exploration missions. Simulation and modeling will play an increasing role in the future for nondestructive evaluation in order to better understand the physics of the inspection process, to prove or disprove the feasibility for an inspection method or inspection scenario, for inspection optimization, for better understanding of experimental results, and for assessment of probability of detection. This study presents simulation and experimental results for an ultrasonic phased array inspection of a critical welded structure important for NASA future exploration vehicles. Keywords: nondestructive evaluation, computational simulation, ultrasonics, weld, modeling, phased array

Learning from Higgs physics at future Higgs factories

DOE PAGES

Gu, Jiayin; Li, Honglei; Liu, Zhen; ...

2017-12-29

Future Higgs factories can reach impressive precision on Higgs property measurements. In this paper, instead of conventional focus of Higgs precision in certain interaction bases, we explored its sensitivity to new physics models at the electron-positron colliders. In particular, we studied two categories of new physics models, Standard Model (SM) with a real scalar singlet extension, and Two Higgs Double Model (2HDM) as examples of weakly-interacting models, Minimal Composite Higgs Model (MCHM) and three typical patterns of the more general operator counting for strong interacting models as examples of strong dynamics. We performed a global fit to various Higgs searchmore » channels to obtain the 95% C.L. constraints on the model parameter space. In the SM with a singlet extension, we obtained the limits on the singlet-doublet mixing angle sin(theta), as well as the more general Wilson coefficients of the induced higher dimensional operators. In the 2HDM, we analyzed tree level effects in tan(beta) vs. cos(beta-alpha) plane, as well as the one-loop contributions from the heavy Higgs bosons in the alignment limit to obtain the constraints on heavy Higgs masses for different types of 2HDM. In strong dynamics models, we obtained lower limits on the strong dynamics scale. In addition, once deviations of Higgs couplings are observed, they can be used to distinguish different models. Here, we also compared the sensitivity of various future Higgs factories, namely Circular Electron Positron Collider (CEPC), Future Circular Collider (FCC)-ee and International Linear Collider (ILC).« less

Learning from Higgs physics at future Higgs factories

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

Gu, Jiayin; Li, Honglei; Liu, Zhen

Future Higgs factories can reach impressive precision on Higgs property measurements. In this paper, instead of conventional focus of Higgs precision in certain interaction bases, we explored its sensitivity to new physics models at the electron-positron colliders. In particular, we studied two categories of new physics models, Standard Model (SM) with a real scalar singlet extension, and Two Higgs Double Model (2HDM) as examples of weakly-interacting models, Minimal Composite Higgs Model (MCHM) and three typical patterns of the more general operator counting for strong interacting models as examples of strong dynamics. We performed a global fit to various Higgs searchmore » channels to obtain the 95% C.L. constraints on the model parameter space. In the SM with a singlet extension, we obtained the limits on the singlet-doublet mixing angle sin(theta), as well as the more general Wilson coefficients of the induced higher dimensional operators. In the 2HDM, we analyzed tree level effects in tan(beta) vs. cos(beta-alpha) plane, as well as the one-loop contributions from the heavy Higgs bosons in the alignment limit to obtain the constraints on heavy Higgs masses for different types of 2HDM. In strong dynamics models, we obtained lower limits on the strong dynamics scale. In addition, once deviations of Higgs couplings are observed, they can be used to distinguish different models. Here, we also compared the sensitivity of various future Higgs factories, namely Circular Electron Positron Collider (CEPC), Future Circular Collider (FCC)-ee and International Linear Collider (ILC).« less

Changes in Urban Climate due to Future Land-Use Changes based on Population Changes in the Nagoya Region

NASA Astrophysics Data System (ADS)

Adachi, S. A.; Hara, M.; Takahashi, H. G.; Ma, X.; Yoshikane, T.; Kimura, F.

2013-12-01

Severe hot weather in summer season becomes a big social problem in metropolitan areas, including the Nagoya region in Japan. Surface air temperature warming is projected in the future. Therefore, the reduction of surface air temperature is an urgent issue in the urban area. Although there are several studies dealing with the effects of global climate change and urbanization to the local climate in the future, these studies tend to ignore the future population changes. This study estimates future land-use scenarios associated with the multi-projections of future population and investigates the impacts of these scenarios on the surface temperature change. The Weather Research and Forecast model ver. 3.3.1 (hereafter, WRF) was used in this study. The horizontal resolutions were 20km, 4km, and 2km, for outer, middle, and inner domains, respectively. The results from the inner domain, covering the Nagoya region, were used for the analysis. The Noah land surface model and the single-layer urban canopy model were applied to calculate the land surface processes and urban surface processes, respectively. The initial and boundary conditions were given from the NCEP/NCAR reanalysis data in August 2010. The urban area ratio used in the WRF model was calculated from the future land-use data provided by the S8 project. The land-use data was created as follows. (1) Three scenarios of population, namely, with high-fertility assumption and low-mortality assumption (POP-high), with medium-fertility assumption and medium-mortality assumption (POP-med), and with low-fertility assumption and high-mortality assumption (POP-low), are estimated using the method proposed by Ariga and Matsuhashi (2012). These scenarios are based on the future projections provided by the National Institute of Population and Social Security Research. (2) The future changes in urban area ratio were assumed to be proportional to the population change (Hanasaki et al., 2012). The averaged urban area ratio in the Nagoya region was 0.37 in 2010. The area ratios were projected to reach a peak in 2010 to 2020, and then to decrease in the future in all of scenarios. The urban heat island intensity in the Nagoya region is about 1.5°C in 2010. In contrast, the differences of surface temperature is -0.17°C, -0.21°C, and -0.30°C in POP-high, POP-med, and POP-low, from the current situation in 2010. These impacts correspond to the 10% to 20% of current urban heat island intensity. However, the changes in the efficiency of energy consumption were not considered. Considering that the future surface temperature change is projected to be about 1.2°C to 4°C in 2070, it is required to quantitatively evaluate future urban scenarios including the mitigation strategies for urban heat island such as the improvement of energy consumption, greening, and so on. Acknowledgments. This study was supported by the Research Program on Climate Change Adaptation (RECCA) Fund by Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan and the Global Environment Research Fund (S-8) of the Ministry of the Environment of Japan.

Uncertainties in Projecting Future Changes in Atmospheric Rivers and Their Impacts on Heavy Precipitation over Europe

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

Gao, Yang; Lu, Jian; Leung, L. Ruby

This study investigates the North Atlantic atmospheric rivers (ARs) making landfall over western Europe in the present and future climate from the multi-model ensemble of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Overall, CMIP5 captures the seasonal and spatial variations of historical landfalling AR days, with the large inter-model variability strongly correlated with the inter-model spread of historical jet position. Under RCP 8.5, AR frequency is projected to increase a few times by the end of this century. While thermodynamics plays a dominate role in the future increase of ARs, wind changes associated with the midlatitude jet shifts alsomore » significantly contribute to AR changes, resulting in dipole change patterns in all seasons. In the North Atlantic, the model projected jet shifts are strongly correlated with the simulated historical jet position. As models exhibit predominantly equatorward biases in the historical jet position, the large poleward jet shifts reduce AR days south of the historical mean jet position through the dynamical connections between the jet positions and AR days. Using the observed historical jet position as an emergent constraint, dynamical effects further increase AR days in the future above the large increases due to thermodynamical effects. In the future, both total and extreme precipitation induced by AR contribute more to the seasonal mean and extreme precipitation compared to present primarily because of the increase in AR frequency. While AR precipitation intensity generally increases more relative to the increase in integrated vapor transport, AR extreme precipitation intensity increases much less.« less

Urban airshed modeling of air quality impacts of alternative transportation fuel use in Los Angeles and Atlanta

DOT National Transportation Integrated Search

1997-12-01

This report documents a photochemical modeling study of the potential impacts on air quality of future emissions from alternative fuel vehicles (AFVs). The main objective of the National Renewable Energy Laboratory (NREL) in supporting this study is ...

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.

Impact of climate change on runoff pollution in urban environments

NASA Astrophysics Data System (ADS)

Coutu, S.; Kramer, S.; Barry, D. A.; Roudier, P.

2012-12-01

Runoff from urban environments is generally contaminated. These contaminants mostly originate from road traffic and building envelopes. Facade envelopes generate lead, zinc and even biocides, which are used for facade protection. Road traffic produces particles from tires and brakes. The transport of these pollutants to the environment is controlled by rainfall. The interval, duration and intensity of rainfall events are important as the dynamics of the pollutants are often modeled with non-linear buildup/washoff functions. Buildup occurs during dry weather when pollution accumulates, and is subsequently washed-off at the time of the following rainfall, contaminating surface runoff. Climate predictions include modified rainfall distributions, with changes in both number and intensity of events, even if the expected annual rainfall varies little. Consequently, pollutant concentrations in urban runoff driven by buildup/washoff processes will be affected by these changes in rainfall distributions. We investigated to what extent modifications in future rainfall distributions will impact the concentrations of pollutants present in urban surface runoff. The study used the example of Lausanne, Switzerland (temperate climate zone). Three emission scenarios (time horizon 2090), multiple combinations of RCM/GCM and modifications in rain event frequency were used to simulate future rainfall distributions with various characteristics. Simulated rainfall events were used as inputs for four pairs of buildup/washoff models, in order to compare future pollution concentrations in surface runoff. In this way, uncertainty in model structure was also investigated. Future concentrations were estimated to be between ±40% of today's concentrations depending on the season and, importantly, on the choice of the RCM/GCM model. Overall, however, the dominant factor was the uncertainty inherent in buildup/washoff models, which dominated over the uncertainty in future rainfall distributions. Consequently, the choice of a proper buildup/washoff model, with calibrated site-specific coefficients, is a major factor in modeling future runoff concentrations from contaminated urban surfaces.

The Convoy Model: Explaining Social Relations From a Multidisciplinary Perspective

PubMed Central

Antonucci, Toni C.

2014-01-01

Purpose of the Study: Social relations are a key aspect of aging and the life course. In this paper, we trace the scientific origins of the study of social relations, focusing in particular on research grounded in the convoy model. Design and Methods: We first briefly review and critique influential historical studies to illustrate how the scientific study of social relations developed. Next, we highlight early and current findings grounded in the convoy model that have provided key insights into theory, method, policy, and practice in the study of aging. Results: Early social relations research, while influential, lacked the combined approach of theoretical grounding and methodological rigor. Nevertheless, previous research findings, especially from anthropology, suggested the importance of social relations in the achievement of positive outcomes. Considering both life span and life course perspectives and grounded in a multidisciplinary perspective, the convoy model was developed to unify and consolidate scattered evidence while at the same time directing future empirical and applied research. Early findings are summarized, current evidence presented, and future directions projected. Implications: The convoy model has provided a useful framework in the study of aging, especially for understanding predictors and consequences of social relations across the life course. PMID:24142914

Forecasting and Maximizing Post-Secondary Futures: Dilemmas Over Negative Futures and Their Hidden Costs.

ERIC Educational Resources Information Center

Hoffman, Benjamin B.

Forecasting models for maximizing postsecondary futures and applications of the model are considered. The forecasting of broad human futures has many parallels to human futures in the field of medical prognosis. The concept of "exasperated negative" is used to refer to the suppression of critical information about a negative future with…

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

The role of emotions in UV protection intentions and behaviors.

PubMed

Mahler, Heike I M

2014-01-01

Two studies examined the role of emotions, relative to cognitions, in predicting sun protection intentions and practices. In Study 1, 106 females were assessed for baseline sun protection, ultraviolet (UV) radiation exposure-related cognitions (perceived susceptibility to skin damage, self-efficacy for regular sunscreen use, perceived costs of sun protection use, perceived rewards of tanning), anticipated negative mood following future risky UV behavior, and future sun protection intentions. Self-reported sun protection behavior was then assessed in the same participants five weeks later. The results of Study 1 demonstrated that the extent to which participants' expected to experience negative feelings if they engaged in future risky UV behavior predicted their intentions to sun protect and their subsequent sun protection behaviors independent of their UV radiation exposure-related cognitions. In Study 2, in addition to the assessments collected in Study 1, participants were exposed to an appearance-based intervention that included visual images of their existing skin damage and were then assessed for their emotional reactions to the intervention. The results replicated those of Study 1 and, in addition, showed that negative emotional reactions to the intervention predicted future sun protection intentions and self-reported behaviors at follow-up, independent of the various cognitive factors that are central to prominent models of health behavior. These studies provide preliminary support for the development of expanded health behavior models that incorporate anticipated and experienced emotions.

Seltzer_et_al_2016

EPA Pesticide Factsheets

This dataset supports the modeling study of Seltzer et al. (2016) published in Atmospheric Environment. In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000-2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method??s use for future air quality projections.This dataset is associated with the following publication:Seltzer, K., C

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

NASA Astrophysics Data System (ADS)

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

2002-12-01

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

Peeling back the lithosphere: Controlling parameters, surface expressions and the future directions in delamination modeling

NASA Astrophysics Data System (ADS)

Göğüş, Oğuz H.; Ueda, Kosuke

2018-06-01

Geodynamical models investigate the rheological and physical properties of the lithosphere that peels back (delaminates) from the upper-middle crust. Meanwhile, model predictions are used to relate to a set of observations in the geological context to the test the validity of delamination. Here, we review numerical and analogue models of delamination from these perspectives and provide a number of first-order topics which future modeling studies may address. Models suggest that the presence of the weak lower crust that resides between the strong mantle lithosphere (at least 100 times more viscous/stronger) and the strong upper crust is necessary to develop delamination. Lower crustal weakening may be induced by melt infiltration, shear heating or it naturally occurs through the jelly sandwich type strength profile of the continental lithosphere. The negative buoyancy of the lithosphere required to facilitate the delamination is induced by the pre-existing ocean subduction and/or the lower crustal eclogitization. Surface expression of the peeling back lithosphere has a distinct transient and migratory imprint on the crust, resulting in rapid surface uplift/subsidence, magmatism, heating and shortening/extension. New generation of geodynamical experiments can explain how different types of melting (e.g hydrated, dry melting) occurs with delamination. Reformation of the lithosphere after removal, three dimensional aspects, and the termination of the process are key investigation areas for future research. The robust model predictions, as with other geodynamic modeling studies should be reconciled with observations.

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.

Does the covariance structure matter in longitudinal modelling for the prediction of future CD4 counts?

PubMed

Taylor, J M; Law, N

1998-10-30

We investigate the importance of the assumed covariance structure for longitudinal modelling of CD4 counts. We examine how individual predictions of future CD4 counts are affected by the covariance structure. We consider four covariance structures: one based on an integrated Ornstein-Uhlenbeck stochastic process; one based on Brownian motion, and two derived from standard linear and quadratic random-effects models. Using data from the Multicenter AIDS Cohort Study and from a simulation study, we show that there is a noticeable deterioration in the coverage rate of confidence intervals if we assume the wrong covariance. There is also a loss in efficiency. The quadratic random-effects model is found to be the best in terms of correctly calibrated prediction intervals, but is substantially less efficient than the others. Incorrectly specifying the covariance structure as linear random effects gives too narrow prediction intervals with poor coverage rates. Fitting using the model based on the integrated Ornstein-Uhlenbeck stochastic process is the preferred one of the four considered because of its efficiency and robustness properties. We also use the difference between the future predicted and observed CD4 counts to assess an appropriate transformation of CD4 counts; a fourth root, cube root and square root all appear reasonable choices.

Supersymmetry searches in GUT models with non-universal scalar masses

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

Cannoni, M.; Gómez, M.E.; Ellis, J.

2016-03-01

We study SO(10), SU(5) and flipped SU(5) GUT models with non-universal soft supersymmetry-breaking scalar masses, exploring how they are constrained by LHC supersymmetry searches and cold dark matter experiments, and how they can be probed and distinguished in future experiments. We find characteristic differences between the various GUT scenarios, particularly in the coannihilation region, which is very sensitive to changes of parameters. For example, the flipped SU(5) GUT predicts the possibility of ∼t{sub 1}−χ coannihilation, which is absent in the regions of the SO(10) and SU(5) GUT parameter spaces that we study. We use the relic density predictions in differentmore » models to determine upper bounds for the neutralino masses, and we find large differences between different GUT models in the sparticle spectra for the same LSP mass, leading to direct connections of distinctive possible experimental measurements with the structure of the GUT group. We find that future LHC searches for generic missing E{sub T}, charginos and stops will be able to constrain the different GUT models in complementary ways, as will the Xenon 1 ton and Darwin dark matter scattering experiments and future FERMI or CTA γ-ray searches.« less

Evaluation of the impacts of climate change on disease vectors through ecological niche modelling.

PubMed

Carvalho, B M; Rangel, E F; Vale, M M

2017-08-01

Vector-borne diseases are exceptionally sensitive to climate change. Predicting vector occurrence in specific regions is a challenge that disease control programs must meet in order to plan and execute control interventions and climate change adaptation measures. Recently, an increasing number of scientific articles have applied ecological niche modelling (ENM) to study medically important insects and ticks. With a myriad of available methods, it is challenging to interpret their results. Here we review the future projections of disease vectors produced by ENM, and assess their trends and limitations. Tropical regions are currently occupied by many vector species; but future projections indicate poleward expansions of suitable climates for their occurrence and, therefore, entomological surveillance must be continuously done in areas projected to become suitable. The most commonly applied methods were the maximum entropy algorithm, generalized linear models, the genetic algorithm for rule set prediction, and discriminant analysis. Lack of consideration of the full-known current distribution of the target species on models with future projections has led to questionable predictions. We conclude that there is no ideal 'gold standard' method to model vector distributions; researchers are encouraged to test different methods for the same data. Such practice is becoming common in the field of ENM, but still lags behind in studies of disease vectors.

Stated choice for transportation demand management models : using a disaggregate truth set to study predictive validity

DOT National Transportation Integrated Search

1997-01-01

Discrete choice models have expanded the ability of transportation planners to forecast future trends. Where new services or policies are proposed, the stated-choice approach can provide an objective basis for forecasts. Stated-choice models are subj...

[The future of clinical laboratory database management system].

PubMed

Kambe, M; Imidy, D; Matsubara, A; Sugimoto, Y

1999-09-01

To assess the present status of the clinical laboratory database management system, the difference between the Clinical Laboratory Information System and Clinical Laboratory System was explained in this study. Although three kinds of database management systems (DBMS) were shown including the relational model, tree model and network model, the relational model was found to be the best DBMS for the clinical laboratory database based on our experience and developments of some clinical laboratory expert systems. As a future clinical laboratory database management system, the IC card system connected to an automatic chemical analyzer was proposed for personal health data management and a microscope/video system was proposed for dynamic data management of leukocytes or bacteria.

Combining a Spatial Model and Demand Forecasts to Map Future Surface Coal Mining in Appalachia

PubMed Central

Strager, Michael P.; Strager, Jacquelyn M.; Evans, Jeffrey S.; Dunscomb, Judy K.; Kreps, Brad J.; Maxwell, Aaron E.

2015-01-01

Predicting the locations of future surface coal mining in Appalachia is challenging for a number of reasons. Economic and regulatory factors impact the coal mining industry and forecasts of future coal production do not specifically predict changes in location of future coal production. With the potential environmental impacts from surface coal mining, prediction of the location of future activity would be valuable to decision makers. The goal of this study was to provide a method for predicting future surface coal mining extents under changing economic and regulatory forecasts through the year 2035. This was accomplished by integrating a spatial model with production demand forecasts to predict (1 km2) gridded cell size land cover change. Combining these two inputs was possible with a ratio which linked coal extraction quantities to a unit area extent. The result was a spatial distribution of probabilities allocated over forecasted demand for the Appalachian region including northern, central, southern, and eastern Illinois coal regions. The results can be used to better plan for land use alterations and potential cumulative impacts. PMID:26090883

Application of scenario-neutral methods to quantify impacts of climate change on water resources in East Africa

NASA Astrophysics Data System (ADS)

Ascott, M.; Macdonald, D.; Lapworth, D.; Tindimugaya, C.

2017-12-01

Quantification of the impact of climate change on water resources is essential for future resource planning. Unfortunately, climate change impact studies in African regions are often hindered by the extent in variability in future rainfall predictions, which also diverge from current drying trends. To overcome this limitation, "scenario-neutral" methods have been developed which stress a hydrological system using a wide range of climate futures to build a "climate response surface". We developed a hydrological model and scenario-neutral framework to quantify climate change impacts on river flows in the Katonga catchment, Uganda. Using the lumped catchment model GR4J, an acceptable calibration to historic daily flows (1966 - 2010, NSE = 0.69) was achieved. Using a delta change approach, we then systematically changed rainfall and PET inputs to develop response surfaces for key metrics, developed with Ugandan water resources planners (e.g. Q5, Q95). Scenarios from the CMIP5 models for 2030s and 2050s were then overlain on the response surface. The CMIP5 scenarios show consistent increases in temperature but large variability in rainfall increases, which results in substantial variability in increases in river flows. The developed response surface covers a wide range of climate futures beyond the CMIP5 projections, and can help water resources planners understand the sensitivity of water resource systems to future changes. When future climate scenarios are available, these can be directly overlain on the response surface without the need to re-run the hydrological model. Further work will consider using scenario-neutral approaches in more complex, semi-distributed models (e.g. SWAT), and will consider land use and socioeconomic change.

Projected Irrigation Requirement Under Climate Change in Korean Peninsula by Apply Global Hydrologic Model to Local Scale.

NASA Astrophysics Data System (ADS)

Yang, B.; Lee, D. K.

2016-12-01

Understanding spatial distribution of irrigation requirement is critically important for agricultural water management. However, many studies considering future agricultural water management in Korea assessed irrigation requirement on watershed or administrative district scale, but have not accounted the spatial distribution. Lumped hydrologic model has typically used in Korea for simulating watershed scale irrigation requirement, while distribution hydrologic model can simulate the spatial distribution grid by grid. To overcome this shortcoming, here we applied a grid base global hydrologic model (H08) into local scale to estimate spatial distribution under future irrigation requirement of Korean Peninsula. Korea is one of the world's most densely populated countries, with also high produce and demand of rice which requires higher soil moisture than other crops. Although, most of the precipitation concentrate in particular season and disagree with crop growth season. This precipitation character makes management of agricultural water which is approximately 60% of total water usage critical issue in Korea. Furthermore, under future climate change, the precipitation predicted to be more concentrated and necessary need change of future water management plan. In order to apply global hydrological model into local scale, we selected appropriate major crops under social and local climate condition in Korea to estimate cropping area and yield, and revised the cropping area map more accurately. As a result, future irrigation requirement estimation varies under each projection, however, slightly decreased in most case. The simulation reveals, evapotranspiration increase slightly while effective precipitation also increase to balance the irrigation requirement. This finding suggest practical guideline to decision makers for further agricultural water management plan including future development of water supply plan to resolve water scarcity.

A framework to analyze emissions implications of ...

EPA Pesticide Factsheets

Future year emissions depend highly on the evolution of the economy, technology and current and future regulatory drivers. A scenario framework was adopted to analyze various technology development pathways and societal change while considering existing regulations and future uncertainty in regulations and evaluate resulting emissions growth patterns. The framework integrates EPA’s energy systems model with an economic Input-Output (I/O) Life Cycle Assessment model. The EPAUS9r MARKAL database is assembled from a set of technologies to represent the U.S. energy system within MARKAL bottom-up technology rich energy modeling framework. The general state of the economy and consequent demands for goods and services from these sectors are taken exogenously in MARKAL. It is important to characterize exogenous inputs about the economy to appropriately represent the industrial sector outlook for each of the scenarios and case studies evaluated. An economic input-output (I/O) model of the US economy is constructed to link up with MARKAL. The I/O model enables user to change input requirements (e.g. energy intensity) for different sectors or the share of consumer income expended on a given good. This gives end-users a mechanism for modeling change in the two dimensions of technological progress and consumer preferences that define the future scenarios. The framework will then be extended to include environmental I/O framework to track life cycle emissions associated

The role of lymphadenectomy in endometrial cancer: was the ASTEC trial doomed by design and are we destined to repeat that mistake?

PubMed

Naumann, R Wendel

2012-07-01

This study examines the design of previous and future trials of lymph node dissection in endometrial cancer. Data from previous trials were used to construct a decision analysis modeling the risk of lymphatic spread and the effects of treatment on patients with endometrial cancer. This model was then applied to previous trials as well as other future trial designs that might be used to address this subject. Comparing the predicted and actual results in the ASTEC trial, the model closely mimics the survival results with and without lymph node dissection for the low and high risk groups. The model suggests a survival difference of less than 2% between the experimental and control arms of the ASTEC trial under all circumstances. Sensitivity analyses reveal that these conclusions are robust. Future trial designs were also modeled with hysterectomy only, hysterectomy with radiation in intermediate risk patients, and staging with radiation only with node positive patients. Predicted outcomes for these approaches yield survival rates of 88%, 90%, and 93% in clinical stage I patients who have a risk of pelvic node involvement of approximately 7%. These estimates were 78%, 82%, and 89% in intermediate risk patients who have a risk of nodal spread of approximately 15%. This model accurately predicts the outcome of previous trials and demonstrates that even if lymph node dissection was therapeutic, these trials would have been negative due to study design. Furthermore, future trial designs that are being considered would need to be conducted in high-intermediate risk patients to detect any difference. Copyright © 2012 Elsevier Inc. All rights reserved.

Theory of choice in bandit, information sampling and foraging tasks.

PubMed

Averbeck, Bruno B

2015-03-01

Decision making has been studied with a wide array of tasks. Here we examine the theoretical structure of bandit, information sampling and foraging tasks. These tasks move beyond tasks where the choice in the current trial does not affect future expected rewards. We have modeled these tasks using Markov decision processes (MDPs). MDPs provide a general framework for modeling tasks in which decisions affect the information on which future choices will be made. Under the assumption that agents are maximizing expected rewards, MDPs provide normative solutions. We find that all three classes of tasks pose choices among actions which trade-off immediate and future expected rewards. The tasks drive these trade-offs in unique ways, however. For bandit and information sampling tasks, increasing uncertainty or the time horizon shifts value to actions that pay-off in the future. Correspondingly, decreasing uncertainty increases the relative value of actions that pay-off immediately. For foraging tasks the time-horizon plays the dominant role, as choices do not affect future uncertainty in these tasks.

Past, present and future distributions of an Iberian Endemic, Lepus granatensis: ecological and evolutionary clues from species distribution models.

PubMed

Acevedo, Pelayo; Melo-Ferreira, José; Real, Raimundo; Alves, Paulo Célio

2012-01-01

The application of species distribution models (SDMs) in ecology and conservation biology is increasing and assuming an important role, mainly because they can be used to hindcast past and predict current and future species distributions. However, the accuracy of SDMs depends on the quality of the data and on appropriate theoretical frameworks. In this study, comprehensive data on the current distribution of the Iberian hare (Lepus granatensis) were used to i) determine the species' ecogeographical constraints, ii) hindcast a climatic model for the last glacial maximum (LGM), relating it to inferences derived from molecular studies, and iii) calibrate a model to assess the species future distribution trends (up to 2080). Our results showed that the climatic factor (in its pure effect and when it is combined with the land-cover factor) is the most important descriptor of the current distribution of the Iberian hare. In addition, the model's output was a reliable index of the local probability of species occurrence, which is a valuable tool to guide species management decisions and conservation planning. Climatic potential obtained for the LGM was combined with molecular data and the results suggest that several glacial refugia may have existed for the species within the major Iberian refugium. Finally, a high probability of occurrence of the Iberian hare in the current species range and a northward expansion were predicted for future. Given its current environmental envelope and evolutionary history, we discuss the macroecology of the Iberian hare and its sensitivity to climate change.

Modeling the potential impacts of climate change on the water table level of selected forested wetlands in the southeastern United States

NASA Astrophysics Data System (ADS)

Zhu, Jie; Sun, Ge; Li, Wenhong; Zhang, Yu; Miao, Guofang; Noormets, Asko; McNulty, Steve G.; King, John S.; Kumar, Mukesh; Wang, Xuan

2017-12-01

The southeastern United States hosts extensive forested wetlands, providing ecosystem services including carbon sequestration, water quality improvement, groundwater recharge, and wildlife habitat. However, these wetland ecosystems are dependent on local climate and hydrology, and are therefore at risk due to climate and land use change. This study develops site-specific empirical hydrologic models for five forested wetlands with different characteristics by analyzing long-term observed meteorological and hydrological data. These wetlands represent typical cypress ponds/swamps, Carolina bays, pine flatwoods, drained pocosins, and natural bottomland hardwood ecosystems. The validated empirical models are then applied at each wetland to predict future water table changes using climate projections from 20 general circulation models (GCMs) participating in Coupled Model Inter-comparison Project 5 (CMIP5) under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios. We show that combined future changes in precipitation and potential evapotranspiration would significantly alter wetland hydrology including groundwater dynamics by the end of the 21st century. Compared to the historical period, all five wetlands are predicted to become drier over time. The mean water table depth is predicted to drop by 4 to 22 cm in response to the decrease in water availability (i.e., precipitation minus potential evapotranspiration) by the year 2100. Among the five examined wetlands, the depressional wetland in hot and humid Florida appears to be most vulnerable to future climate change. This study provides quantitative information on the potential magnitude of wetland hydrological response to future climate change in typical forested wetlands in the southeastern US.

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.

Evaluation of the Triple Code Model of numerical processing-Reviewing past neuroimaging and clinical findings.

PubMed

Siemann, Julia; Petermann, Franz

2018-01-01

This review reconciles past findings on numerical processing with key assumptions of the most predominant model of arithmetic in the literature, the Triple Code Model (TCM). This is implemented by reporting diverse findings in the literature ranging from behavioral studies on basic arithmetic operations over neuroimaging studies on numerical processing to developmental studies concerned with arithmetic acquisition, with a special focus on developmental dyscalculia (DD). We evaluate whether these studies corroborate the model and discuss possible reasons for contradictory findings. A separate section is dedicated to the transfer of TCM to arithmetic development and to alternative accounts focusing on developmental questions of numerical processing. We conclude with recommendations for future directions of arithmetic research, raising questions that require answers in models of healthy as well as abnormal mathematical development. This review assesses the leading model in the field of arithmetic processing (Triple Code Model) by presenting knowledge from interdisciplinary research. It assesses the observed contradictory findings and integrates the resulting opposing viewpoints. The focus is on the development of arithmetic expertise as well as abnormal mathematical development. The original aspect of this article is that it points to a gap in research on these topics and provides possible solutions for future models. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Past, Present, and Future of Computational Models of Cognitive Development

ERIC Educational Resources Information Center

Schlesinger, Matthew; McMurray, Bob

2012-01-01

Does modeling matter? We address this question by providing a broad survey of the computational models of cognitive development that have been proposed and studied over the last three decades. We begin by noting the advantages and limitations of computational models. We then describe four key dimensions across which models of development can be…

Generation of future potential scenarios in an Alpine Catchment by applying bias-correction techniques, delta-change approaches and stochastic Weather Generators at different spatial scale. Analysis of their influence on basic and drought statistics.

NASA Astrophysics Data System (ADS)

Collados-Lara, Antonio-Juan; Pulido-Velazquez, David; Pardo-Iguzquiza, Eulogio

2017-04-01

Assessing impacts of potential future climate change scenarios in precipitation and temperature is essential to design adaptive strategies in water resources systems. The objective of this work is to analyze the possibilities of different statistical downscaling methods to generate future potential scenarios in an Alpine Catchment from historical data and the available climate models simulations performed in the frame of the CORDEX EU project. The initial information employed to define these downscaling approaches are the historical climatic data (taken from the Spain02 project for the period 1971-2000 with a spatial resolution of 12.5 Km) and the future series provided by climatic models in the horizon period 2071-2100 . We have used information coming from nine climate model simulations (obtained from five different Regional climate models (RCM) nested to four different Global Climate Models (GCM)) from the European CORDEX project. In our application we have focused on the Representative Concentration Pathways (RCP) 8.5 emissions scenario, which is the most unfavorable scenario considered in the fifth Assessment Report (AR5) by the Intergovernmental Panel on Climate Change (IPCC). For each RCM we have generated future climate series for the period 2071-2100 by applying two different approaches, bias correction and delta change, and five different transformation techniques (first moment correction, first and second moment correction, regression functions, quantile mapping using distribution derived transformation and quantile mapping using empirical quantiles) for both of them. Ensembles of the obtained series were proposed to obtain more representative potential future climate scenarios to be employed to study potential impacts. In this work we propose a non-equifeaseble combination of the future series giving more weight to those coming from models (delta change approaches) or combination of models and techniques that provides better approximation to the basic and drought statistic of the historical data. A multi-objective analysis using basic statistics (mean, standard deviation and asymmetry coefficient) and droughts statistics (duration, magnitude and intensity) has been performed to identify which models are better in terms of goodness of fit to reproduce the historical series. The drought statistics have been obtained from the Standard Precipitation index (SPI) series using the Theory of Runs. This analysis allows discriminate the best RCM and the best combination of model and correction technique in the bias-correction method. We have also analyzed the possibilities of using different Stochastic Weather Generators to approximate the basic and droughts statistics of the historical series. These analyses have been performed in our case study in a lumped and in a distributed way in order to assess its sensibility to the spatial scale. The statistic of the future temperature series obtained with different ensemble options are quite homogeneous, but the precipitation shows a higher sensibility to the adopted method and spatial scale. The global increment in the mean temperature values are 31.79 %, 31.79 %, 31.03 % and 31.74 % for the distributed bias-correction, distributed delta-change, lumped bias-correction and lumped delta-change ensembles respectively and in the precipitation they are -25.48 %, -28.49 %, -26.42 % and -27.35% respectively. Acknowledgments: This research work has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank Spain02 and CORDEX projects for the data provided for this study and the R package qmap.

Impact of Demographic Trends on Future Development Patterns and the Loss of Open Space in the California Mojave Desert

NASA Astrophysics Data System (ADS)

Gomben, Peter; Lilieholm, Robert; Gonzalez-Guillen, Manuel

2012-02-01

During the post-World War II era, the Mojave Desert Region of San Bernardino County, California, has experienced rapid levels of population growth. Over the past several decades, growth has accelerated, accompanied by significant shifts in ethnic composition, most notably from predominantly White non-Hispanic to Hispanic. This study explores the impacts of changing ethnicity on future development and the loss of open space by modeling ethnic propensities regarding family size and settlement preferences reflected by U.S. Census Bureau data. Demographic trends and land conversion data were obtained for seven Mojave Desert communities for the period between 1990 and 2001. Using a spatially explicit, logistic regression-based urban growth model, these data and trends were used to project community-specific future growth patterns from 2000 to 2020 under three future settlement scenarios: (1) an "historic" scenario reported in earlier research that uses a Mojave-wide average settlement density of 3.76 persons/ha; (2) an "existing" scenario based on community-specific settlement densities as of 2001; and (3) a "demographic futures" scenario based on community-specific settlement densities that explicitly model the Region's changing ethnicity. Results found that under the demographic futures scenario, by 2020 roughly 53% of within-community open space would remain, under the existing scenario only 40% would remain, and under the historic scenario model the communities would have what amounts to a deficit of open space. Differences in the loss of open space across the scenarios demonstrate the importance of considering demographic trends that are reflective of the residential needs and preferences of projected future populations.

Changes in the shoreline at Paradip Port, India in response to climate change

NASA Astrophysics Data System (ADS)

Gopikrishna, B.; Deo, M. C.

2018-02-01

One of the popular methods to predict shoreline shifts into the future involves use of a shoreline evolution model driven by the historical wave climate. It is however understood by now that historical wave conditions might substantially change in future in response to climate change induced by the global warming. The future shoreline changes as well as sediment transport therefore need to be determined with the help of future projections of wave climate. In this work this is done at the port of Paradip situated along the east coast of India. The high resolution wind resulting from a climate modelling experiment called: CORDEX, South Asia, was used to simulate waves over two time-slices of 25 years each in past and future. The wave simulations were carried out with the help of a numerical wave model. Thereafter, rates of longshore sediment transport as well as shoreline shifts were determined over past and future using a numerical shoreline model. It was found that at Paradip Port the net littoral drift per metre width of cross-shore might go up by 37% and so also the net accumulated drift over the entire cross-shore width by 71%. This could be caused by an increase in the mean significant wave height of around 32% and also by changes in the frequency and direction of waves. The intensification of waves in turn might result from an increase in the mean wind speed of around 19%. Similarly, the horizontal extent of the beach accretion and erosion at the port's southern breakwater might go up by 4 m and 8 m, respectively, from the current level in another 25 years. This study should be useful in framing future port management strategies.

Impact of demographic trends on future development patterns and the loss of open space in the California Mojave Desert.

PubMed

Gomben, Peter; Lilieholm, Robert; Gonzalez-Guillen, Manuel

2012-02-01

During the post-World War II era, the Mojave Desert Region of San Bernardino County, California, has experienced rapid levels of population growth. Over the past several decades, growth has accelerated, accompanied by significant shifts in ethnic composition, most notably from predominantly White non-Hispanic to Hispanic. This study explores the impacts of changing ethnicity on future development and the loss of open space by modeling ethnic propensities regarding family size and settlement preferences reflected by U.S. Census Bureau data. Demographic trends and land conversion data were obtained for seven Mojave Desert communities for the period between 1990 and 2001. Using a spatially explicit, logistic regression-based urban growth model, these data and trends were used to project community-specific future growth patterns from 2000 to 2020 under three future settlement scenarios: (1) an "historic" scenario reported in earlier research that uses a Mojave-wide average settlement density of 3.76 persons/ha; (2) an "existing" scenario based on community-specific settlement densities as of 2001; and (3) a "demographic futures" scenario based on community-specific settlement densities that explicitly model the Region's changing ethnicity. Results found that under the demographic futures scenario, by 2020 roughly 53% of within-community open space would remain, under the existing scenario only 40% would remain, and under the historic scenario model the communities would have what amounts to a deficit of open space. Differences in the loss of open space across the scenarios demonstrate the importance of considering demographic trends that are reflective of the residential needs and preferences of projected future populations.

Expansion of the Lyme Disease Vector Ixodes Scapularis in Canada Inferred from CMIP5 Climate Projections

PubMed Central

McPherson, Michelle; García-García, Almudena; Cuesta-Valero, Francisco José; Hansen-Ketchum, Patti; MacDougall, Donna; Ogden, Nicholas Hume

2017-01-01

Background: A number of studies have assessed possible climate change impacts on the Lyme disease vector, Ixodes scapularis. However, most have used surface air temperature from only one climate model simulation and/or one emission scenario, representing only one possible climate future. Objectives: We quantified effects of different Representative Concentration Pathway (RCP) and climate model outputs on the projected future changes in the basic reproduction number (R0) of I. scapularis to explore uncertainties in future R0 estimates. Methods: We used surface air temperature generated by a complete set of General Circulation Models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to hindcast historical (1971–2000), and to forecast future effects of climate change on the R0 of I. scapularis for the periods 2011–2040 and 2041–2070. Results: Increases in the multimodel mean R0 values estimated for both future periods, relative to 1971–2000, were statistically significant under all RCP scenarios for all of Nova Scotia, areas of New Brunswick and Quebec, Ontario south of 47°N, and Manitoba south of 52°N. When comparing RCP scenarios, only the estimated R0 mean values between RCP6.0 and RCP8.5 showed statistically significant differences for any future time period. Conclusion: Our results highlight the potential for climate change to have an effect on future Lyme disease risk in Canada even if the Paris Agreement’s goal to keep global warming below 2°C is achieved, although mitigation reducing emissions from RCP8.5 levels to those of RCP6.0 or less would be expected to slow tick invasion after the 2030s. https://doi.org/10.1289/EHP57 PMID:28599266

Land Cover and Climate Change May Limit Invasiveness of Rhododendron ponticum in Wales.

PubMed

Manzoor, Syed A; Griffiths, Geoffrey; Iizuka, Kotaro; Lukac, Martin

2018-01-01

Invasive plant species represent a serious threat to biodiversity precipitating a sustained global effort to eradicate or at least control the spread of this phenomenon. Current distribution ranges of many invasive species are likely to be modified in the future by land cover and climate change. Thus, invasion management can be made more effective by forecasting the potential spread of invasive species. Rhododendron ponticum (L.) is an aggressive invasive species which appears well suited to western areas of the UK. We made use of MAXENT modeling environment to develop a current distribution model and to assess the likely effects of land cover and climatic conditions (LCCs) on the future distribution of this species in the Snowdonia National park in Wales. Six global circulation models (GCMs) and two representative concentration pathways (RCPs), together with a land cover simulation for 2050 were used to investigate species' response to future environmental conditions. Having considered a range of environmental variables as predictors and carried out the AICc-based model selection, we find that under all LCCs considered in this study, the range of R. ponticum in Wales is likely to contract in the future. Land cover and topographic variables were found to be the most important predictors of the distribution of R. ponticum . This information, together with maps indicating future distribution trends will aid the development of mitigation practices to control R. ponticum .

Effects of climate change on hydrology and hydraulics of Qu River Basin, East China.

NASA Astrophysics Data System (ADS)

Gao, C.; Zhu, Q.; Zhao, Z.; Pan, S.; Xu, Y. P.

2015-12-01

The impacts of climate change on regional hydrological extreme events have attracted much attention in recent years. This paper aims to provide a general overview of changes on future runoffs and water levels in the Qu River Basin, upper reaches of Qiantang River, East China by combining future climate scenarios, hydrological model and 1D hydraulic model. The outputs of four GCMs BCC, BNU, CanESM and CSIRO under two scenarios RCP4.5 and RCP8.5 for 2021-2050 are chosen to represent future climate change projections. The LARS-WG statistical downscaling method is used to downscale the coarse GCM outputs and generate 50 years of synthetic precipitation and maximum and minimum temperatures to drive the GR4J hydrological model and the 1D hydraulic model for the baseline period 1971-2000 and the future period 2021-2050. Finally the POT (Peaks Over Threshold) method is applied to analyze the change of extreme events in the study area. The results show that design runoffs and water levels all indicate an increasing trend in the future period for Changshangang River, Jiangshangang River and Qu River at most cases, especially for small return periods(≤20), and for Qu River the increase becomes larger, which suggests that the risk of flooding will probably become greater and appropriate adaptation measures need to be taken.

High-resolution dynamical downscaling of the future Alpine climate

NASA Astrophysics Data System (ADS)

Bozhinova, Denica; José Gómez-Navarro, Juan; Raible, Christoph

2017-04-01

The Alpine region and Switzerland is a challenging area for simulating and analysing Global Climate Model (GCM) results. This is mostly due to the combination of a very complex topography and the still rather coarse horizontal resolution of current GCMs, in which not all of the many-scale processes that drive the local weather and climate can be resolved. In our study, the Weather Research and Forecasting (WRF) model is used to dynamically downscale a GCM simulation to a resolution as high as 2 km x 2 km. WRF is driven by initial and boundary conditions produced with the Community Earth System Model (CESM) for the recent past (control run) and until 2100 using the RCP8.5 climate scenario (future run). The control run downscaled with WRF covers the period 1976-2005, while the future run investigates a 20-year-slice simulated for the 2080-2099. We compare the control WRF-CESM simulations to an observational product provided by MeteoSwiss and an additional WRF simulation driven by the ERA-Interim reanalysis, to estimate the bias that is introduced by the extra modelling step of our framework. Several bias-correction methods are evaluated, including a quantile mapping technique, to ameliorate the bias in the control WRF-CESM simulation. In the next step of our study these corrections are applied to our future WRF-CESM run. The resulting downscaled and bias-corrected data is analysed for the properties of precipitation and wind speed in the future climate. Our special interest focuses on the absolute quantities simulated for these meteorological variables as these are used to identify extreme events, such as wind storms and situations that can lead to floods.

Past and ongoing shifts in Joshua tree distribution support future modeled range contraction

USGS Publications Warehouse

Cole, Kenneth L.; Ironside, Kirsten; Eischeid, Jon K.; Garfin, Gregg; Duffy, Phil; Toney, Chris

2011-01-01

The future distribution of the Joshua tree (Yucca brevifolia) is projected by combining a geostatistical analysis of 20th-century climates over its current range, future modeled climates, and paleoecological data showing its response to a past similar climate change. As climate rapidly warmed ;11 700 years ago, the range of Joshua tree contracted, leaving only the populations near what had been its northernmost limit. Its ability to spread northward into new suitable habitats after this time may have been inhibited by the somewhat earlier extinction of megafaunal dispersers, especially the Shasta ground sloth. We applied a model of climate suitability for Joshua tree, developed from its 20th-century range and climates, to future climates modeled through a set of six individual general circulation models (GCM) and one suite of 22 models for the late 21st century. All distribution data, observed climate data, and future GCM results were scaled to spatial grids of ;1 km and ;4 km in order to facilitate application within this topographically complex region. All of the models project the future elimination of Joshua tree throughout most of the southern portions of its current range. Although estimates of future monthly precipitation differ between the models, these changes are outweighed by large increases in temperature common to all the models. Only a few populations within the current range are predicted to be sustainable. Several models project significant potential future expansion into new areas beyond the current range, but the species' Historical and current rates of dispersal would seem to prevent natural expansion into these new areas. Several areas are predicted to be potential sites for relocation/ assisted migration. This project demonstrates how information from paleoecology and modern ecology can be integrated in order to understand ongoing processes and future distributions.

Impacts of elevated temperature on ant species, communities and ecological roles at two temperate forests in Eastern North America

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

Dunn, Robert

2014-04-01

Over the course of five years we have established a long-term array of warming chambers at Duke and Harvard Forest that simulate future conditions with regard to temperature. In these chambers, we have studied, ants, other animal taxa, fungi, bacteria and plants and their responses to the treatments. We have coupled these studies with lab experiments, large-scale observations, and models to contextualize our results. Finally, we have developed integrative models of the future distribution of species and their consequences as a result of warming in eastern North America and more generally.

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.

Responses of Terrestrial Ecosystems’ Net Primary Productivity to Future Regional Climate Change in China

PubMed Central

Zhao, Dongsheng; Wu, Shaohong; Yin, Yunhe

2013-01-01

The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems’ response to global climate change. China’s ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund–Potsdam–Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China’s terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change. PMID:23593325

Responses of terrestrial ecosystems' net primary productivity to future regional climate change in China.

PubMed

Zhao, Dongsheng; Wu, Shaohong; Yin, Yunhe

2013-01-01

The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems' response to global climate change. China's ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund-Potsdam-Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China's terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change.

Contributions to Future Stratospheric Climate Change: An Idealized Chemistry-Climate Model Sensitivity Study

NASA Technical Reports Server (NTRS)

Hurwitz, M. M.; Braesicke, P.; Pyle, J. A.

2010-01-01

Within the framework of an idealized model sensitivity study, three of the main contributors to future stratospheric climate change are evaluated: increases in greenhouse gas concentrations, ozone recovery, and changing sea surface temperatures (SSTs). These three contributors are explored in combination and separately, to test the interactions between ozone and climate; the linearity of their contributions to stratospheric climate change is also assessed. In a simplified chemistry-climate model, stratospheric global mean temperature is most sensitive to CO2 doubling, followed by ozone depletion, then by increased SSTs. At polar latitudes, the Northern Hemisphere (NH) stratosphere is more sensitive to changes in CO2, SSTs and O3 than is the Southern Hemisphere (SH); the opposing responses to ozone depletion under low or high background CO2 concentrations, as seen with present-day SSTs, are much weaker and are not statistically significant under enhanced SSTs. Consistent with previous studies, the strength of the Brewer-Dobson circulation is found to increase in an idealized future climate; SSTs contribute most to this increase in the upper troposphere/lower stratosphere (UT/LS) region, while CO2 and ozone changes contribute most in the stratosphere and mesosphere.

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.

Spatially distributed potential evapotranspiration modeling and climate projections.

PubMed

Gharbia, Salem S; Smullen, Trevor; Gill, Laurence; Johnston, Paul; Pilla, Francesco

2018-08-15

Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50m 2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Modeled Instructional Routines: Will Preservice Teachers Embed Them in Their Future Lessons?

ERIC Educational Resources Information Center

Slaughter, Sandra K.

2017-01-01

Modeling in the classroom is the key to successful teaching. This study examines whether preservice teachers would use content area literacy instructional routines, which had been modeled in my university course, in their student teaching and first-year classrooms. Both content area literacy and disciplinary literacy were modeled in my university…

Transition and protective agency of early childhood learning behaviors as portents of later school attendance and adjustment.

PubMed

McDermott, Paul A; Rikoon, Samuel H; Fantuzzo, John W

2016-02-01

This article reports on the study of differential change trajectories for early childhood learning behaviors as they relate to future classroom adjustment and school attendance. A large sample (N=2152) of Head Start children was followed through prekindergarten, kindergarten, and 1st grade. Classroom learning behaviors were assessed twice each year by teachers who observed gradual declines in Competence Motivation and Attentional Persistence as children transitioned through schooling. Cross-classified multilevel growth models revealed distinct transitional pathways for future adjustment versus maladjustment and sporadic versus chronic absenteeism. Generalized multilevel logistic modeling and receiver operating characteristic curve analyses showed that teachers' earliest assessments were substantially predictive of eventual good classroom adjustment and school attendance, with increasing accuracy for prediction of future sociobehavioral adjustment as time progressed. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Revisiting historical climatic signals to better explore the future: prospects of water cycle changes in Central Sahel

NASA Astrophysics Data System (ADS)

Leauthaud, C.; Demarty, J.; Cappelaere, B.; Grippa, M.; Kergoat, L.; Velluet, C.; Guichard, F.; Mougin, E.; Chelbi, S.; Sultan, B.

2015-06-01

Rainfall and climatic conditions are the main drivers of natural and cultivated vegetation productivity in the semiarid region of Central Sahel. In a context of decreasing cultivable area per capita, understanding and predicting changes in the water cycle are crucial. Yet, it remains challenging to project future climatic conditions in West Africa since there is no consensus on the sign of future precipitation changes in simulations coming from climate models. The Sahel region has experienced severe climatic changes in the past 60 years that can provide a first basis to understand the response of the water cycle to non-stationary conditions in this part of the world. The objective of this study was to better understand the response of the water cycle to highly variable climatic regimes in Central Sahel using historical climate records and the coupling of a land surface energy and water model with a vegetation model that, when combined, simulated the Sahelian water, energy and vegetation cycles. To do so, we relied on a reconstructed long-term climate series in Niamey, Republic of Niger, in which three precipitation regimes can be distinguished with a relative deficit exceeding 25% for the driest period compared to the wettest period. Two temperature scenarios (+2 and +4 °C) consistent with future warming scenarios were superimposed to this climatic signal to generate six virtual future 20-year climate time series. Simulations by the two coupled models forced by these virtual scenarios showed a strong response of the water budget and its components to temperature and precipitation changes, including decreases in transpiration, runoff and drainage for all scenarios but those with highest precipitation. Such climatic changes also strongly impacted soil temperature and moisture. This study illustrates the potential of using the strong climatic variations recorded in the past decades to better understand potential future climate variations.

Assessment of the Present and Future Offshore Wind Power Potential: A Case Study in a Target Territory of the Baltic Sea Near the Latvian Coast

PubMed Central

Teilans, Artis

2013-01-01

Offshore wind energy development promises to be a significant domestic renewable energy source in Latvia. The reliable prediction of present and future wind resources at offshore sites is crucial for planning and selecting the location for wind farms. The overall goal of this paper is the assessment of offshore wind power potential in a target territory of the Baltic Sea near the Latvian coast as well as the identification of a trend in the future wind energy potential for the study territory. The regional climate model CLM and High Resolution Limited Area Model (Hirlam) simulations were used to obtain the wind climatology data for the study area. The results indicated that offshore wind energy is promising for expanding the national electricity generation and will continue to be a stable resource for electricity generation in the region over the 21st century. PMID:23983619

Projecting Sexual and Injecting HIV Risks into Future Outcomes with Agent-Based Modeling

NASA Astrophysics Data System (ADS)

Bobashev, Georgiy V.; Morris, Robert J.; Zule, William A.

Longitudinal studies of health outcomes for HIV could be very costly cumbersome and not representative of the risk population. Conversely, cross-sectional approaches could be representative but rely on the retrospective information to estimate prevalence and incidence. We present an Agent-based Modeling (ABM) approach where we use behavioral data from a cross-sectional representative study and project the behavior into the future so that the risks of acquiring HIV could be studied in a dynamical/temporal sense. We show how the blend of behavior and contact network factors (sexual, injecting) play the role in the risk of future HIV acquisition and time till obtaining HIV. We show which subjects are the most likely persons to get HIV in the next year, and whom they are likely to infect. We examine how different behaviors are related to the increase or decrease of HIV risks and how to estimate the quantifiable risk measures such as survival HIV free.

Correlations in fertility across generations: can low fertility persist?

PubMed

Kolk, Martin; Cownden, Daniel; Enquist, Magnus

2014-03-22

Correlations in family size across generations could have a major influence on human population size in the future. Empirical studies have shown that the associations between the fertility of parents and the fertility of children are substantial and growing over time. Despite their potential long-term consequences, intergenerational fertility correlations have largely been ignored by researchers. We present a model of the fertility transition as a cultural process acting on new lifestyles associated with fertility. Differences in parental and social influences on the acquisition of these lifestyles result in intergenerational correlations in fertility. We show different scenarios for future population size based on models that disregard intergenerational correlations in fertility, models with fertility correlations and a single lifestyle, and models with fertility correlations and multiple lifestyles. We show that intergenerational fertility correlations will result in an increase in fertility over time. However, present low-fertility levels may persist if the rapid introduction of new cultural lifestyles continues into the future.

Correlations in fertility across generations: can low fertility persist?

PubMed Central

Kolk, Martin; Cownden, Daniel; Enquist, Magnus

2014-01-01

Correlations in family size across generations could have a major influence on human population size in the future. Empirical studies have shown that the associations between the fertility of parents and the fertility of children are substantial and growing over time. Despite their potential long-term consequences, intergenerational fertility correlations have largely been ignored by researchers. We present a model of the fertility transition as a cultural process acting on new lifestyles associated with fertility. Differences in parental and social influences on the acquisition of these lifestyles result in intergenerational correlations in fertility. We show different scenarios for future population size based on models that disregard intergenerational correlations in fertility, models with fertility correlations and a single lifestyle, and models with fertility correlations and multiple lifestyles. We show that intergenerational fertility correlations will result in an increase in fertility over time. However, present low-fertility levels may persist if the rapid introduction of new cultural lifestyles continues into the future. PMID:24478294

High Assurance Human-Centric Decision Systems

DTIC Science & Technology

2013-05-01

of the human operator who is multitasking in this situation. 38 Crandall, Cummings, and Mitchell [7], [8] have introduced “fan-out” models to estimate...planning in multitasking contexts. In the future, we will study extensions of our cog- nitive model. Currently, the cognitive model is focused solely

Modelling the effects of past and future climate on the risk of bluetongue emergence in Europe

PubMed Central

Guis, Helene; Caminade, Cyril; Calvete, Carlos; Morse, Andrew P.; Tran, Annelise; Baylis, Matthew

2012-01-01

Vector-borne diseases are among those most sensitive to climate because the ecology of vectors and the development rate of pathogens within them are highly dependent on environmental conditions. Bluetongue (BT), a recently emerged arboviral disease of ruminants in Europe, is often cited as an illustration of climate's impact on disease emergence, although no study has yet tested this association. Here, we develop a framework to quantitatively evaluate the effects of climate on BT's emergence in Europe by integrating high-resolution climate observations and model simulations within a mechanistic model of BT transmission risk. We demonstrate that a climate-driven model explains, in both space and time, many aspects of BT's recent emergence and spread, including the 2006 BT outbreak in northwest Europe which occurred in the year of highest projected risk since at least 1960. Furthermore, the model provides mechanistic insight into BT's emergence, suggesting that the drivers of emergence across Europe differ between the South and the North. Driven by simulated future climate from an ensemble of 11 regional climate models, the model projects increase in the future risk of BT emergence across most of Europe with uncertainty in rate but not in trend. The framework described here is adaptable and applicable to other diseases, where the link between climate and disease transmission risk can be quantified, permitting the evaluation of scale and uncertainty in climate change's impact on the future of such diseases. PMID:21697167

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.

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.

Franchising the Future

ERIC Educational Resources Information Center

Colomb, Gregory G.

2010-01-01

Central to the future of rhetoric and composition (or writing studies or whatever label we use) is the service mission of composition: to teach students to write. But that term "service" has not and will not serve us well. This essay examines the limitations and dangers of a service mission and explores a different model, that of a franchise, a…

Social Learning Theory: A Multicultural Study of Influences on Ethical Behavior

ERIC Educational Resources Information Center

Hanna, Richard C.; Crittenden, Victoria L.; Crittenden, William F.

2013-01-01

We propose Social Learning Theory as a theoretical foundation for understanding the ethical standards of future business leaders. Using data drawn from students from 115 four-year undergraduate institutions in 36 different countries, the relationships among role models, capitalism, and laws were examined. The data suggest that future business…

Current and Future Effects of Mexican Immigration in California. Executive Summary. R-3365/1-CR.

ERIC Educational Resources Information Center

McCarthy, Kevin F.; Valdez, R. Burciaga

This study to assess the current situation of Mexican immigrants in California and project future possibilities constructs a demographic profile of the immigrants, examines their economic effects on the state, and describes their socioeconomic integration into California society. Models of immigration/integration processes are developed and used…

Generation of a modeling and simulation system for a semi-closed plant growth chamber

NASA Technical Reports Server (NTRS)

Blackwell, A. L.; Maa, S.; Kliss, M.; Blackwell, C. C.

1993-01-01

The fluid and thermal dynamics of the environment of plants in a small controlled-environment system have been modeled. The results of the simulation under two scenarios have been compared to measurements taken during tests on the actual system. The motivation for the modeling effort and the status of the modeling exercise and system scenario studies are described. An evaluation of the model and a discussion of future studies are included.

Collective motion of predictive swarms

PubMed Central

Vural, Dervis Can

2017-01-01

Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small. PMID:29065136

Collective motion of predictive swarms.

PubMed

Rupprecht, Nathaniel; Vural, Dervis Can

2017-01-01

Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small.

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.

Alternative futures of proactive tools for a citizen's own wellbeing.

PubMed

Meristö, Tarja; Tuohimaa, Hanna; Leppimäki, Sami; Laitinen, Jukka

2009-01-01

The aim of this paper is to create the basis for a vision of an empowered citizen who can control his/her life, especially in relation to health and personal wellbeing with the use of new ICT-tools. The methods used in the study are based on futures studies, especially on scenario methodology. Alternative future paths, i.e. scenarios are constructed using the scenario filter model that we have developed, with market, technology and society perspectives. Scenarios not resulting in the vision are described in what if - analysis as well. The scenarios are combined with Viherä's model on citizen's skills, access and motivation to use new ICT-tools. The concept COPER is targeted to different user groups with an adaptable user interface and its development is user centered. We will consider the effects and the appropriate elements of COPER in every scenario, as well as the possibilities and challenges nursing will confront. As a result we will gain information of the characteristic of COPER that advance the vision. For the future development of COPER the alternative scenarios give the basis for flexibility planning, too.

Large scale structures in the kinetic gravity braiding model that can be unbraided

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

Kimura, Rampei; Yamamoto, Kazuhiro, E-mail: rampei@theo.phys.sci.hiroshima-u.ac.jp, E-mail: kazuhiro@hiroshima-u.ac.jp

2011-04-01

We study cosmological consequences of a kinetic gravity braiding model, which is proposed as an alternative to the dark energy model. The kinetic braiding model we study is characterized by a parameter n, which corresponds to the original galileon cosmological model for n = 1. We find that the background expansion of the universe of the kinetic braiding model is the same as the Dvali-Turner's model, which reduces to that of the standard cold dark matter model with a cosmological constant (ΛCDM model) for n equal to infinity. We also find that the evolution of the linear cosmological perturbation inmore » the kinetic braiding model reduces to that of the ΛCDM model for n = ∞. Then, we focus our study on the growth history of the linear density perturbation as well as the spherical collapse in the nonlinear regime of the density perturbations, which might be important in order to distinguish between the kinetic braiding model and the ΛCDM model when n is finite. The theoretical prediction for the large scale structure is confronted with the multipole power spectrum of the luminous red galaxy sample of the Sloan Digital Sky survey. We also discuss future prospects of constraining the kinetic braiding model using a future redshift survey like the WFMOS/SuMIRe PFS survey as well as the cluster redshift distribution in the South Pole Telescope survey.« less

How obstacles and facilitators predict academic performance: the mediating role of study burnout and engagement.

PubMed

Salanova, Marisa; Schaufeli, Wilmar; Martinez, Isabel; Breso, Edgar

2010-01-01

Most people would agree with the maxim that "success breeds success." However, this is not the whole story. The current study investigated the additional impact of psychosocial factors (i.e., performance obstacles and facilitators) as well as psychological well-being (i.e., burnout and engagement) on success (i.e., academic performance). More specifically, our purpose was to show that, instead of directly affecting future performance, obstacles and facilitators exert an indirect effect via well-being. A total of 527 university students comprised the sample and filled out a questionnaire. We obtained their previous and future academic performance Grade Point Average (GPA) from the university's records. Structural equations modeling showed that the best predictor of future performance was the students' previous performance. As expected, study engagement mediated the relationship between performance obstacles and facilitators on the one hand, and future performance on the other. Contrary to expectations, burnout did not predict future performance, although, it is significantly associated with the presence of obstacles and the absence of facilitators. Our results illustrate that, although "success breeds success" (i.e., the best predictor of future performance is past performance), positive psychological states like study engagement are also important in explaining future performance, at least more so than negative states like study burnout.

Surface Nitrification: A Major Uncertainty in Marine N2O Emissions

NASA Technical Reports Server (NTRS)

Zamora, Lauren M.; Oschlies, Andreas

2014-01-01

The ocean is responsible for up to a third of total global nitrous oxide (N2O) emissions, but uncertainties in emission rates of this potent greenhouse gas are high (approaching 100%). Here we use a marine biogeochemical model to assess six major uncertainties in estimates of N2O production, thereby providing guidance in how future studies may most effectively reduce uncertainties in current and future marine N2O emissions. Potential surface N2O production from nitrification causes the largest uncertainty in N2O emissions (estimated up to approximately 1.6 Tg N/yr (sup -1) or 48% of modeled values), followed by the unknown oxygen concentration at which N2O production switches to N2O consumption (0.8 Tg N/yr (sup -1)or 24% of modeled values). Other uncertainties are minor, cumulatively changing regional emissions by less than 15%. If production of N2O by surface nitrification could be ruled out in future studies, uncertainties in marine N2O emissions would be halved.

Optimism/pessimism and future orientation as predictors of suicidal ideation: Are there ethnic differences?

PubMed

Yu, Elizabeth A; Chang, Edward C

2016-10-01

The present study sought to test the generalizability of Chang et al.'s (2013) model, which suggests that optimism/pessimism and future orientation function as additive and interactive predictors of suicidal risk, to specific ethnic minority college student groups (i.e., Asian Americans, African Americans, and Latino Americans). The present study used Chang et al.'s (2013) model to predict suicidal ideation among 81 (34 male and 47 female) Asian-American, 71 (22 male and 49 female) African-American adults, and 83 (34 male and 49 female) Latino-American college students. Our results indicated that this model did not predict suicidal ideation well for Asian-American college students; however, it did work well to predict suicidal ideation for African-American and Latino-American college students. Our findings indicate that optimism/pessimism and future orientation are important positive cognitions involved with suicidal ideation for African-American and Latino-American college students. Further research is needed to better understand the cultural underpinnings of how these positive cognitions work to predict suicide-related outcomes. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Associations Among Individuals' Perceptions of Future Time, Individual Resources, and Subjective Well-Being in Old Age.

PubMed

Hoppmann, Christiane A; Infurna, Frank J; Ram, Nilam; Gerstorf, Denis

2017-05-01

Perceptions of future time are of key interest to aging research because of their implications for subjective well-being. Interestingly, perceptions about future time are only moderately associated with age when looking at the second half of life, pointing to a vast heterogeneity in future time perceptions among older adults. We examine associations between future time perceptions, age, and subjective well-being across two studies, including moderations by individual resources. Using data from the Berlin Aging Study (N = 516; Mage = 85 years), we link one operationalization (subjective nearness to death) and age to subjective well-being. Using Health and Retirement Study data (N = 2,596; Mage = 77 years), we examine associations of another future time perception indicator (subjective future life expectancy) and age with subjective well-being. Consistent across studies, perceptions of limited time left were associated with poorer subjective well-being (lower life satisfaction and positive affect; more negative affect and depressive symptoms). Importantly, individual resources moderated future time perception-subjective well-being associations with those of better health exhibiting reduced future time perception-subjective well-being associations. We discuss our findings in the context of the Model of Strength and Vulnerability Integration. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The Theory of Planned Behavior as a Model of Heavy Episodic Drinking Among College Students

PubMed Central

Collins, Susan E.; Carey, Kate B.

2008-01-01

This study provided a simultaneous, confirmatory test of the theory of planned behavior (TPB) in predicting heavy episodic drinking (HED) among college students. It was hypothesized that past HED, drinking attitudes, subjective norms and drinking refusal self-efficacy would predict intention, which would in turn predict future HED. Participants consisted of 131 college drinkers (63% female) who reported having engaged in HED in the previous two weeks. Participants were recruited and completed questionnaires within the context of a larger intervention study (see Collins & Carey, 2005). Latent factor structural equation modeling was used to test the ability of the TPB to predict HED. Chi-square tests and fit indices indicated good fit for the final structural models. Self-efficacy and attitudes but not subjective norms significantly predicted baseline intention, and intention and past HED predicted future HED. Contrary to hypotheses, however, a structural model excluding past HED provided a better fit than a model including it. Although further studies must be conducted before a definitive conclusion is reached, a TPB model excluding past behavior, which is arguably more parsimonious and theory driven, may provide better prediction of HED among college drinkers than a model including past behavior. PMID:18072832

Investigation of Climate Change Impact on Water Resources for an Alpine Basin in Northern Italy: Implications for Evapotranspiration Modeling Complexity

PubMed Central

Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco

2014-01-01

Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required beacause of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied. PMID:25285917

Investigation of climate change impact on water resources for an Alpine basin in northern Italy: implications for evapotranspiration modeling complexity.

PubMed

Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco

2014-01-01

Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required because of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied.

Model learning for robot control: a survey.

PubMed

Nguyen-Tuong, Duy; Peters, Jan

2011-11-01

Models are among the most essential tools in robotics, such as kinematics and dynamics models of the robot's own body and controllable external objects. It is widely believed that intelligent mammals also rely on internal models in order to generate their actions. However, while classical robotics relies on manually generated models that are based on human insights into physics, future autonomous, cognitive robots need to be able to automatically generate models that are based on information which is extracted from the data streams accessible to the robot. In this paper, we survey the progress in model learning with a strong focus on robot control on a kinematic as well as dynamical level. Here, a model describes essential information about the behavior of the environment and the influence of an agent on this environment. In the context of model-based learning control, we view the model from three different perspectives. First, we need to study the different possible model learning architectures for robotics. Second, we discuss what kind of problems these architecture and the domain of robotics imply for the applicable learning methods. From this discussion, we deduce future directions of real-time learning algorithms. Third, we show where these scenarios have been used successfully in several case studies.

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 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.

Expected changes in future agro-climatological conditions in Northeast Thailand and their differences between general circulation models

NASA Astrophysics Data System (ADS)

Masaki, Yoshimitsu; Ishigooka, Yasushi; Kuwagata, Tsuneo; Goto, Shinkichi; Sawano, Shinji; Hasegawa, Toshihiro

2011-12-01

We have studied future changes in the atmospheric and hydrological environments in Northeast Thailand from the viewpoint of risk assessment of future cultural environments in crop fields. To obtain robust and reliable estimation for future climate, ten general circulation models under three warming scenarios, B1, A1B, and A2, were used in this study. The obtained change trends show that daily maximum air temperature and precipitation will increase by 2.6°C and 4.0%, respectively, whereas soil moisture will decrease by c.a. 1% point in volumetric water content at the end of this century under the A1B scenario. Seasonal contrasts in precipitation will intensify: precipitation increases in the rainy season and precipitation decreases in the dry season. Soil moisture will slightly decrease almost throughout the year. Despite a homogeneous increase in the air temperature over Northeast Thailand, a future decrease in soil water content will show a geographically inhomogeneous distribution: Soil will experience a relative larger decrease in wetness at a shallow depth on the Khorat plateau than in the surrounding mountainous area, reflecting vegetation cover and soil texture. The predicted increase in air temperature is relatively consistent between general circulation models. In contrast, relatively large intermodel differences in precipitation, especially in long-term trends, produce unwanted bias errors in the estimation of other hydrological elements, such as soil moisture and evaporation, and cause uncertainties in projection of the agro-climatological environment. Offline hydrological simulation with a wide precipitation range is one strategy to compensate for such uncertainties and to obtain reliable risk assessment of future cultural conditions in rainfed paddy fields in Northeast Thailand.

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.

Competing effects of groundwater withdrawals and climate change on water availability in semi-arid India

NASA Astrophysics Data System (ADS)

Sishodia, R. P.; Shukla, S.

2017-12-01

India, a global leader in groundwater use (250 km3/yr), is experiencing groundwater depletion. There has been a 130-fold increase in number of irrigation wells since 1960. Anticipated future increase in groundwater demand is likely to exacerbate the water availability in the semi-arid regions of India. Depending on the direction of change, future climate change may either worsen or enhance the water availability. This study uses an integrated hydrologic modeling approach (MIKE SHE MIKE 11) to compare and combine the effects of future (2040-2069) increased groundwater withdrawals and climate change on surface and groundwater flows and availability for an agricultural watershed in semi-arid south India. Modeling results showed that increased groundwater withdrawals in the future resulted in reduced surface flows (25%) and increased frequency and duration (90 days/yr) of well drying. In contrast, projected future increase in rainfall (7-43%) under the changed climate showed increased groundwater recharge (15-67%) and surface flows (9-155%). Modeling results suggest that the positive effects of climate change may enhance the water availability in this semi-arid region of India. However, in combination with increased withdrawals, climate change was shown to increase the well drying and reduce the water availability especially during dry years. A combination of management options such as flood to drip conversion, energy subsidy reductions and water storage can support increased groundwater irrigated area in the future while mitigating the well drying. A cost-benefit analysis showed that dispersed water storage and flood to drip conversion can be highly cost-effective in this semi-arid region. The study results suggest that the government and management policies need to be focused towards an integrated management of demand and supply to create a sustainable food-water-energy nexus in the region.

Persistent cold air outbreaks over North America in a warming climate

DOE PAGES

Gao, Yang; Leung, L. Ruby; Lu, Jian; ...

2015-03-30

This study examines future changes of cold air outbreaks (CAO) using a multi-model ensemble of global climate simulations from the Coupled Model Intercomparison Project Phase 5 as well as regional high resolution climate simulations. In the future, while robust decrease of CAO duration dominates in most regions, the magnitude of decrease over northwestern U.S. is much smaller than the surrounding regions. We identified statistically significant increases in sea level pressure during CAO events centering over Yukon, Alaska, and Gulf of Alaska that advects continental cold air to northwestern U.S., leading to blocking and CAO events. Changes in large scale circulationmore » contribute to about 50% of the enhanced sea level pressure anomaly conducive to CAO in northwestern U.S. in the future. High resolution regional simulations revealed potential contributions of increased existing snowpack to increased CAO in the near future over the Rocky Mountain, southwestern U.S., and Great Lakes areas through surface albedo effects, despite winter mean snow water equivalent decreases in the future. Overall, the multi-model projections emphasize that cold extremes do not completely disappear in a warming climate. Concomitant with the relatively smaller reduction in CAO events in northwestern U.S., the top 5 most extreme CAO events may still occur in the future, and wind chill warning will continue to have societal impacts in that region.« less

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.

Nanotoxicity prediction using computational modelling - review and future directions

NASA Astrophysics Data System (ADS)

Saini, Bhavna; Srivastava, Sumit

2018-04-01

Nanomaterials has stimulated various outlooks for future in a number of industries and scientific ventures. A number of applications such as cosmetics, medicines, and electronics are employing nanomaterials due to their various compelling properties. The unending growth of nanomaterials usage in our daily life has escalated the health and environmental risks. Early nanotoxicity recognition is a big challenge. Various researches are going on in the field of nanotoxicity, which comprised of several problems such as inadequacy of proper datasets, lack of appropriate rules and characterization of nanomaterials. Computational modelling would be beneficial asset for nanomaterials researchers because it can foresee the toxicity, rest on previous experimental data. In this study, we have reviewed sufficient work demonstrating a proper pathway to proceed with QSAR analysis of Nanomaterials for toxicity modelling. The paper aims at providing comprehensive insight of Nano QSAR, various theories, tools and approaches used, along with an outline for future research directions to work on.

New methods in hydrologic modeling and decision support for culvert flood risk under climate change

NASA Astrophysics Data System (ADS)

Rosner, A.; Letcher, B. H.; Vogel, R. M.; Rees, P. S.

2015-12-01

Assessing culvert flood vulnerability under climate change poses an unusual combination of challenges. We seek a robust method of planning for an uncertain future, and therefore must consider a wide range of plausible future conditions. Culverts in our case study area, northwestern Massachusetts, USA, are predominantly found in small, ungaged basins. The need to predict flows both at numerous sites and under numerous plausible climate conditions requires a statistical model with low data and computational requirements. We present a statistical streamflow model that is driven by precipitation and temperature, allowing us to predict flows without reliance on reference gages of observed flows. The hydrological analysis is used to determine each culvert's risk of failure under current conditions. We also explore the hydrological response to a range of plausible future climate conditions. These results are used to determine the tolerance of each culvert to future increases in precipitation. In a decision support context, current flood risk as well as tolerance to potential climate changes are used to provide a robust assessment and prioritization for culvert replacements.

A top-down approach to projecting market impacts of climate change

NASA Astrophysics Data System (ADS)

Lemoine, Derek; Kapnick, Sarah

2016-01-01

To evaluate policies to reduce greenhouse-gas emissions, economic models require estimates of how future climate change will affect well-being. So far, nearly all estimates of the economic impacts of future warming have been developed by combining estimates of impacts in individual sectors of the economy. Recent work has used variation in warming over time and space to produce top-down estimates of how past climate and weather shocks have affected economic output. Here we propose a statistical framework for converting these top-down estimates of past economic costs of regional warming into projections of the economic cost of future global warming. Combining the latest physical climate models, socioeconomic projections, and economic estimates of past impacts, we find that future warming could raise the expected rate of economic growth in richer countries, reduce the expected rate of economic growth in poorer countries, and increase the variability of growth by increasing the climate's variability. This study suggests we should rethink the focus on global impacts and the use of deterministic frameworks for modelling impacts and policy.

Potential impact of climate change to the future streamflow of Yellow River Basin based on CMIP5 data

NASA Astrophysics Data System (ADS)

Yang, Xiaoli; Zheng, Weifei; Ren, Liliang; Zhang, Mengru; Wang, Yuqian; Liu, Yi; Yuan, Fei; Jiang, Shanhu

2018-02-01

The Yellow River Basin (YRB) is the largest river basin in northern China, which has suffering water scarcity and drought hazard for many years. Therefore, assessments the potential impacts of climate change on the future streamflow in this basin is very important for local policy and planning on food security. In this study, based on the observations of 101 meteorological stations in YRB, equidistant CDF matching (EDCDFm) statistical downscaling approach was applied to eight climate models under two emissions scenarios (RCP4.5 and RCP8.5) from phase five of the Coupled Model Intercomparison Project (CMIP5). Variable infiltration capacity (VIC) model with 0.25° × 0.25° spatial resolution was developed based on downscaled fields for simulating streamflow in the future period over YRB. The results show that with the global warming trend, the annual streamflow will reduced about 10 % during the period of 2021-2050, compared to the base period of 1961-1990 in YRB. There should be suitable water resources planning to meet the demands of growing populations and future climate changing in this region.

Impacts of boundary condition changes on regional climate projections over West Africa

NASA Astrophysics Data System (ADS)

Kim, Jee Hee; Kim, Yeonjoo; Wang, Guiling

2017-06-01

Future projections using regional climate models (RCMs) are driven with boundary conditions (BCs) typically derived from global climate models. Understanding the impact of the various BCs on regional climate projections is critical for characterizing their robustness and uncertainties. In this study, the International Center for Theoretical Physics Regional Climate Model Version 4 (RegCM4) is used to investigate the impact of different aspects of boundary conditions, including lateral BCs and sea surface temperature (SST), on projected future changes of regional climate in West Africa, and BCs from the coupled European Community-Hamburg Atmospheric Model 5/Max Planck Institute Ocean Model are used as an example. Historical, future, and several sensitivity experiments are conducted with various combinations of BCs and CO2 concentration, and differences among the experiments are compared to identify the most important drivers for RCMs. When driven by changes in all factors, the RegCM4-produced future climate changes include significantly drier conditions in Sahel and wetter conditions along the Guinean coast. Changes in CO2 concentration within the RCM domain alone or changes in wind vectors at the domain boundaries alone have minor impact on projected future climate changes. Changes in the atmospheric humidity alone at the domain boundaries lead to a wetter Sahel due to the northward migration of rain belts during summer. This impact, although significant, is offset and dominated by changes of other BC factors (primarily temperature) that cause a drying signal. Future changes of atmospheric temperature at the domain boundaries combined with SST changes over oceans are sufficient to cause a future climate that closely resembles the projection that accounts for all factors combined. Therefore, climate variability and changes simulated by RCMs depend primarily on the variability and change of temperature aspects of the RCM BCs. Moreover, it is found that the response of the RCM climate to different climate change factors is roughly linear in that the projected changes driven by combined factors are close to the sum of projected changes due to each individual factor alone at least for long-term averages. Findings from this study are important for understanding the source(s) of uncertainties in regional climate projections and for designing innovative approaches to climate downscaling and impact assessment.

A sensor fusion field experiment in forest ecosystem dynamics

NASA Technical Reports Server (NTRS)

Smith, James A.; Ranson, K. Jon; Williams, Darrel L.; Levine, Elissa R.; Goltz, Stewart M.

1990-01-01

The background of the Forest Ecosystem Dynamics field campaign is presented, a progress report on the analysis of the collected data and related modeling activities is provided, and plans for future experiments at different points in the phenological cycle are outlined. The ecological overview of the study site is presented, and attention is focused on forest stands, needles, and atmospheric measurements. Sensor deployment and thermal and microwave observations are discussed, along with two examples of the optical radiation measurements obtained during the experiment in support of radiative transfer modeling. Future activities pertaining to an archival system, synthetic aperture radar, carbon acquisition modeling, and upcoming field experiments are considered.

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).

A stakeholder project to model water temperature under future climate scenarios in the Satus and Toppenish watersheds of the Yakima River Basinin Washington, USA

USGS Publications Warehouse

Graves, D.; Maule, A.

2014-01-01

The goal of this study was to support an assessment of the potential effects of climate change on select natural, social, and economic resources in the Yakima River Basin. A workshop with local stakeholders highlighted the usefulness of projecting climate change impacts on anadromous steelhead (Oncorhynchus mykiss), a fish species of importance to local tribes, fisherman, and conservationists. Stream temperature is an important environmental variable for the freshwater stages of steelhead. For this study, we developed water temperature models for the Satus and Toppenish watersheds, two of the key stronghold areas for steelhead in the Yakima River Basin. We constructed the models with the Stream Network Temperature Model (SNTEMP), a mechanistic approach to simulate water temperature in a stream network. The models were calibrated over the April 15, 2008 to September 30, 2008 period and validated over the April 15, 2009 to September 30, 2009 period using historic measurements of stream temperature and discharge provided by the Yakama Nation Fisheries Resource Management Program. Once validated, the models were run to simulate conditions during the spring and summer seasons over a baseline period (1981–2005) and two future climate scenarios with increased air temperature of 1°C and 2°C. The models simulated daily mean and maximum water temperatures at sites throughout the two watersheds under the baseline and future climate scenarios.

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.

Evaluating characteristics of dry spell changes in Lake Urmia Basin using an ensemble CMIP5 GCM models

NASA Astrophysics Data System (ADS)

Fazel, Nasim; Berndtsson, Ronny; Bertacchi Uvo, Cintia; Klove, Bjorn; Madani, Kaveh

2015-04-01

Drought is a natural phenomenon that can cause significant environmental, ecological, and socio-economic losses in water scarce regions. Studies of drought under climate change are essential for water resources planning and management. Dry spells and number of consecutive days with precipitation below a certain threshold can be used to identify the severity of hydrological drought. In this study, we analyzed the projected changes of number of dry days in two future periods, 2011-2040 and 2071-2100, for both seasonal and annual time scales in the Lake Urmia Basin. The lake and its wetlands, located in northwestern Iran, have invaluable environmental, social, and economic importance for the region. The lake level has been shrinking dramatically since 1995 and now the water volume is less than 30% of its original. Moreover, frequent dry spells have struck the region and effected the region's water resources and lake ecosystem as in other parts of Iran too. Analyzing future drought and dry spells characteristics in the region is crucial for sustainable water management and lake restoration plans. We used daily projected precipitation from 20 climate models used in the CMIP5 (Coupled Model Inter-comparison Project Phase 5) driven by three representative paths, RCP2.6, RCP4.5, and, RCP8.5. The model outputs were statistically downscaled and validated based on the historical observation period 1980-2010. We defined days with precipitation less than 1 mm as dry days for both observation periods and model projections. The model validation showed that all models underestimated the number of dry days. An ensemble based on the validation results consisting of five models which were in best agreement with observations was used to assess the changes in number of future dry days in Lake Urmia Basin. The entire ensemble showed increase in number of dry days for all seasons. The projected changes in winter and spring were larger than for summer and autumn. All models projected dryer winter and spring periods in the near and far future periods. The ensemble mean for future annual dry days increased by 6.5 % to 7.3% for the different climate change related emission and concentration pathway RCP2.6, RCP4.5, and, RCP8.5.

Determining the Current and Future Health of Low-Latitude Andean Glaciers Using an Equilibrium Line Altitude Model and Hypsometric Data from the Randolph Glacier Inventory

NASA Astrophysics Data System (ADS)

Malone, A.; MacAyeal, D. R.

2015-12-01

Mountain glaciers have been described as the water towers of world, and for many populations in the low-latitude South American Andes, glacial runoff is vital for agricultural, industrial, and basic water needs. Previous studies of low-latitude Andean glaciers suggest a precarious future due to contemporary warming. These studies have looked at trends in freezing level heights or observations of contemporary retreat. However, regional-scale understanding of low-latitude glacial responses to present and future climate change is limited, in part due to incomplete information about the extent and elevation distribution of low-latitude glaciers. The recently published Randolph Glacier Inventory (RGI) (5.0) provides the necessary information about the size and elevation distribution of low-latitude glaciers to begin such studies. We determine the contemporary equilibrium line altitudes (ELAs) for low-latitude Andean glaciers in the RGI, using a numerical energy balance ablation model driven with reanalysis and gridded data products. Contemporary ELAs tend to fall around the peak of the elevation histogram, with an exception being the southern-most outer tropical glaciers whose modeled ELAs tend to be higher than the elevation histogram for that region (see below figure). Also, we use the linear tends in temperature and precipitation from the contemporary climatology to extrapolate 21stcentury climate forcings. Modeled ELAs by the middle on the century are universally predicted to rise, with outer tropical ELAs rising more than the inner tropical glaciers. These trends continue through the end of the century. Finally, we explore how climate variables and parameters in our numerical model may vary for different warming scenarios from United Nation's IPCC AR5 report. We quantify the impacts of these changes on ELAs for various climate change trajectories. These results support previous work on the precarious future of low latitude Andean glaciers, while providing a richer understanding of the glacial impacts of contemporary and future warming. Also, this work provides analysis of processes and feedbacks between different climate variables important to glacier mass balances in a warming world, improving predictions for the fate of low-latitude Andean glaciers.

Will Outer Tropical Cyclone Size Change due to Anthropogenic Warming?

NASA Astrophysics Data System (ADS)

Schenkel, B. A.; Lin, N.; Chavas, D. R.; Vecchi, G. A.; Knutson, T. R.; Oppenheimer, M.

2017-12-01

Prior research has shown significant interbasin and intrabasin variability in outer tropical cyclone (TC) size. Moreover, outer TC size has even been shown to vary substantially over the lifetime of the majority of TCs. However, the factors responsible for both setting initial outer TC size and determining its evolution throughout the TC lifetime remain uncertain. Given these gaps in our physical understanding, there remains uncertainty in how outer TC size will change, if at all, due to anthropogenic warming. The present study seeks to quantify whether outer TC size will change significantly in response to anthropogenic warming using data from a high-resolution global climate model and a regional hurricane model. Similar to prior work, the outer TC size metric used in this study is the radius in which the azimuthal-mean surface azimuthal wind equals 8 m/s. The initial results from the high-resolution global climate model data suggest that the distribution of outer TC size shifts significantly towards larger values in each global TC basin during future climates, as revealed by 1) statistically significant increase of the median outer TC size by 5-10% (p<0.05) according to a 1,000-sample bootstrap resampling approach with replacement and 2) statistically significant differences between distributions of outer TC size from current and future climate simulations as shown using two-sample Kolmogorov Smirnov testing (p<<0.01). Additional analysis of the high-resolution global climate model data reveals that outer TC size does not uniformly increase within each basin in future climates, but rather shows substantial locational dependence. Future work will incorporate the regional mesoscale hurricane model data to help focus on identifying the source of the spatial variability in outer TC size increases within each basin during future climates and, more importantly, why outer TC size changes in response to anthropogenic warming.

Potential impacts of agricultural drought on crop yield variability under a changing climate in Texas

NASA Astrophysics Data System (ADS)

Lee, K.; Leng, G.; Huang, M.; Sheffield, J.; Zhao, G.; Gao, H.

2017-12-01

Texas has the largest farm area in the U.S, and its revenue from crop production ranks third overall. With the changing climate, hydrological extremes such as droughts are becoming more frequent and intensified, causing significant yield reduction in rainfed agricultural systems. The objective of this study is to investigate the potential impacts of agricultural drought on crop yields (corn, sorghum, and wheat) under a changing climate in Texas. The Variable Infiltration Capacity (VIC) model, which is calibrated and validated over 10 major Texas river basins during the historical period, is employed in this study.The model is forced by a set of statistically downscaled climate projections from Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The CMIP5 projections contain four Representative Concentration Pathways (RCP) that represent different greenhouse gas concentration (4.5 and 8.5 w/m2 are selected in this study). To carry out the analysis, VIC simulations from 1950 to 2099 are first analyzed to investigate how the frequency and severity of agricultural droughts will be altered in Texas (under a changing climate). Second, future crop yields are projected using a statistical crop model. Third, the effects of agricultural drought on crop yields are quantitatively analyzed. The results are expected to contribute to future water resources planning, with a goal of mitigating the negative impacts of future droughts on agricultural production in Texas.

Validation of a multifactorial risk factor model used for predicting future caries risk with Nevada adolescents.

PubMed

Ditmyer, Marcia M; Dounis, Georgia; Howard, Katherine M; Mobley, Connie; Cappelli, David

2011-05-20

The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting. This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model. Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%. Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.

Economic Impacts of Climate Change on Winter Tourism: Challenges for Ski Area Operators

NASA Astrophysics Data System (ADS)

Damm, A.; Köberl, J.; Prettenthaler, F.; Töglhofer, C.

2012-04-01

Increasing temperatures and snow scarce winter seasons pose a big challenge for the winter tourism industry. Changing natural snow reliability influences tourism demand and ski area operators are faced with an enhanced need of technical snow production. The goal of the present research work is to analyze the economic effects of technical snow production under future climate conditions. Snowmaking as an adaptation strategy to climate change impacts on the ski tourism industry is already taken into consideration in several studies from a scientific perspective concerning snowmaking potentials under future climate conditions and the impacts on ski season length (e.g. Scott et al. 2003; Scott & McBoyle 2007; Hennessy et al. 2008; Steiger 2010). A few studies considered economic aspects of technical snowmaking (e.g. Teich et al. 2007; Gonseth 2008). However, a detailed analysis of the costs and benefits of snowmaking under future climate and snow conditions based on sophisticated climate and snow models has not been carried out yet. The present study addresses the gap of knowledge concerning the economic profitability of prospective snowmaking requirements under future climate scenarios. We carry out a detailed cost-revenue analysis of snowmaking under current and future climate conditions for a case study site in Styria (Austria) using dynamic investment models. The starting point of all economic calculations is the daily demand for artificial snow that determines the requirements for additional snowmaking investments and additional operating costs. The demand for artificial snow is delivered by the snow cover model AMUNDSEN (see Strasser et al. 2011) and is driven by four climate scenarios. Apart from future climate conditions the profitability of snowmaking depends on changes in costs and visitor numbers. The results of a ski tourism demand model analyzing daily visitor numbers and their dependencies of prevailing weather conditions enter the cost-revenue analysis of snowmaking and enable the determination of the immediate benefits in terms of additional revenues of ski ticket sales. Furthermore, we conduct an econometric analysis of how snowmaking investments changed ski ticket prices in previous years, as the positive effects of snowmaking on snow reliability could be offset in the longer term by the effects of higher prices for skiing, possibly resulting in lower demand.

Water cycle changes over the Mediterranean: a comparison study of a super-high-resolution global model with CMIP3.

PubMed

Jin, Fengjun; Kitoh, Akio; Alpert, Pinhas

2010-11-28

Water cycle components over the Mediterranean for both a current run (1979-2007) and a future run (2075-2099) are studied with the Japan Meteorological Agency's 20 km grid global climate model. Results are compared with another study using the Coupled Model Intercomparison Project Phase 3 ensemble model (hereafter, the Mariotti model). Our results are surprisingly close to Mariotti's. The projected mean annual change rates of precipitation (P) between the future and the current run for sea and land are -11 per cent and -10 per cent, respectively, which are not as high as Mariotti's. Projected changes for evaporation (E) are +9.3 per cent and -3.6 per cent, compared with +7.2 per cent and -8.1 per cent in Mariotti's study, respectively. However, no significant difference in the change in P-E over the sea body was found between these two studies. The increased E over the eastern Mediterranean was found to be higher than that in the western Mediterranean, but the P decrease was lower. The net moisture budget, P-E, shows that the eastern Mediterranean will become even drier than the western Mediterranean. The river model suggests decreasing water inflow to the Mediterranean of approximately 36 per cent (excluding the Nile).

Football with three ‘halves’: A qualitative exploratory study of the football3 model at the Football for Hope Festival 2010

PubMed Central

ZA, Kaufman; MA, Clark; ST, McGarvey

2015-01-01

The “football3” model refers to a restructuring of traditional football/soccer rules to bring social and developmental benefits to participating youth and their communities. The model incorporates three “halves”: pre-game discussion, football match, and post-game discussion. This study was carried out to shed light on the experiences of youth and adults with the football3 model at the Football for Hope Festival 2010. As an official 2010 FIFA World Cup event, the festival assembled 32 mixed-sex delegations of youth for cultural activities and a football tournament. The study's aim was to inform the model's future design and implementation. Twenty interviews, two focus group discussions, and participant observation were conducted. Findings highlight positive experiences with the model regarding cultural exchange and relationship building, Fair Play and social values, and gender integration. Challenges pertain to misunderstanding of the football3 model, tournament atmosphere, and skill level differences. Recommendations centre on systematically formulating desired outcomes, formalizing a curriculum and training plan, piloting football3 in a range of settings over an extended period of time, and emphasizing monitoring and evaluation to assess the model's effectiveness and impact. Future piloting and research should inform the potential scale-up of the model. PMID:27064214

Oxygen Mass Transport in Stented Coronary Arteries.

PubMed

Murphy, Eoin A; Dunne, Adrian S; Martin, David M; Boyle, Fergal J

2016-02-01

Oxygen deficiency, known as hypoxia, in arterial walls has been linked to increased intimal hyperplasia, which is the main adverse biological process causing in-stent restenosis. Stent implantation has significant effects on the oxygen transport into the arterial wall. Elucidating these effects is critical to optimizing future stent designs. In this study the most advanced oxygen transport model developed to date was assessed in two test cases and used to compare three coronary stent designs. Additionally, the predicted results from four simplified blood oxygen transport models are compared in the two test cases. The advanced model showed good agreement with experimental measurements within the mass-transfer boundary layer and at the luminal surface; however, more work is needed in predicting the oxygen transport within the arterial wall. Simplifying the oxygen transport model within the blood flow produces significant errors in predicting the oxygen transport in arteries. This study can be used as a guide for all future numerical studies in this area and the advanced model could provide a powerful tool in aiding design of stents and other cardiovascular devices.

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.

A Prospective Test of Cognitive Vulnerability Models of Depression with Adolescent Girls

ERIC Educational Resources Information Center

Bohon, Cara; Stice, Eric; Burton, Emily; Fudell, Molly; Nolen-Hoeksema, Susan

2008-01-01

This study sought to provide a more rigorous prospective test of two cognitive vulnerability models of depression with longitudinal data from 496 adolescent girls. Results supported the cognitive vulnerability model in that stressors predicted future increases in depressive symptoms and onset of clinically significant major depression for…

Brachypodium as a model for the grasses: today and the future

USDA-ARS?s Scientific Manuscript database

Over the past several years, Brachypodium distachyon (Brachypodium) has emerged as a tractable model system to study biological questions relevant to the grasses. To place its relevance in the larger context of plant biology, we outline here the expanding adoption of Brachypodium as a model grass an...

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...

Quercus pollen season dynamics in the Iberian peninsula: response to meteorological parameters and possible consequences of climate change.

PubMed

Garcia-Mozo, Herminia; Galan, Carmen; Jato, Victoria; Belmonte, Jordina; de la Guardia, Consuelo; Fernandez, Delia; Gutierrez, Montserrat; Aira, M; Roure, Joan; Ruiz, Luis; Trigo, Mar; Dominguez-Vilches, Eugenio

2006-01-01

The main characteristics of the Quercus pollination season were studied in 14 different localities of the Iberian Peninsula from 1992-2004. Results show that Quercus flowering season has tended to start earlier in recent years, probably due to the increased temperatures in the pre-flowering period, detected at study sites over the second half of the 20th century. A Growing Degree Days forecasting model was used, together with future meteorological data forecast using the Regional Climate Model developed by the Hadley Meteorological Centre, in order to determine the expected advance in the start of Quercus pollination in future years. At each study site, airborne pollen curves presented a similar pattern in all study years, with different peaks over the season attributable in many cases to the presence of several species. High pollen concentrations were recorded, particularly at Mediterranean sites. This study also proposes forecasting models to predict both daily pollen values and annual pollen emission. All models were externally validated using data for 2001 and 2004, with acceptable results. Finally, the impact of the highly-likely climate change on Iberian Quercus pollen concentration values was studied by applying RCM meteorological data for different future years, 2025, 2050, 2075 and 2099. Results indicate that under a doubled CO(2) scenario at the end of the 21st century Quercus pollination season could start on average one month earlier and airborne pollen concentrations will increase by 50 % with respect to current levels, with higher values in Mediterranean inland areas.

Experimental design for three interrelated marine ice sheet and ocean model intercomparison projects: MISMIP v. 3 (MISMIP +), ISOMIP v. 2 (ISOMIP +) and MISOMIP v. 1 (MISOMIP1)

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

Asay-Davis, Xylar S.; Cornford, Stephen L.; Durand, Gaël

Coupled ice sheet-ocean models capable of simulating moving grounding lines are just becoming available. Such models have a broad range of potential applications in studying the dynamics of marine ice sheets and tidewater glaciers, from process studies to future projections of ice mass loss and sea level rise. The Marine Ice Sheet-Ocean Model Intercomparison Project (MISOMIP) is a community effort aimed at designing and coordinating a series of model intercomparison projects (MIPs) for model evaluation in idealized setups, model verification based on observations, and future projections for key regions of the West Antarctic Ice Sheet (WAIS). Here we describe computationalmore » experiments constituting three interrelated MIPs for marine ice sheet models and regional ocean circulation models incorporating ice shelf cavities. These consist of ice sheet experiments under the Marine Ice Sheet MIP third phase (MISMIP+), ocean experiments under the Ice Shelf-Ocean MIP second phase (ISOMIP+) and coupled ice sheet-ocean experiments under the MISOMIP first phase (MISOMIP1). All three MIPs use a shared domain with idealized bedrock topography and forcing, allowing the coupled simulations (MISOMIP1) to be compared directly to the individual component simulations (MISMIP+ and ISOMIP+). The experiments, which have qualitative similarities to Pine Island Glacier Ice Shelf and the adjacent region of the Amundsen Sea, are designed to explore the effects of changes in ocean conditions, specifically the temperature at depth, on basal melting and ice dynamics. In future work, differences between model results will form the basis for the evaluation of the participating models.« less

Changes in groundwater recharge under projected climate in the upper Colorado River basin

USGS Publications Warehouse

Tillman, Fred; Gangopadhyay, Subhrendu; Pruitt, Tom

2016-01-01

Understanding groundwater-budget components, particularly groundwater recharge, is important to sustainably manage both groundwater and surface water supplies in the Colorado River basin now and in the future. This study quantifies projected changes in upper Colorado River basin (UCRB) groundwater recharge from recent historical (1950–2015) through future (2016–2099) time periods, using a distributed-parameter groundwater recharge model with downscaled climate data from 97 Coupled Model Intercomparison Project Phase 5 climate projections. Simulated future groundwater recharge in the UCRB is generally expected to be greater than the historical average in most decades. Increases in groundwater recharge in the UCRB are a consequence of projected increases in precipitation, offsetting reductions in recharge that would result from projected increased temperatures.

Future Climate Change Impacts on Surface Hydrology over Texas River Basins

NASA Astrophysics Data System (ADS)

Lee, K.; Gao, H.; Huang, M.; Sheffield, J.

2014-12-01

Future freshwater availability is a pressing issue in Texas due to frequent drought events and fast population growth. Even though the science community has well investigated future temperature trends, it is still unclear whether precipitation will increase or decrease in this region. Furthermore, there is a lack of understanding on how the changing climate will affect water resources across different spatial-temporal scales. This study aims to quantify the impacts of climate change on surface hydrology at the basin scale under different future emission scenarios. The Variable Infiltration Capacity (VIC) model, forced by an ensemble of statistically downscaled climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) models, is employed to predict the future hydrology. The VIC model parameters are adopted from the North American Land Data Assimilation System (NLDAS) at a spatial resolution of 1/8°. The CMIP5 projections contain four different scenarios in terms of Representative Concentration Pathway (RCP) (i.e. 2.6, 4.5, 6.0 and 8.5 w/m2). The analysis is carried out in three steps. First, the observed streamflows are used to evaluate the performance of VIC simulations forced by CMIP5 models during historical period. Second, VIC outputs under multiple CMIP5 model scenarios from 1950 to 2099 are analyzed to identify how soil moisture, evapotranspiration, runoff, and routed streamflows change in time and space. Third, the spatial patterns of seasonal temperature, seasonal precipitation, and the Palmer Drought Severity Index (PDSI)—over four 20-year periods (1980-1999, 2010-2029, 2040-2059 and 2080-2099)—are used to pinpoint the regions that will be most affected by climate change (among the 13 Texan river basins). Furthermore, the role of groundwater in meeting the increasing needs for water supply is discussed. The results are expected to contribute to various future water resources management decisions in Texas.

Current and future background ozone simulations for Mexico using a multi-scale regional climate modeling system

NASA Astrophysics Data System (ADS)

Lamb, B. K.; Gonzalez Abraham, R.; Avise, J. C.; Chung, S. H.; Salathe, E. P.; Zhang, Y.; Guenther, A. B.; Wiedinmyer, C.; Duhl, T.; Streets, D. G.

2013-05-01

Global change will clearly have a significant impact on the environment. Among the concerns for future air quality in North America, intercontinental transport of pollution has become increasingly important. In this study, we examined the effect of projected changes in Asian emissions and emissions from lightning and wildfires to produce ozone background concentrations within Mexico and the continental US. This provides a basis for developing an understanding of North American background levels and how they may change in the future. Meteorological fields were downscaled from the results of the ECHAM5 global climate model using the Weather Research Forecast (WRF) model. Two nested domains were employed, one covering most of the Northern Hemisphere from eastern Asia to North America using 220 km grid cells (semi-hemispheric domain) and one covering the continental US and northern Mexico using 36 km grid cells. Meteorological results from WRF were used to drive the MEGAN biogenic emissions model, the SMOKE emissions processing tool, and the CMAQ chemical transport model to predict ozone concentrations for current (1995-2004) and future (2045-2054) summertime conditions. The MEGAN model was used to calculate biogenic emissions for all simulations. For the semi-hemispheric domain, year 2000 global emissions of gases (ozone precursors) from anthropogenic (outside of North America), natural, and biomass burning sources from the POET and EDGAR emission inventories were used. The global tabulation for black and organic carbon (BC and OC respectively) was obtained from Bond et al. (2004) For the future decade, the current emissions were projected to the year 2050 following the Intergovernmental Panel for Climate Change (IPCC) A1B emission scenario. Anthropogenic emissions from the US, Canada, and Mexico were omitted so that only global background concentrations, and local biogenic, wildfire, and lightning emissions were treated. In this paper, we focus on background ozone levels in Mexico due to changes in future climate, local biogenic emissions and global emissions.

Predictions of future ephemeral springtime waterbird stopover habitat availability under global change

USGS Publications Warehouse

Uden, Daniel R.; Allen, Craig R.; Bishop, Andrew A.; Grosse, Roger; Jorgensen, Christopher F.; LaGrange, Theodore G.; Stutheit, Randy G.; Vrtiska, Mark P.

2015-01-01

In the present period of rapid, worldwide change in climate and landuse (i.e., global change), successful biodiversity conservation warrants proactive management responses, especially for long-distance migratory species. However, the development and implementation of management strategies can be impeded by high levels of uncertainty and low levels of control over potentially impactful future events and their effects. Scenario planning and modeling are useful tools for expanding perspectives and informing decisions under these conditions. We coupled scenario planning and statistical modeling to explain and predict playa wetland inundation (i.e., presence/absence of water) and ponded area (i.e., extent of water) in the Rainwater Basin, an anthropogenically altered landscape that provides critical stopover habitat for migratory waterbirds. Inundation and ponded area models for total wetlands, those embedded in rowcrop fields, and those not embedded in rowcrop fields were trained and tested with wetland ponding data from 2004 and 2006–2009, and then used to make additional predictions under two alternative climate change scenarios for the year 2050, yielding a total of six predictive models and 18 prediction sets. Model performance ranged from moderate to good, with inundation models outperforming ponded area models, and models for non-rowcrop-embedded wetlands outperforming models for total wetlands and rowcrop-embedded wetlands. Model predictions indicate that if the temperature and precipitation changes assumed under our climate change scenarios occur, wetland stopover habitat availability in the Rainwater Basin could decrease in the future. The results of this and similar studies could be aggregated to increase knowledge about the potential spatial and temporal distributions of future stopover habitat along migration corridors, and to develop and prioritize multi-scale management actions aimed at mitigating the detrimental effects of global change on migratory waterbird populations.

Long-term simulations of dissolved oxygen concentrations in Lake Trout lakes

NASA Astrophysics Data System (ADS)

Jabbari, A.; Boegman, L.; MacKay, M.; Hadley, K.; Paterson, A.; Jeziorski, A.; Nelligan, C.; Smol, J. P.

2016-02-01

Lake Trout are a rare and valuable natural resource that are threatened by multiple environmental stressors. With the added threat of climate warming, there is growing concern among resource managers that increased thermal stratification will reduce the habitat quality of deep-water Lake Trout lakes through enhanced oxygen depletion. To address this issue, a three-part study is underway, which aims to: analyze sediment cores to understand the past, develop empirical formulae to model the present and apply computational models to forecast the future. This presentation reports on the computational modeling efforts. To this end, a simple dissolved oxygen sub-model has been embedded in the one-dimensional bulk mixed-layer thermodynamic Canadian Small Lake Model (CSLM). This model is currently being incorporated into the Canadian Land Surface Scheme (CLASS), the primary land surface component of Environment Canada's global and regional climate modelling systems. The oxygen model was calibrated and validated by hind-casting temperature and dissolved oxygen profiles from two Lake Trout lakes on the Canadian Shield. These data sets include 5 years of high-frequency (10 s to 10 min) data from Eagle Lake and 30 years of bi-weekly data from Harp Lake. Initial results show temperature and dissolved oxygen was predicted with root mean square error <1.5 °C and <3 mgL-1, respectively. Ongoing work is validating the model, over climate-change relevant timescales, against dissolved oxygen reconstructions from the sediment cores and predicting future deep-water temperature and dissolved oxygen concentrations in Canadian Lake Trout lakes under future climate change scenarios. This model will provide a useful tool for managers to ensure sustainable fishery resources for future generations.

Role of Internal Variability in Surface Temperature and Precipitation Change Uncertainties over India.

NASA Astrophysics Data System (ADS)

Achutarao, K. M.; Singh, R.

2017-12-01

There are various sources of uncertainty in model projections of future climate change. These include differences in the formulation of climate models, internal variability, and differences in scenarios. Internal variability in a climate system represents the unforced change due to the chaotic nature of the climate system and is considered irreducible (Deser et al., 2012). Internal variability becomes important at regional scales where it can dominate forced changes. Therefore it needs to be carefully assessed in future projections. In this study we segregate the role of internal variability in the future temperature and precipitation projections over the Indian region. We make use of the Coupled Model Inter-comparison Project - phase 5 (CMIP5; Taylor et al., 2012) database containing climate model simulations carried out by various modeling centers around the world. While the CMIP5 experimental protocol recommended producing numerous ensemble members, only a handful of the modeling groups provided multiple realizations. Having a small number of realizations is a limitation in producing a quantification of internal variability. We therefore exploit the Community Earth System Model Large Ensemble (CESM-LE; Kay et al., 2014) dataset which contains a 40 member ensemble of a single model- CESM1 (CAM5) to explore the role of internal variability in Future Projections. Surface air temperature and precipitation change projections over regional and sub-regional scale are analyzed under the IPCC emission scenario (RCP8.5) for different seasons and homogeneous climatic zones over India. We analyze the spread in projections due to internal variability in the CESM-LE and CMIP5 datasets over these regions.

A Prospective Test of Cognitive Vulnerability Models of Depression With Adolescent Girls

PubMed Central

Bohon, Cara; Stice, Eric; Burton, Emily; Fudell, Molly; Nolen-Hoeksema, Susan

2009-01-01

This study sought to provide a more rigorous prospective test of two cognitive vulnerability models of depression with longitudinal data from 496 adolescent girls. Results supported the cognitive vulnerability model in that stressors predicted future increases in depressive symptoms and onset of clinically significant major depression for individuals with a negative attributional style, but not for those with a positive attributional style, although these effects were small. This model appeared to be specific to depression, in that it did not predict future increases in bulimia nervosa or substance abuse symptoms. In contrast, results did not support the integrated cognitive vulnerability self-esteem model that asserts stressors should only predict increased depression for individuals with a confluence of negative attributional style and low self-esteem, and this model did not appear to be specific to depression. PMID:18328873

Simulated hydrologic response to climate change during the 21st century in New Hampshire

USGS Publications Warehouse

Bjerklie, David M.; Sturtevant, Luke P.

2018-01-24

The U.S. Geological Survey, in cooperation with the New Hampshire Department of Environmental Services and the Department of Health and Human Services, has developed a hydrologic model to assess the effects of short- and long-term climate change on hydrology in New Hampshire. This report documents the model and datasets developed by using the model to predict how climate change will affect the hydrologic cycle and provide data that can be used by State and local agencies to identify locations that are vulnerable to the effects of climate change in areas across New Hampshire. Future hydrologic projections were developed from the output of five general circulation models for two future climate scenarios. The scenarios are based on projected future greenhouse gas emissions and estimates of land-use and land-cover change within a projected global economic framework. An evaluation of the possible effect of projected future temperature on modeling of evapotranspiration is summarized to address concerns regarding the implications of the future climate on model parameters that are based on climate variables. The results of the model simulations are hydrologic projections indicating increasing streamflow across the State with large increases in streamflow during winter and early spring and general decreases during late spring and summer. Wide spatial variability in changes to groundwater recharge is projected, with general decreases in the Connecticut River Valley and at high elevations in the northern part of the State and general increases in coastal and lowland areas of the State. In general, total winter snowfall is projected to decrease across the State, but there is a possibility of increasing snow in some locations, particularly during November, February, and March. The simulated future changes in recharge and snowfall vary by watershed across the State. This means that each area of the State could experience very different changes, depending on topography or other factors. Therefore, planning for infrastructure and public safety needs to be flexible in order to address the range of possible outcomes indicated by the various model simulations. The absolute magnitude and timing of the daily streamflows, especially the larger floods, are not considered to be reliably simulated compared to changes in frequency and duration of daily streamflows and changes in accumulated monthly and seasonal streamflow volumes. Simulated current and future streamflow, groundwater recharge, and snowfall datasets include simulated data derived from the five general circulation models used in this study for a current reference time period and two future time periods. Average monthly streamflow time series datasets are provided for 27 streamgages in New Hampshire. Fourteen of the 27 streamgages associated with daily streamflow time series showed a good calibration. Average monthly groundwater recharge and snowfall time series for the same reference time period and two future time periods are also provided for each of the 467 hydrologic response units that compose the model.

Understanding the dynamics in distribution of invasive alien plant species under predicted climate change in Western Himalaya

PubMed Central

Chitale, Vishwas; Rijal, Srijana Joshi; Bisht, Neha; Shrestha, Bharat Babu

2018-01-01

Invasive alien plant species (IAPS) can pose severe threats to biodiversity and stability of native ecosystems, therefore, predicting the distribution of the IAPS plays a crucial role in effective planning and management of ecosystems. In the present study, we use Maximum Entropy (MaxEnt) modelling approach to predict the potential of distribution of eleven IAPS under future climatic conditions under RCP 2.6 and RCP 8.5 in part of Kailash sacred landscape region in Western Himalaya. Based on the model predictions, distribution of most of these invasive plants is expected to expand under future climatic scenarios, which might pose a serious threat to the native ecosystems through competition for resources in the study area. Native scrublands and subtropical needle-leaved forests will be the most affected ecosystems by the expansion of these IAPS. The present study is first of its kind in the Kailash Sacred Landscape in the field of invasive plants and the predictions of potential distribution under future climatic conditions from our study could help decision makers in planning and managing these forest ecosystems effectively. PMID:29664961

Understanding the dynamics in distribution of invasive alien plant species under predicted climate change in Western Himalaya.

PubMed

Thapa, Sunil; Chitale, Vishwas; Rijal, Srijana Joshi; Bisht, Neha; Shrestha, Bharat Babu

2018-01-01

Invasive alien plant species (IAPS) can pose severe threats to biodiversity and stability of native ecosystems, therefore, predicting the distribution of the IAPS plays a crucial role in effective planning and management of ecosystems. In the present study, we use Maximum Entropy (MaxEnt) modelling approach to predict the potential of distribution of eleven IAPS under future climatic conditions under RCP 2.6 and RCP 8.5 in part of Kailash sacred landscape region in Western Himalaya. Based on the model predictions, distribution of most of these invasive plants is expected to expand under future climatic scenarios, which might pose a serious threat to the native ecosystems through competition for resources in the study area. Native scrublands and subtropical needle-leaved forests will be the most affected ecosystems by the expansion of these IAPS. The present study is first of its kind in the Kailash Sacred Landscape in the field of invasive plants and the predictions of potential distribution under future climatic conditions from our study could help decision makers in planning and managing these forest ecosystems effectively.

The Effect of Prosocial Cartoons on Preschool Children

ERIC Educational Resources Information Center

Forge, Karen L. S.; Phemister, Sherri

1987-01-01

Study examined the effect of prosocial cartoons on 40 preschool children. Supported hypothesis that prosocial program models would elicit more prosocial behavior than would neutral program models. Implications for future research on prosocial children's programming were discussed. (Author/RWB)

Global Scale Atmospheric Processes Research Program Review

NASA Technical Reports Server (NTRS)

Worley, B. A. (Editor); Peslen, C. A. (Editor)

1984-01-01

Global modeling; satellite data assimilation and initialization; simulation of future observing systems; model and observed energetics; dynamics of planetary waves; First Global Atmospheric Research Program Global Experiment (FGGE) diagnosis studies; and National Research Council Research Associateship Program are discussed.

Are predictors of future suicide attempts and the transition from suicidal ideation to suicide attempts shared or distinct: a 12-month prospective study among patients with depressive disorders.

PubMed

Chan, Lai Fong; Shamsul, Azhar Shah; Maniam, Thambu

2014-12-30

Our study aimed to examine the interplay between clinical and social predictors of future suicide attempt and the transition from suicidal ideation to suicide attempt in depressive disorders. Sixty-six Malaysian inpatients with a depressive disorder were assessed at index admission and within 1 year for suicide attempt, suicidal ideation, depression severity, life event changes, treatment history and relevant clinical and socio-demographic factors. One-fifth of suicidal ideators transitioned to a future suicide attempt. All future attempters (12/66) had prior ideation and 83% of attempters had a prior attempt. The highest risk for transitioning from ideation to attempt was 5 months post-discharge. Single predictor models showed that previous psychiatric hospitalization and ideation severity were shared predictors of future attempt and ideation to attempt transition. Substance use disorders (especially alcohol) predicted future attempt and approached significance for the transition process. Low socio-economic status predicted the transition process while major personal injury/illness predicted future suicide attempt. Past suicide attempt, subjective depression severity and medication compliance predicted only future suicide attempt. The absence of prior suicide attempt did not eliminate the risk of future attempt. Given the limited sample, future larger studies on mechanisms underlying the interactions of such predictors are needed. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Longitudinal histories as predictors of future diagnoses of domestic abuse: modelling study

PubMed Central

Kohane, Isaac S; Mandl, Kenneth D

2009-01-01

Objective To determine whether longitudinal data in patients’ historical records, commonly available in electronic health record systems, can be used to predict a patient’s future risk of receiving a diagnosis of domestic abuse. Design Bayesian models, known as intelligent histories, used to predict a patient’s risk of receiving a future diagnosis of abuse, based on the patient’s diagnostic history. Retrospective evaluation of the model’s predictions using an independent testing set. Setting A state-wide claims database covering six years of inpatient admissions to hospital, admissions for observation, and encounters in emergency departments. Population All patients aged over 18 who had at least four years between their earliest and latest visits recorded in the database (561 216 patients). Main outcome measures Timeliness of detection, sensitivity, specificity, positive predictive values, and area under the ROC curve. Results 1.04% (5829) of the patients met the narrow case definition for abuse, while 3.44% (19 303) met the broader case definition for abuse. The model achieved sensitive, specific (area under the ROC curve of 0.88), and early (10-30 months in advance, on average) prediction of patients’ future risk of receiving a diagnosis of abuse. Analysis of model parameters showed important differences between sexes in the risks associated with certain diagnoses. Conclusions Commonly available longitudinal diagnostic data can be useful for predicting a patient’s future risk of receiving a diagnosis of abuse. This modelling approach could serve as the basis for an early warning system to help doctors identify high risk patients for further screening. PMID:19789406

Climate change impacts on water availability in the Red River Basin and critical areas for future water conservation

NASA Astrophysics Data System (ADS)

Zamani Sabzi, H.; Moreno, H. A.; Neeson, T. M.; Rosendahl, D. H.; Bertrand, D.; Xue, X.; Hong, Y.; Kellog, W.; Mcpherson, R. A.; Hudson, C.; Austin, B. N.

2017-12-01

Previous periods of severe drought followed by exceptional flooding in the Red River Basin (RRB) have significantly affected industry, agriculture, and the environment in the region. Therefore, projecting how climate may change in the future and being prepared for potential impacts on the RRB is crucially important. In this study, we investigated the impacts of climate change on water availability across the RRB. We used three down-scaled global climate models and three potential greenhouse gas emission scenarios to assess precipitation, temperature, streamflow and lake levels throughout the RRB from 1961 to 2099 at a spatial resolution of 1/10°. Unit-area runoff and streamflow were obtained using the Variable Infiltration Capacity (VIC) model applied across the entire basin. We found that most models predict less precipitation in the western side of the basin and more in the eastern side. In terms of temperature, the models predict that average temperature could increase as much as 6°C. Most models project slightly more precipitation and streamflow values in the future, specifically in the eastern side of the basin. Finally, we analyzed the projected meteorological and hydrologic parameters alongside regional water demand for different sectors to identify the areas on the RRB that will need water-environmental conservation actions in the future. These hotspots of future low water availability are locations where regional environmental managers, water policy makers, and the agricultural and industrial sectors must proactively prepare to deal with declining water availability over the coming decades.

A manpower calculus: the implications of SUO fellowship expansion on oncologic surgeon case volumes.

PubMed

See, William A

2014-01-01

Society of Urologic Oncology (SUO)-accredited fellowship programs have undergone substantial expansion. This study developed a mathematical model to estimate future changes in urologic oncologic surgeon (UOS) manpower and analyzed the effect of those changes on per-UOS case volumes. SUO fellowship program directors were queried as to the number of positions available on an annual basis. Current US UOS manpower was estimated from the SUO membership list. Future manpower was estimated on an annual basis by linear senescence of existing manpower combined with linear growth of newly trained surgeons. Case-volume estimates for the 4 surgical disease sites (prostate, kidney/renal pelvis, bladder, and testes) were obtained from the literature. The future number of major cases was determined from current volumes based upon the US population growth rates and the historic average annual change in disease incidence. Two models were used to predict future per-UOS major case volumes. Model 1 assumed the current distribution of cases between nononcologic surgeons and UOS would continue. Model 2 assumed a progressive redistribution of cases over time such that in 2043 100% of major urologic cancer cases would be performed by UOSs. Over the 30-year period to "manpower steady-state" SUO-accredited UOSs practicing in the United States have the potential to increase from approximately 600 currently to 1,650 in 2043. During this interval, case volumes are predicted to change 0.97-, 2.4-, 1.1-, and 1.5-fold for prostatectomy, nephrectomy, cystectomy, and retroperitoneal lymph node dissection, respectively. The ratio of future to current total annual case volumes is predicted to be 0.47 and 0.9 for models 1 and 2, respectively. The number of annual US practicing graduates necessary to achieve a future to current case-volume ratio greater than 1 is 25 and 49 in models 1 and 2, respectively. The current number of SUO fellowship trainees has the potential to decrease future per-UOS case volumes relative to current levels. Redistribution of existing case volume or a decrease in the annual number of trainees or both would be required to insure sufficient surgical volumes for skill maintenance and optimal patient outcomes. Published by Elsevier Inc.

Future Supply of Pediatric Surgeons: Analytical Study of the Current and Projected Supply of Pediatric Surgeons in the Context of a Rapidly Changing Process for Specialty and Subspecialty Training.

PubMed

Ricketts, Thomas C; Adamson, William T; Fraher, Erin P; Knapton, Andy; Geiger, James D; Abdullah, Fizan; Klein, Michael D

2017-03-01

To describe the future supply and demand for pediatric surgeons using a physician supply model to determine what the future supply of pediatric surgeons will be over the next decade and a half and to compare that projected supply with potential indicators of demand and the growth of other subspecialties. Anticipating the supply of physicians and surgeons in the future has met with varying levels of success. However, there remains a need to anticipate supply given the rapid growth of specialty and subspecialty fellowships. This analysis is intended to support decision making on the size of future fellowships in pediatric surgery. The model used in the study is an adaptation of the FutureDocs physician supply and need tool developed to anticipate future supply and need for all physician specialties. Data from national inventories of physicians by specialty, age, sex, activity, and location are combined with data from residency and fellowship programs and accrediting bodies in an agent-based or microsimulation projection model that considers movement into and among specialties. Exits from practice and the geographic distribution of physician and the patient population are also included in the model. Three scenarios for the annual entry into pediatric surgery fellowships (28, 34, and 56) are modeled and their effects on supply through 2030 are presented. The FutureDocs model predicts a very rapid growth of the supply of surgeons who treat pediatric patients-including general pediatric surgeon and focused subspecialties. The supply of all pediatric surgeons will grow relatively rapidly through 2030 under current conditions. That growth is much faster than the rate of growth of the pediatric population. The volume of complex surgical cases will likely match this population growth rate meaning there will be many more surgeons trained for those procedures. The current entry rate into pediatric surgery fellowships (34 per year) will result in a slowing of growth after 2025, a rate of 56 will generate a continued growth through 2030 with a likely plateau after 2035. The rate of entry into pediatric surgery will continue to exceed population growth through 2030 under two likely scenarios. The very rapid anticipated growth in focused pediatric subspecialties will likely prove challenging to surgeons wishing to maintain their skills with complex cases as a larger and more diverse group of surgeons will also seek to care for many of the conditions and patients which the general pediatric surgeons and general surgeons now see. This means controlling the numbers of pediatric surgery fellowships in a way that recognizes problems with distribution, the volume of cases available to maintain proficiency, and the dynamics of retirement and shifts into other specialty practice.

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.

Computer simulation modeling of recreation use: Current status, case studies, and future directions

Treesearch

David N. Cole

2005-01-01

This report compiles information about recent progress in the application of computer simulation modeling to planning and management of recreation use, particularly in parks and wilderness. Early modeling efforts are described in a chapter that provides an historical perspective. Another chapter provides an overview of modeling options, common data input requirements,...

Direct and Indirect Effects of Parental Influence upon Adolescent Alcohol Use: A Structural Equation Modeling Analysis

ERIC Educational Resources Information Center

Kim, Young-Mi; Neff, James Alan

2010-01-01

A model incorporating the direct and indirect effects of parental monitoring on adolescent alcohol use was evaluated by applying structural equation modeling (SEM) techniques to data on 4,765 tenth-graders in the 2001 Monitoring the Future Study. Analyses indicated good fit of hypothesized measurement and structural models. Analyses supported both…

Comparative Synthesis of Current and Future Urban Stormwater Runoff Scenarios in Tampa Bay Basin under a Changing Climate

NASA Astrophysics Data System (ADS)

Khan, M.; Abdul-Aziz, O. I.

2016-12-01

Changes in climatic regimes and basin characteristics such as imperviousness, roughness and land use types would lead to potential changes in stormwater budget. In this study we quantified reference sensitivities of stormwater runoff to the potential climatic and land use/cover changes by developing a large-scale, mechanistic rainfall-runoff model for the Tampa Bay Basin of Florida using the US EPA Storm Water Management Model (SWMM 5.1). Key processes of urban hydrology, its dynamic interactions with groundwater and sea level, hydro-climatic variables and land use/cover characteristics were incorporated within the model. The model was calibrated and validated with historical streamflow data. We then computed the historical (1970-2000) and potential 2050s stormwater budgets for the Tampa Bay Basin. Climatic scenario projected by the global climate models (GCMs) and the regional climate models (RCMs), along with sea level and land use/cover projections, were utilized to anticipate the future stormwater budget. The comparative assessment of current and future stormwater scenario will aid a proactive management of stormwater runoff under a changing climate in the Tampa Bay Basin and similar urban basins around the world.

Inferring Ice Thickness from a Glacier Dynamics Model and Multiple Surface Datasets.

NASA Astrophysics Data System (ADS)

Guan, Y.; Haran, M.; Pollard, D.

2017-12-01

The future behavior of the West Antarctic Ice Sheet (WAIS) may have a major impact on future climate. For instance, ice sheet melt may contribute significantly to global sea level rise. Understanding the current state of WAIS is therefore of great interest. WAIS is drained by fast-flowing glaciers which are major contributors to ice loss. Hence, understanding the stability and dynamics of glaciers is critical for predicting the future of the ice sheet. Glacier dynamics are driven by the interplay between the topography, temperature and basal conditions beneath the ice. A glacier dynamics model describes the interactions between these processes. We develop a hierarchical Bayesian model that integrates multiple ice sheet surface data sets with a glacier dynamics model. Our approach allows us to (1) infer important parameters describing the glacier dynamics, (2) learn about ice sheet thickness, and (3) account for errors in the observations and the model. Because we have relatively dense and accurate ice thickness data from the Thwaites Glacier in West Antarctica, we use these data to validate the proposed approach. The long-term goal of this work is to have a general model that may be used to study multiple glaciers in the Antarctic.

North Atlantic Tropical Cyclones: historical simulations and future changes with the new high-resolution Arpege AGCM.

NASA Astrophysics Data System (ADS)

Pilon, R.; Chauvin, F.; Palany, P.; Belmadani, A.

2017-12-01

A new version of the variable high-resolution Meteo-France Arpege atmospheric general circulation model (AGCM) has been developed for tropical cyclones (TC) studies, with a focus on the North Atlantic basin, where the model horizontal resolution is 15 km. Ensemble historical AMIP (Atmospheric Model Intercomparison Project)-type simulations (1965-2014) and future projections (2020-2080) under the IPCC (Intergovernmental Panel on Climate Change) representative concentration pathway (RCP) 8.5 scenario have been produced. TC-like vortices tracking algorithm is used to investigate TC activity and variability. TC frequency, genesis, geographical distribution and intensity are examined. Historical simulations are compared to best-track and reanalysis datasets. Model TC frequency is generally realistic but tends to be too high during the rst decade of the historical simulations. Biases appear to originate from both the tracking algorithm and model climatology. Nevertheless, the model is able to simulate extremely well intense TCs corresponding to category 5 hurricanes in the North Atlantic, where grid resolution is highest. Interaction between developing TCs and vertical wind shear is shown to be contributing factor for TC variability. Future changes in TC activity and properties are also discussed.

A first look at the influence of anthropogenic climate change on the future delivery of fluvial sediment to the Ganges-Brahmaputra-Meghna delta.

PubMed

Darby, Stephen E; Dunn, Frances E; Nicholls, Robert J; Rahman, Munsur; Riddy, Liam

2015-09-01

We employ a climate-driven hydrological water balance and sediment transport model (HydroTrend) to simulate future climate-driven sediment loads flowing into the Ganges-Brahmaputra-Meghna (GBM) mega-delta. The model was parameterised using high-quality topographic data and forced with daily temperature and precipitation data obtained from downscaled Regional Climate Model (RCM) simulations for the period 1971-2100. Three perturbed RCM model runs were selected to quantify the potential range of future climate conditions associated with the SRES A1B scenario. Fluvial sediment delivery rates to the GBM delta associated with these climate data sets are projected to increase under the influence of anthropogenic climate change, albeit with the magnitude of the increase varying across the two catchments. Of the two study basins, the Brahmaputra's fluvial sediment load is predicted to be more sensitive to future climate change. Specifically, by the middle part of the 21(st) century, our model results suggest that sediment loads increase (relative to the 1981-2000 baseline period) over a range of between 16% and 18% (depending on climate model run) for the Ganges, but by between 25% and 28% for the Brahmaputra. The simulated increase in sediment flux emanating from the two catchments further increases towards the end of the 21(st) century, reaching between 34% and 37% for the Ganges and between 52% and 60% for the Brahmaputra by the 2090s. The variability in these changes across the three climate change simulations is small compared to the changes, suggesting they represent a significant increase. The new data obtained in this study offer the first estimate of whether and how anthropogenic climate change may affect the delivery of fluvial sediment to the GBM delta, informing assessments of the future sustainability and resilience of one of the world's most vulnerable mega-deltas. Specifically, such significant increases in future sediment loads could increase the resilience of the delta to sea-level rise by giving greater potential for vertical accretion. However, these increased sediment fluxes may not be realised due to uncertainties in the monsoon related response to climate change or other human-induced changes in the catchment: this is a subject for further research.

Impact of climate change on future concentrated solar power (CSP) production

NASA Astrophysics Data System (ADS)

Wild, Martin; Folini, Doris; Henschel, Florian

2017-02-01

Traditionally, for the planning and assessment of solar power plants, the amount of solar radiation incident on the Earth's surface is assumed to be invariable over the years. However, with changing climate and air pollution levels, solar resources may no longer be stable over time and undergo substantial decadal changes. Observational records covering several decades indeed confirm long-term changes in this quantity. In a previous study (Wild et al. 2015, Solar Energy)1 we examined how the latest generation of climate models (CMIP5) projects potential changes in surface solar radiation over the coming decades, and how this may affect, in combination with the expected greenhouse warming, future power output from photovoltaic (PV) systems. In the present complementary study, we use the CMIP5 model projections to estimate possible future changes in power output from Concentrated Solar Power (CSP) systems due to changing climate and air pollution levels up to the mid-21th century. The results indicate a potential for future increases in CSP production in many parts of the globe, with few exceptions such as the North of India and the irrelevant polar areas. Compared to the changes in PV production, the estimated future production changes by CSP are larger by a factor of 4.

Occupational Decision-Related Processes for Amotivated Adolescents: Confirmation of a Model

ERIC Educational Resources Information Center

Jung, Jae Yup; McCormick, John

2011-01-01

This study developed and (statistically) confirmed a new model of the occupational decision-related processes of adolescents, in terms of the extent to which they may be amotivated about choosing a future occupation. A theoretical framework guided the study. A questionnaire that had previously been administered to an Australian adolescent sample…

Modelling between Epistemological Beliefs and Constructivist Learning Environment

ERIC Educational Resources Information Center

Çetin-Dindar, Ayla; Kirbulut, Zübeyde Demet; Boz, Yezdan

2014-01-01

The purpose of this study was to model the relationship between pre-service chemistry teachers' epistemological beliefs and their preference to use constructivist-learning environment in their future class. The sample was 125 pre-service chemistry teachers from five universities in Turkey. Two instruments were used in this study. One of the…

The Role of Personality Traits through Habit and Intention on Determining Future Preferences of Public Transport Use

PubMed Central

Yazdanpanah, Mahdi; Hadji Hosseinlou, Mansour

2017-01-01

A complex set of factors may affect transportation mode choice. While earlier studies have often considered objective factors in determining preferences of public transport use as a sustainable transportation, subjective factors such as personality traits are underexplored. Therefore, this study aimed to investigate the influence of personality traits on the number of future public transport use. Additionally, “car habit” and “intention toward using public modes” were considered to be important. For this purpose, a case study from departure passengers at Imam Khomeini International Airport (IKIA, Tehran, Iran) was conducted between January and February 2015 at IKIA. Results of structural equation modeling (SEM) shows that only neuroticism and extraversion personality traits were significant in determining future public transportation mode choice. However, the model indicates that these traits indirectly influence intention and car habit. Neuroticism was found to have a total effect of −0.022 on future public transport use, which represents a negative association with public transport use, while extraversion positively influenced future public transport use with a total effect of 0.031. Moreover, the results found interestingly that car access had a better fit to the data than the number of cars in household (NCH); both had significant positive effect on car habit, but only car access had a significant influence on intention. Furthermore, the effect of socio-demographic variables such as age, gender, educational level, income level, and body mass index (BMI) were determined to be significant in identifying choice of future transport mode to airports, which is explained in the discussion section of this paper. PMID:28218641

Direct Polishing of Full-Shell, High-Resolution X-Ray Optics

NASA Technical Reports Server (NTRS)

Roche, Jacqueline M.; Gubarev, Mikhail V.; Smith, W. Scott; O'Dell, Stephen L.; Kolodziejczak, Jeffrey J.; Weisskopf, Martin C.; Ramsey, Brian D.; Elsner, Ronald F.

2014-01-01

Future x-ray telescopes will likely require lightweight mirrors to attain the large collecting areas needed to accomplish the science objectives. Understanding and demonstrating processes now is critical to achieving sub-arcsecond performance in the future. Consequently, designs not only of the mirrors but of fixtures for supporting them during fabrication, metrology, handling, assembly, and testing must be adequately modeled and verified. To this end, MSFC is using finite-element modeling to study the effects of mounting on thin, full-shell grazing-incidence mirrors, during all processes leading to a flight.

Predictability of Precipitation Over the Conterminous U.S. Based on the CMIP5 Multi-Model Ensemble

PubMed Central

Jiang, Mingkai; Felzer, Benjamin S.; Sahagian, Dork

2016-01-01

Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950–2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040–2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment. PMID:27425819

Predictability of Precipitation Over the Conterminous U.S. Based on the CMIP5 Multi-Model Ensemble.

PubMed

Jiang, Mingkai; Felzer, Benjamin S; Sahagian, Dork

2016-07-18

Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950-2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040-2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment.

Global Climate Model Simulated Hydrologic Droughts and Floods in the Nelson-Churchill Watershed

NASA Astrophysics Data System (ADS)

Vieira, M. J. F.; Stadnyk, T. A.; Koenig, K. A.

2014-12-01

There is uncertainty surrounding the duration, magnitude and frequency of historical hydroclimatic extremes such as hydrologic droughts and floods prior to the observed record. In regions where paleoclimatic studies are less reliable, Global Climate Models (GCMs) can provide useful information about past hydroclimatic conditions. This study evaluates the use of Coupled Model Intercomparison Project 5 (CMIP5) GCMs to enhance the understanding of historical droughts and floods across the Canadian Prairie region in the Nelson-Churchill Watershed (NCW). The NCW is approximately 1.4 million km2 in size and drains into Hudson Bay in Northern Manitoba, Canada. One hundred years of observed hydrologic records show extended dry and wet periods in this region; however paleoclimatic studies suggest that longer, more severe droughts have occurred in the past. In Manitoba, where hydropower is the primary source of electricity, droughts are of particular interest as they are important for future resource planning. Twenty-three GCMs with daily runoff are evaluated using 16 metrics for skill in reproducing historic annual runoff patterns. A common 56-year historic period of 1950-2005 is used for this evaluation to capture wet and dry periods. GCM runoff is then routed at a grid resolution of 0.25° using the WATFLOOD hydrological model storage-routing algorithm to develop streamflow scenarios. Reservoir operation is naturalized and a consistent temperature scenario is used to determine ice-on and ice-off conditions. These streamflow simulations are compared with the historic record to remove bias using quantile mapping of empirical distribution functions. GCM runoff data from pre-industrial and future projection experiments are also bias corrected to obtain extended streamflow simulations. GCM streamflow simulations of more than 650 years include a stationary (pre-industrial) period and future periods forced by radiative forcing scenarios. Quantile mapping adjusts for magnitude only while maintaining the GCM's sequencing of events, allowing for the examination of differences in historic and future hydroclimatic extremes. These bias corrected streamflow scenarios provide an alternative to stochastic simulations for hydrologic data analysis and can aid future resource planning and environmental studies.

Precipitation forecast verification over Brazilian watersheds on present and future climate

NASA Astrophysics Data System (ADS)

Xavier, L.; Bruyere, C. L.; Rotunno, O.

2016-12-01

Evaluating the quality of precipitation forecast is an essential step for hydrological studies, among other applications, which is particularly relevant when taking into account climate change and the consequent likely modification of precipitation patterns. In this study we analyzed daily precipitation forecasts given by the global model CESM and the regional model WRF on present and future climate. For present runs, CESM data have been considered from 1980 to 2005, and WRF data from 1990 to 2000. CESM future runs were available for 3 RCP scenarios (4.5, 6.0 and 8.5), over 2005-2100 period; for WRF, future runs spanned 4 different 11-year periods (2020-2030, 2030-2040, 2050-2060 and 2080-2090). WRF simulations had been driven by bias-corrected forcings, and had been done on present climate for a 24 members ensemble created by varying the adopted parameterization schemes. On WRF future climate simulations, data from 3 members out of the original ensemble were available. Precipitation data have been spatially averaged over some large Brazilian watersheds (Amazon and subbasins, Tocantins, Sao Francisco, 4 of Parana`s subbasins) and have been evaluated for present climate against a gauge gridded dataset and ERA Interim data both spanning the 1980-2013 period. The evaluation was focused on the analysis of precipitation forecasts probabilities distribution. Taking into account daily and monthly mean precipitation aggregated on 3-month periods (DJF,MAM,JJA,SON), we adopted some skill measures, amongst them, the Perkins Skill Score (PSS). From the results we verified that on present climate WRF ensemble mean led to clearly better results when compared with CESM data for Amazon, Tocantins and Sao Francisco, but model was not as skillful to the other basins, which could be also been observed for future climate. PSS results from future runs showed that few changes would be observed over the different periods for the considered basins.

Pathways to delinquency and substance use among African American youth: Does future orientation mediate the effects of peer norms and parental monitoring?

PubMed

Marotta, Phillip L; Voisin, Dexter R

2017-10-01

The following study assessed whether future orientation mediated the effects of peer norms and parental monitoring on delinquency and substance use among 549 African American adolescents. Structural equation modeling computed direct and indirect (meditational) relationships between parental monitoring and peer norms through future orientation. Parental monitoring significantly correlated with lower delinquency through future orientation ( B = -.05, standard deviation = .01, p < .01). Future orientation mediated more than quarter (27.70%) of the total effect of parental monitoring on delinquency. Overall findings underscore the importance of strengthening resilience factors for African American youth, especially those who live in low-income communities.

The use of machine learning for the identification of peripheral artery disease and future mortality risk.

PubMed

Ross, Elsie Gyang; Shah, Nigam H; Dalman, Ronald L; Nead, Kevin T; Cooke, John P; Leeper, Nicholas J

2016-11-01

A key aspect of the precision medicine effort is the development of informatics tools that can analyze and interpret "big data" sets in an automated and adaptive fashion while providing accurate and actionable clinical information. The aims of this study were to develop machine learning algorithms for the identification of disease and the prognostication of mortality risk and to determine whether such models perform better than classical statistical analyses. Focusing on peripheral artery disease (PAD), patient data were derived from a prospective, observational study of 1755 patients who presented for elective coronary angiography. We employed multiple supervised machine learning algorithms and used diverse clinical, demographic, imaging, and genomic information in a hypothesis-free manner to build models that could identify patients with PAD and predict future mortality. Comparison was made to standard stepwise linear regression models. Our machine-learned models outperformed stepwise logistic regression models both for the identification of patients with PAD (area under the curve, 0.87 vs 0.76, respectively; P = .03) and for the prediction of future mortality (area under the curve, 0.76 vs 0.65, respectively; P = .10). Both machine-learned models were markedly better calibrated than the stepwise logistic regression models, thus providing more accurate disease and mortality risk estimates. Machine learning approaches can produce more accurate disease classification and prediction models. These tools may prove clinically useful for the automated identification of patients with highly morbid diseases for which aggressive risk factor management can improve outcomes. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

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.

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

Impacts of Changing Climate, Hydrology and Land Use on the Stormwater Runoff of Urbanizing Central Florida

NASA Astrophysics Data System (ADS)

Huq, E.; Abdul-Aziz, O. I.

2017-12-01

We computed the historical and future storm runoff scenarios for the Shingle Creek Basin, including the growing urban centers of central Florida (e.g., City of Orlando). Storm Water Management Model (SWMM 5.1) of US EPA was used to develop a mechanistic hydrologic model for the basin by incorporating components of urban hydrology, hydroclimatological variables, and land use/cover features. The model was calibrated and validated with historical streamflow of 2004-2013 near the outlet of the Shingle Creek. The calibrated model was used to compute the sensitivities of stormwater budget to reference changes in hydroclimatological variables (rainfall and evapotranspiration) and land use/cover features (imperviousness, roughness). Basin stormwater budgets for the historical (2010s = 2004-2013) and future periods (2050s = 2030-2059; 2080s = 2070-2099) were also computed based on downscaled climatic projections of 20 GCMs-RCMs representing the coupled model intercomparison project (CMIP5), and anticipated changes in land use/cover. The sensitivity analyses indicated the dominant drivers of urban runoff in the basin. Comparative assessment of the historical and future stormwater runoff scenarios helped to locate basin areas that would be at a higher risk of future stormwater flooding. Importance of the study lies in providing valuable guidelines for managing stormwater flooding in central Florida and similar growing urban centers around the world.

Probing the dynamics of dark energy with divergence-free parametrizations: A global fit study

NASA Astrophysics Data System (ADS)

Li, Hong; Zhang, Xin

2011-09-01

The CPL parametrization is very important for investigating the property of dark energy with observational data. However, the CPL parametrization only respects the past evolution of dark energy but does not care about the future evolution of dark energy, since w ( z ) diverges in the distant future. In a recent paper [J.Z. Ma, X. Zhang, Phys. Lett. B 699 (2011) 233], a robust, novel parametrization for dark energy, w ( z ) = w + w ( l n ( 2 + z ) 1 + z - l n 2 ) , has been proposed, successfully avoiding the future divergence problem in the CPL parametrization. On the other hand, an oscillating parametrization (motivated by an oscillating quintom model) can also avoid the future divergence problem. In this Letter, we use the two divergence-free parametrizations to probe the dynamics of dark energy in the whole evolutionary history. In light of the data from 7-year WMAP temperature and polarization power spectra, matter power spectrum of SDSS DR7, and SN Ia Union2 sample, we perform a full Markov Chain Monte Carlo exploration for the two dynamical dark energy models. We find that the best-fit dark energy model is a quintom model with the EOS across -1 during the evolution. However, though the quintom model is more favored, we find that the cosmological constant still cannot be excluded.

The Development of Future Orientation is Associated with Faster Decline in Hopelessness during Adolescence.

PubMed

Mac Giollabhui, Naoise; Nielsen, Johanna; Seidman, Sam; Olino, Thomas M; Abramson, Lyn Y; Alloy, Lauren B

2018-01-05

Hopelessness is implicated in multiple psychological disorders. Little is known, however, about the trajectory of hopelessness during adolescence or how emergent future orientation may influence its trajectory. Parallel process latent growth curve modelling tested whether (i) trajectories of future orientation and hopelessness and (ii) within-individual change in future orientation and hopelessness were related. The study was comprised of 472 adolescents [52% female, 47% Caucasian, 47% received free lunch] recruited at ages 12-13 who completed measures of future orientation and hopelessness at five annual assessments. The results indicate that a general decline in hopelessness across adolescence occurs quicker for those experiencing faster development of future orientation, when controlling for age, sex, low socio-economic status in addition to stressful life events in childhood and adolescence. Stressful childhood life events were associated with worse future orientation at baseline and negative life events experienced during adolescence were associated with both an increase in the trajectory of hopelessness as well as a decrease in the trajectory of future orientation. This study provides compelling evidence that the development of future orientation during adolescence is associated with a faster decline in hopelessness.

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…

Informal Science Experience, Attitudes, Future Interest in Science, and Gender of High-Ability Students: An Exploratory Study.

ERIC Educational Resources Information Center

Joyce, Beverly A.; Farenga, Stephen J.

1999-01-01

Examines specific science-related attitudes, informal science-related experiences, future interest in science, and gender of young high-ability students (n=111) who completed the Test of Science Related Attitudes (TOSRA), the Science Experience Survey (SES), and the Course Selection Sheet (CSS). Develops two regression models to predict the number…

Selecting climate change scenarios using impact-relevant sensitivities

Treesearch

Julie A. Vano; John B. Kim; David E. Rupp; Philip W. Mote

2015-01-01

Climate impact studies often require the selection of a small number of climate scenarios. Ideally, a subset would have simulations that both (1) appropriately represent the range of possible futures for the variable/s most important to the impact under investigation and (2) come from global climate models (GCMs) that provide plausible results for future climate in the...

Crude oil price dynamics: A study on effects of market expectation and strategic supply on price movements

NASA Astrophysics Data System (ADS)

Jin, Xin

Recent years have seen dramatic fluctuations in crude oil prices. This dissertation attempts to better understand price behavior. The first chapter studies the behavior of crude oil spot and futures prices. Oil prices, particularly spot and short-term futures prices, appear to have switched from I(0) to I(1) in early 2000s. To better understand this apparent change in persistence, a factor model of oil prices is proposed, where the prices are decomposed into long-term and short-term components. The change in the persistence behavior can be explained by changes in the relative volatility of the underlying components. Fitting the model to weekly data on WTI prices, the volatility of the persistent shocks increased substantially relative to other shocks. In addition, the risk premiums in futures prices have changed their signs and become more volatile. The estimated net marginal convenience yield using the model also shows changes in its behavior. These observations suggest that a dramatic fundamental change occurred in the period from 2002 to 2004 in the dynamics of the crude oil market. The second chapter explores the short-run price-inventory dynamics in the presence of different shocks. Classical competitive storage model states that inventory decision considers both current and future market condition, and thus interacts with spot and expected future spot prices. We study competitive storage holding in an equilibrium framework, focusing on the dynamic response of price and inventory to different shocks. We show that news shock generates response profile different from traditional contemporaneous shocks in price and inventory. The model is applied to world crude oil market, where the market expectation is estimated to experience a sharp change in early 2000s, together with a persisting constrained supply relative to demand. The expectation change has limited effect on crude oil spot price though. The world oil market structure has been studied extensively but no consensus has been reached on OPEC strategic behavior. In the third chapter, we are interested in the effects of supply-side market power on oil price dynamics in face of different demand shocks, and model the oil market as composed of a strategic dominant firm and several competitive fringe producers. In each period, the dominant firm makes decision while taking fringe's response into consideration. We consider two alternative pricing strategies for the dominant firm. Our results show that this dynamic strategic model improves the potential of dominant firm-competitive fringe model in fitting and explaining real world data. A regime switch after a permanent demand increase generates a time path for price that looks like the price movements in the recent years.

Promoting Positive Future Expectations During Adolescence: The Role of Assets.

PubMed

Stoddard, Sarah A; Pierce, Jennifer

2015-12-01

Positive future expectations can facilitate optimal development and contribute to healthier outcomes for youth. Researchers suggest that internal resources and community-level factors may influence adolescent future expectations, yet little is known about the processes through which these benefits are conferred. The present study examined the relationship between contribution to community, neighborhood collective efficacy, purpose, hope and future expectations, and tested a mediation model that linked contribution to community and collective efficacy with future expectations through purpose and hope in a sample of 7th grade youth (N = 196; Mage = 12.39; 60 % female; 40 % African American; 71 % economically disadvantaged). Greater collective efficacy and contribution to community predicted higher levels of hope and purpose. Higher levels of hope and purpose predicted more positive future expectations. Contribution to community and neighborhood collective efficacy indirectly predicted future expectations via hope. Implications of the findings and suggestions for future research are discussed.

Promoting Positive Future Expectations during Adolescence: The Role of Assets

PubMed Central

Stoddard, Sarah A.; Pierce, Jennifer

2015-01-01

Positive future expectations can facilitate optimal development and contribute to healthier outcomes for youth. Researchers suggest that internal resources and community-level factors may influence adolescent future expectations, yet little is known about the processes through which these benefits are conferred. The present study examined the relationship between contribution to community, neighborhood collective efficacy, purpose, hope and future expectations, and tested a mediation model that linked contribution to community and collective efficacy with future expectations through purpose and hope in a sample of 7th grade youth (N = 196; Mage = 12.39; 60% female; 40% African American; 71% economically disadvantaged). Greater collective efficacy and contribution to community predicted higher levels of hope and purpose. Higher levels of hope and purpose predicted more positive future expectations. Contribution to community and neighborhood collective efficacy indirectly predicted future expectations via hope. Implications of the findings and suggestions for future research are discussed. PMID:26385095

A global assessment of gross and net land change dynamics for current conditions and future scenarios

NASA Astrophysics Data System (ADS)

Fuchs, Richard; Prestele, Reinhard; Verburg, Peter H.

2018-05-01

The consideration of gross land changes, meaning all area gains and losses within a pixel or administrative unit (e.g. country), plays an essential role in the estimation of total land changes. Gross land changes affect the magnitude of total land changes, which feeds back to the attribution of biogeochemical and biophysical processes related to climate change in Earth system models. Global empirical studies on gross land changes are currently lacking. Whilst the relevance of gross changes for global change has been indicated in the literature, it is not accounted for in future land change scenarios. In this study, we extract gross and net land change dynamics from large-scale and high-resolution (30-100 m) remote sensing products to create a new global gross and net change dataset. Subsequently, we developed an approach to integrate our empirically derived gross and net changes with the results of future simulation models by accounting for the gross and net change addressed by the land use model and the gross and net change that is below the resolution of modelling. Based on our empirical data, we found that gross land change within 0.5° grid cells was substantially larger than net changes in all parts of the world. As 0.5° grid cells are a standard resolution of Earth system models, this leads to an underestimation of the amount of change. This finding contradicts earlier studies, which assumed gross land changes to appear in shifting cultivation areas only. Applied in a future scenario, the consideration of gross land changes led to approximately 50 % more land changes globally compared to a net land change representation. Gross land changes were most important in heterogeneous land systems with multiple land uses (e.g. shifting cultivation, smallholder farming, and agro-forestry systems). Moreover, the importance of gross changes decreased over time due to further polarization and intensification of land use. Our results serve as an empirical database for land change dynamics that can be applied in Earth system models and integrated assessment models.

Modelling benthic macrofauna and seagrass distribution patterns in a North Sea tidal basin in response to 2050 climatic and environmental scenarios

NASA Astrophysics Data System (ADS)

Singer, Anja; Millat, Gerald; Staneva, Joanna; Kröncke, Ingrid

2017-03-01

Small-scale spatial distribution patterns of seven macrofauna species, seagrass beds and mixed mussel/oyster reefs were modelled for the Jade Bay (North Sea, Germany) in response to climatic and environmental scenarios (representing 2050). For the species distribution models four presence-absence modelling methods were merged within the ensemble forecasting platform 'biomod2'. The present spatial distribution (representing 2009) was modelled by statistically related species presences, true species absences and six high-resolution environmental grids. The future spatial distribution was then predicted in response to expected climate change-induced ongoing (1) sea-level rise and (2) water temperature increase. Between 2009 and 2050, the present and future prediction maps revealed a significant range gain for two macrofauna species (Macoma balthica, Tubificoides benedii), whereas the species' range sizes of five macrofauna species remained relatively stable across space and time. The predicted probability of occurrence (PO) of two macrofauna species (Cerastoderma edule, Scoloplos armiger) decreased significantly under the potential future habitat conditions. In addition, a clear seagrass bed extension (Zostera noltii) on the lower intertidal flats (mixed sediments) and a decrease in the PO of mixed Mytilus edulis/Crassostrea gigas reefs was predicted for 2050. Until the mid-21st century, our future climatic and environmental scenario revealed significant changes in the range sizes (gains-losses) and/or the PO (increases-decreases) for seven of the 10 modelled species at the study site.

Making Culverts Great Again: Modeling Road Culvert Vulnerability to Assist Prioritization of Local Infrastructure Investment

NASA Astrophysics Data System (ADS)

Gold, D.; Walter, M. T.; Watkins, L.; Kaufman, Z.; Meyer, A.; Mahaney, M.

2016-12-01

The concurrent threats posed by climate change and aging infrastructure have become of increasing concern in recent years. In the Northeastern US, storms such as Hurricane Irene and Super Storm Sandy have highlighted the vulnerability of infrastructure to extreme weather events, which are projected to become more frequent under future climate change scenarios. Road culverts are one type of infrastructure that is particularly vulnerable to such threats. Culverts allow roads to safely traverse small streams or drainage ditches, and their proper design is critical to ensuring a safe and reliable transportation network. Much of the responsibility for designing and maintaining road culverts lies at the local level, but many local governments lack the resources to quantify the vulnerability of their culverts to major storms. This study contributes a model designed to assist local governments in rapidly assessing the vulnerability of large numbers of culverts and identifies common characteristics of vulnerable culverts. Model inputs include culvert geometry and location data collected by trained local field teams. The model uses custom tools created in ArcGIS and Python to determine the maximum return period storm that each culvert can safely convey under current and projected future rainfall regimes. As a demonstration, over 1000 culverts in New York State were modeled. It was found that a significant percentage of modeled culverts failed to convey the current 5 year return period storm event (deemed a failure) and this percentage increased under projected future rainfall conditions. The model results were analyzed to determine correlations between culvert characteristics and failure. Characteristics investigated included watershed size, road type (state, county or local), affluence of the surrounding area and suitability for aquatic organism passage. Results from this study can be used by local governments to quantify and characterize the vulnerability of current infrastructure and prioritize future infrastructure investment.

Increasing the realism of projected tree species ranges by incorporating migration potential: an eastern US case study

NASA Astrophysics Data System (ADS)

Rogers, B. M.; Jantz, P.; Goetz, S. J.

2015-12-01

Models of vegetation distributions are used for a wide variety of purposes, from global assessments of biome shifts and biogeochemical feedbacks to local management planning. Dynamic vegetation models, mostly mechanistic in origin, are valuable for regional to global studies but remain limited for more local-scale applications, especially those that require species-specific responses to climate change. Species distribution models (SDMs) are broadly used for such applications, but these too have several outstanding limitations, one of the most prominent being a lack of dispersal and migration. Several hybrid models have recently been developed, but these generally require detailed parameterization of species-level attributes that may not be known. Here we present an approach to couple migration potential with SDM output for a large number of species in order to more realistically project future range shifts. We focus on 40 tree species in the eastern US of potential management concern, either because of their canopy dominance, ecosystem functions, or potential for utilizing future climates. Future climates were taken from a CMIP5 model ensemble average using RCP 4.5 and 8.5 scenarios. We used Random Forests to characterize current and future environmental suitability, and modeled migration as a negative exponential kernel that is affected by forest fragmentation and the density of current seed sources. We present results in a vulnerability framework relevant for a number of ongoing management activities in the region. We find an overarching pattern of northward and eastward range shifts, with high-elevation and northern species being the most adversely impacted. Because of limitations to migration, many newly suitable areas could not be utilized without active intervention. Only a few areas exhibited consistently favorable conditions that could be utilized by the relevant species, including the central Appalachian foothills and the Florida panhandle. We suggest that a continued effort to include migration potential into vegetation models can lead to more realistic results and management-relevant products.

Comparative Analysis of Modeling Studies on China's Future Energy and Emissions Outlook

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

Zheng, Nina; Zhou, Nan; Fridley, David

The past decade has seen the development of various scenarios describing long-term patterns of future Greenhouse Gas (GHG) emissions, with each new approach adding insights to our understanding of the changing dynamics of energy consumption and aggregate future energy trends. With the recent growing focus on China's energy use and emission mitigation potential, a range of Chinese outlook models have been developed across different institutions including in China's Energy Research Institute's 2050 China Energy and CO2 Emissions Report, McKinsey & Co's China's Green Revolution report, the UK Sussex Energy Group and Tyndall Centre's China's Energy Transition report, and the China-specificmore » section of the IEA World Energy Outlook 2009. At the same time, the China Energy Group at Lawrence Berkeley National Laboratory (LBNL) has developed a bottom-up, end-use energy model for China with scenario analysis of energy and emission pathways out to 2050. A robust and credible energy and emission model will play a key role in informing policymakers by assessing efficiency policy impacts and understanding the dynamics of future energy consumption and energy saving and emission reduction potential. This is especially true for developing countries such as China, where uncertainties are greater while the economy continues to undergo rapid growth and industrialization. A slightly different assumption or storyline could result in significant discrepancies among different model results. Therefore, it is necessary to understand the key models in terms of their scope, methodologies, key driver assumptions and the associated findings. A comparative analysis of LBNL's energy end-use model scenarios with the five above studies was thus conducted to examine similarities and divergences in methodologies, scenario storylines, macroeconomic drivers and assumptions as well as aggregate energy and emission scenario results. Besides directly tracing different energy and CO{sub 2} savings potential back to the underlying strategies and combination of efficiency and abatement policy instruments represented by each scenario, this analysis also had other important but often overlooked findings.« less

Assessment of Surface Air Temperature over China Using Multi-criterion Model Ensemble Framework

NASA Astrophysics Data System (ADS)

Li, J.; Zhu, Q.; Su, L.; He, X.; Zhang, X.

2017-12-01

The General Circulation Models (GCMs) are designed to simulate the present climate and project future trends. It has been noticed that the performances of GCMs are not always in agreement with each other over different regions. Model ensemble techniques have been developed to post-process the GCMs' outputs and improve their prediction reliabilities. To evaluate the performances of GCMs, root-mean-square error, correlation coefficient, and uncertainty are commonly used statistical measures. However, the simultaneous achievements of these satisfactory statistics cannot be guaranteed when using many model ensemble techniques. Meanwhile, uncertainties and future scenarios are critical for Water-Energy management and operation. In this study, a new multi-model ensemble framework was proposed. It uses a state-of-art evolutionary multi-objective optimization algorithm, termed Multi-Objective Complex Evolution Global Optimization with Principle Component Analysis and Crowding Distance (MOSPD), to derive optimal GCM ensembles and demonstrate the trade-offs among various solutions. Such trade-off information was further analyzed with a robust Pareto front with respect to different statistical measures. A case study was conducted to optimize the surface air temperature (SAT) ensemble solutions over seven geographical regions of China for the historical period (1900-2005) and future projection (2006-2100). The results showed that the ensemble solutions derived with MOSPD algorithm are superior over the simple model average and any single model output during the historical simulation period. For the future prediction, the proposed ensemble framework identified that the largest SAT change would occur in the South Central China under RCP 2.6 scenario, North Eastern China under RCP 4.5 scenario, and North Western China under RCP 8.5 scenario, while the smallest SAT change would occur in the Inner Mongolia under RCP 2.6 scenario, South Central China under RCP 4.5 scenario, and South Central China under RCP 8.5 scenario.

Simulating the Interactions Among Land Use, Transportation ...

EPA Pesticide Factsheets

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic and non-linear interactions among transportation, land use, and socioeconomic systems. System dynamics (SD) provides a common framework for modeling the complex interactions among transportation and other related systems. This study uses a SD model to simulate the cascading impacts of a proposed light rail transit (LRT) system in central North Carolina, USA. The Durham-Orange Light Rail Project (D-O LRP) SD model incorporates relationships among the land use, transportation, and economy sectors to simulate the complex feedbacks that give rise to the travel behavior changes forecasted by the region’s transportation model. This paper demonstrates the sensitivity of changes in travel behavior to the proposed LRT system and the assumptions that went into the transportation modeling, and compares those results to the impacts of an alternative fare-free transit system. SD models such as the D-O LRP SD model can complement transportation studies by providing valuable insight into the interdependent community systems that collectively contribute to travel behavior changes. Presented at the 35th International Conference of the System Dynamics Society in Cambridge, MA, July 18th, 2017

Coupling Processes between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, Malcolm K. W.; Weisenstein, Debra K.; Shia, Run-Lie; Scott, Courtney J.; Sze, Nien Dak

1998-01-01

This is the fourth semi-annual report for NAS5-97039, covering the time period July through December 1998. The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the Atmospheric and Environmental Research (AER) two-dimensional chemistry-transport model, the AER two-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry. For this six month period, we report on a modeling study of new rate constant which modify the NOx/NOy ratio in the lower stratosphere; sensitivity to changes in stratospheric water vapor in the future atmosphere; a study of N2O and CH4 observations which has allowed us to adjust diffusion in the 2-D CTM in order to obtain appropriate polar vortex isolation; a study of SF6 and age of air with comparisons of models and measurements; and a report on the Models and Measurements II effort.

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.

European higher education space: where do we go from here?

PubMed

Iza, J; García, P Encina

2004-01-01

The Declaration of Bologna and subsequent documents have drastically changed the European university panorama and the future role of universities as providers of continuous education for a lifelong learning. There will be a convergence not only in academic titles, but also in the way we see university education. The previous EEE symposium gave some clues on the approaches taken by different European countries: organization of EE studies, integration of graduates into the market, and interaction with professional bodies. Bologna's outcomes were sold in Spain as a change into an American (USA) model, which, as any other model, has advantages and drawbacks. This paper deals with an open reflection on the future of university studies in Europe.

Temporal Doppler Effect and Future Orientation: Adaptive Function and Moderating Conditions.

PubMed

Gan, Yiqun; Miao, Miao; Zheng, Lei; Liu, Haihua

2017-06-01

The objectives of this study were to examine whether the temporal Doppler effect exists in different time intervals and whether certain individual and environmental factors act as moderators of the effect. Using hierarchical linear modeling, we examined the existence of the temporal Doppler effect and the moderating effect of future orientation among 139 university students (Study 1), and then the moderating conditions of the temporal Doppler effect using two independent samples of 143 and 147 university students (Studies 2 and 3). Results indicated that the temporal Doppler effect existed in all of our studies, and that future orientation moderated the temporal Doppler effect. Further, time interval perception mediated the relationship between future orientation and the motivation to cope at long time intervals. Finally, positive affect was found to enhance the temporal Doppler effect, whereas control deprivation did not influence the effect. The temporal Doppler effect is moderated by the personality trait of future orientation and by the situational variable of experimentally manipulated positive affect. We have identified personality and environmental processes that could enhance the temporal Doppler effect, which could be valuable in cases where attention to a future task is necessary. © 2016 Wiley Periodicals, Inc.

Method for Assessing Impacts of Global Sea Level Rise on Navigation Gate Operations

NASA Astrophysics Data System (ADS)

Obrien, P. S.; White, K. D.; Friedman, D.

2015-12-01

Coastal navigation infrastructure may be highly vulnerable to changing climate, including increasing sea levels and altered frequency and intensity of coastal storms. Future gate operations impacted by global sea level rise will pose unique challenges, especially for structures 50 years and older. Our approach is to estimate future changes in gate operational frequency based on a bootstrapping method to forecast future water levels. A case study will be presented to determine future changes in frequency of operations over the next 100 years. A statistical model in the R programming language was developed to apply future sea level rise projections using the three sea level rise scenarios prescribed by USACE Engineer Regulation ER 1100-2-8162. Information derived from the case study will help forecast changes in operational costs caused by increased gate operations and inform timing of decisions on adaptation measures.

Declining vulnerability to river floods and the global benefits of adaptation

NASA Astrophysics Data System (ADS)

Jongman, Brenden; Winsemius, Hessel; Aerts, Jeroen; Coughlan de Perez, Erin; Van Aalst, Maarten; Kron, Wolfgang; Ward, Philip

2016-04-01

The global impacts of river floods are substantial and rising. Effective adaptation to the increasing risks requires an in-depth understanding of the physical and socioeconomic drivers of risk. Whilst the modeling of flood hazard and exposure has improved greatly, compelling evidence on spatiotemporal patterns in vulnerability of societies around the world is lacking. Hence, the effects of vulnerability on global flood risk are not fully understood, and future projections of fatalities and losses available today are based on simplistic assumptions or do not include vulnerability. In this study, we show that trends and fluctuations in vulnerability to river floods around the world can be estimated by dynamic high-resolution modeling of flood hazard and exposure. We show that fatalities and losses as a share of exposed population and gross domestic product are decreasing with rising income. We also show that there is a tendency of convergence in vulnerability levels between low- and high-income countries. Based on these findings, we simulate future flood impacts per country using traditional assumptions of static vulnerability through time, but also using future assumptions on reduced vulnerability in the future. We show that future risk increases can be largely contained using effective disaster risk reduction strategies, including a reduction of vulnerability. The study was carried out using the global flood risk model, GLOFRIS, combined with high-resolution time-series maps of hazard and exposure at the global scale. Based on: Jongman et al., 2015. Proceedings of the National Academy of Sciences of the United States of America, doi:10.1073/pnas.1414439112.

Forecasting future prevalence of type 2 diabetes mellitus in Syria.

PubMed

Al Ali, Radwan; Mzayek, Fawaz; Rastam, Samer; M Fouad, Fouad; O'Flaherty, Martin; Capewell, Simon; Maziak, Wasim

2013-05-25

Type 2 diabetes mellitus (T2DM) is increasingly becoming a major public health problem worldwide. Estimating the future burden of diabetes is instrumental to guide the public health response to the epidemic. This study aims to project the prevalence of T2DM among adults in Syria over the period 2003-2022 by applying a modelling approach to the country's own data. Future prevalence of T2DM in Syria was estimated among adults aged 25 years and older for the period 2003-2022 using the IMPACT Diabetes Model (a discrete-state Markov model). According to our model, the prevalence of T2DM in Syria is projected to double in the period between 2003 and 2022 (from 10% to 21%). The projected increase in T2DM prevalence is higher in men (148%) than in women (93%). The increase in prevalence of T2DM is expected to be most marked in people younger than 55 years especially the 25-34 years age group. The future projections of T2DM in Syria put it amongst countries with the highest levels of T2DM worldwide. It is estimated that by 2022 approximately a fifth of the Syrian population aged 25 years and older will have T2DM.

Changes of Mediterranean cyclones in the future climate employing high resolution climate simulations

NASA Astrophysics Data System (ADS)

Hatzaki, M.; Flocas, H. A.; Kouroutzoglou, J.; Keay, K.; Simmonds, I.; Giannakopoulos, C. A.; Brikolas, V.

2011-12-01

A number of studies suggest that cyclone activity over both hemispheres has changed over the second half of the 20th century. The assessment of the future changes of the cyclonic activity as imposed by global warming conditions is very important since these cyclones can be associated with extreme precipitation conditions, severe storms and floods. This is more important for the Mediterranean that has been found to be more vulnerable to climate change. The main objective of the current study is to better understand and assess future changes in the main characteristics of Mediterranean cyclones, including temporal and spatial variations of frequency of cyclonic tracks, and dynamic and kinematic parameters, such as intensity, size, propagation velocity, as well as trend analysis. For this purpose, the MPI-HH regional coupled climate model of the Max Planck Institute for Meteorology is employed consisting of the REgional atmosphere MOdel (REMO), the Max-Planck-Institute for Meteorology ocean model (MPI-OM) and the Hydrological Discharge Model (HD Model). A 25 km resolution domain is established on a rotated latitude-longitude coordinate system, while the physical parameterizations are taken from the global climate model ECHAM-4. These model data became available through the EU Project CIRCE which aims to perform, for the first time, climate change projections with a realistic representation of the Mediterranean Sea. The model results for the present climate are evaluated against ERA-40 Reanalysis (available through ECMWF), for the period 1962-2001. The identification and tracking of cyclones is performed with the aid of the Melbourne University algorithm (MS algorithm), according to the Lagrangian perspective. MS algorithm characterizes a cyclone only if a vorticity maximum could be connected with a local pressure minimum. According to the results, a decrease of the storm number and a tendency towards deeper cyclones is expected in the future, in general agreement with the results of previous studies. However, new findings reveal with respect to the dynamic/kinematic characteristics of the cyclonic tracks. The model experiments verify that considerable inter-monthly variations of track density occur in the Mediterranean region. The study of the kinematic and dynamic parameters of the cyclonic tracks according to their origin domain show that the vast majority originate within the examined area itself. ACKNOWLEDGMENTS: M. Hatzaki would like to thank the Greek State Scholarships Foundation for financial support through the program of postdoctoral research. The support of EU-FP6 project CIRCE Integrated Project-Climate Change and Impact Research: the Mediterranean Environment (http://www.circeproject.eu) for climate model data provision is also greatly acknowledged.

Hope for the Forests? Habitat Resiliency Illustrated in the Face of Climate Change Using Fine-Scale Modeling

NASA Astrophysics Data System (ADS)

Flint, L. E.; Flint, A. L.; Weiss, S. B.; Micheli, E. R.

2010-12-01

In the face of rapid climate change, fine-scale predictions of landscape change are of extreme interest to land managers that endeavor to develop long term adaptive strategies for maintaining biodiversity and ecosystem services. Global climate model (GCM) outputs, which generally focus on estimated increases in air temperature, are increasingly applied to species habitat distribution models. For sensitive species subject to climate change, habitat models predict significant migration (either northward or towards higher elevations), or complete extinction. Current studies typically rely on large spatial scale GCM projections (> 10 km) of changes in precipitation and air temperature: at this scale, these models necessarily neglect subtleties of topographic shading, geomorphic expression of the landscape, and fine-scale differences in soil properties - data that is readily available at meaningful local scales. Recent advances in modeling take advantage of available soils, geology, and topographic data to construct watershed-scale scenarios using GCM inputs and result in improved correlations of vegetation distribution with temperature. For this study, future climate projections were downscaled to 270-m and applied to a physically-based hydrologic model to calculate future changes in recharge, runoff, and climatic water deficit (CWD) for basins draining into the northern San Francisco Bay. CWD was analyzed for mapped vegetation types to evaluate the range of CWD for historic time periods in comparison to future time periods. For several forest communities (including blue oak woodlands, montane hardwoods, douglas-fir, and coast redwood) existing landscape area exhibiting suitable CWD diminishes by up 80 percent in the next century, with a trend towards increased CWD throughout the region. However, no forest community loses all suitable habitat, with islands of potential habitat primarily remaining on north facing slopes and deeper soils. Creation of new suitable habitat is also predicted throughout the region. Results have direct application to management issues of habitat connectivity, forest land protection and acquisition, and active management solutions such as transplanting or assisted migration. Although this analysis considers only one driver of forest habitat distribution, consideration of hydrologic derivatives at a fine scale explains current forest community distributions and provides a far more informed perspective on potential future forest distributions. Results demonstrate the utility of fine-scale modeling and provide landscape managers and conservation agencies valuable management tools in fine-scale future forest scenarios and a framework for evaluating forest resiliency in a changing climate.

Estimating Traffic Accidents in Turkey Using Differential Evolution Algorithm

NASA Astrophysics Data System (ADS)

Akgüngör, Ali Payıdar; Korkmaz, Ersin

2017-06-01

Estimating traffic accidents play a vital role to apply road safety procedures. This study proposes Differential Evolution Algorithm (DEA) models to estimate the number of accidents in Turkey. In the model development, population (P) and the number of vehicles (N) are selected as model parameters. Three model forms, linear, exponential and semi-quadratic models, are developed using DEA with the data covering from 2000 to 2014. Developed models are statistically compared to select the best fit model. The results of the DE models show that the linear model form is suitable to estimate the number of accidents. The statistics of this form is better than other forms in terms of performance criteria which are the Mean Absolute Percentage Errors (MAPE) and the Root Mean Square Errors (RMSE). To investigate the performance of linear DE model for future estimations, a ten-year period from 2015 to 2024 is considered. The results obtained from future estimations reveal the suitability of DE method for road safety applications.

An Adjoint-Based Analysis of the Sampling Footprints of Tall Tower, Aircraft and Potential Future Lidar Observations of CO2

NASA Technical Reports Server (NTRS)

Andrews, Arlyn; Kawa, Randy; Zhu, Zhengxin; Burris, John; Abshire, Jim

2004-01-01

A detailed mechanistic understanding of the sources and sinks of CO2 will be required to reliably predict future CO2 levels and climate. A commonly used technique for deriving information about CO2 exchange with surface reservoirs is to solve an 'inverse problem', where CO2 observations are used with an atmospheric transport model to find the optimal distribution of sources and sinks. Synthesis inversion methods are powerful tools for addressing this question, but the results are disturbingly sensitive to the details of the calculation. Studies done using different atmospheric transport models and combinations of surface station data have produced substantially different distributions of surface fluxes. Adjoint methods are now being developed that will more effectively incorporate diverse datasets in estimates of surface fluxes of CO2. In an adjoint framework, it will be possible to combine CO2 concentration data from longterm surface and aircraft monitoring stations with data from intensive field campaigns and with proposed future satellite observations. We have recently developed an adjoint for the GSFC 3-D Parameterized Chemistry and Transport Model (PCTM). Here, we will present results from a PCTM Adjoint study comparing the sampling footprints of tall tower, aircraft and potential future lidar observations of CO2. The vertical resolution and extent of the profiles and the observation frequency will be considered for several sites in North America.

Working with South Florida County Planners to Understand and Mitigate Uncertain Climate Risks

NASA Astrophysics Data System (ADS)

Knopman, D.; Groves, D. G.; Berg, N.

2017-12-01

This talk describes a novel approach for evaluating climate change vulnerabilities and adaptations in Southeast Florida to support long-term resilience planning. The work is unique in that it combines state-of-the-art hydrologic modeling with the region's long-term land use and transportation plans to better assess the future climate vulnerability and adaptations for the region. Addressing uncertainty in future projections is handled through the use of decisionmaking under deep uncertainty methods. Study findings, including analysis of key tradeoffs, were conveyed to the region's stakeholders through an innovative web-based decision support tool. This project leverages existing groundwater models spanning Miami-Dade and Broward Counties developed by the USGS, along with projections of land use and asset valuations for Miami-Dade and Broward County planning agencies. Model simulations are executed on virtual cloud-based servers for a highly scalable and parallelized platform. Groundwater elevations and the saltwater-freshwater interface and intrusion zones from the integrated modeling framework are analyzed under a wide range of long-term climate futures, including projected sea level rise and precipitation changes. The hydrologic hazards are then combined with current and future land use and asset valuation projections to estimate assets at risk across the range of futures. Lastly, an interactive decision support tool highlights the areas with critical climate vulnerabilities; distinguishes between vulnerability due to new development, increased climate hazards, or both; and provides guidance for adaptive management and development practices and decisionmaking in Southeast Florida.

Identification of glacial meltwater runoff in a karstic environment and its implication for present and future water availability

NASA Astrophysics Data System (ADS)

Finger, D.; Hugentobler, A.; Huss, M.; Voinesco, A.; Wernli, H.; Fischer, D.; Weber, E.; Jeannin, P.-Y.; Kauzlaric, M.; Wirz, A.; Vennemann, T.; Hüsler, F.; Schädler, B.; Weingartner, R.

2013-08-01

Glaciers all over the world are expected to continue to retreat due to the global warming throughout the 21st century. Consequently, future seasonal water availability might become scarce once glacier areas have declined below a certain threshold affecting future water management strategies. Particular attention should be paid to glaciers located in a karstic environment, as parts of the meltwater can be drained by underlying karst systems, making it difficult to assess water availability. In this study tracer experiments, karst modeling and glacier melt modeling are combined in order to identify flow paths in a high alpine, glacierized, karstic environment (Glacier de la Plaine Morte, Switzerland) and to investigate current and predict future downstream water availability. Flow paths through the karst underground were determined with natural and fluorescent tracers. Subsequently, geologic information and the findings from tracer experiments were assembled in a karst model. Finally, glacier melt projections driven with a climate scenario were performed to discuss future water availability in the area surrounding the glacier. The results suggest that during late summer glacier meltwater is rapidly drained through well-developed channels at the glacier bottom to the north of the glacier, while during low flow season meltwater enters into the karst and is drained to the south. Climate change projections with the glacier melt model reveal that by the end of the century glacier melt will be significantly reduced in the summer, jeopardizing water availability in glacier-fed karst springs.

Study on Market Stability and Price Limit of Chinese Stock Index Futures Market: An Agent-Based Modeling Perspective.

PubMed

Xiong, Xiong; Nan, Ding; Yang, Yang; Yongjie, Zhang

2015-01-01

This paper explores a method of managing the risk of the stock index futures market and the cross-market through analyzing the effectiveness of price limits on the Chinese Stock Index 300 futures market. We adopt a cross-market artificial financial market (include the stock market and the stock index futures market) as a platform on which to simulate the operation of the CSI 300 futures market by changing the settings of price limits. After comparing the market stability under different price limits by appropriate liquidity and volatility indicators, we find that enhancing price limits or removing price limits both play a negative impact on market stability. In contrast, a positive impact exists on market stability if the existing price limit is maintained (increase of limit by10%, down by 10%) or it is broadened to a proper extent. Our study provides reasonable advice for a price limit setting and risk management for CSI 300 futures.

Study on Market Stability and Price Limit of Chinese Stock Index Futures Market: An Agent-Based Modeling Perspective

PubMed Central

2015-01-01

This paper explores a method of managing the risk of the stock index futures market and the cross-market through analyzing the effectiveness of price limits on the Chinese Stock Index 300 futures market. We adopt a cross-market artificial financial market (include the stock market and the stock index futures market) as a platform on which to simulate the operation of the CSI 300 futures market by changing the settings of price limits. After comparing the market stability under different price limits by appropriate liquidity and volatility indicators, we find that enhancing price limits or removing price limits both play a negative impact on market stability. In contrast, a positive impact exists on market stability if the existing price limit is maintained (increase of limit by10%, down by 10%) or it is broadened to a proper extent. Our study provides reasonable advice for a price limit setting and risk management for CSI 300 futures. PMID:26571135

Competition for land

PubMed Central

Smith, Pete; Gregory, Peter J.; van Vuuren, Detlef; Obersteiner, Michael; Havlík, Petr; Rounsevell, Mark; Woods, Jeremy; Stehfest, Elke; Bellarby, Jessica

2010-01-01

A key challenge for humanity is how a future global population of 9 billion can all be fed healthily and sustainably. Here, we review how competition for land is influenced by other drivers and pressures, examine land-use change over the past 20 years and consider future changes over the next 40 years. Competition for land, in itself, is not a driver affecting food and farming in the future, but is an emergent property of other drivers and pressures. Modelling studies suggest that future policy decisions in the agriculture, forestry, energy and conservation sectors could have profound effects, with different demands for land to supply multiple ecosystem services usually intensifying competition for land in the future. In addition to policies addressing agriculture and food production, further policies addressing the primary drivers of competition for land (population growth, dietary preference, protected areas, forest policy) could have significant impacts in reducing competition for land. Technologies for increasing per-area productivity of agricultural land will also be necessary. Key uncertainties in our projections of competition for land in the future relate predominantly to uncertainties in the drivers and pressures within the scenarios, in the models and data used in the projections and in the policy interventions assumed to affect the drivers and pressures in the future. PMID:20713395

Modeling a failure criterion for U-Mo/Al dispersion fuel

NASA Astrophysics Data System (ADS)

Oh, Jae-Yong; Kim, Yeon Soo; Tahk, Young-Wook; Kim, Hyun-Jung; Kong, Eui-Hyun; Yim, Jeong-Sik

2016-05-01

The breakaway swelling in U-Mo/Al dispersion fuel is known to be caused by large pore formation enhanced by interaction layer (IL) growth between fuel particles and Al matrix. In this study, a critical IL thickness was defined as a criterion for the formation of a large pore in U-Mo/Al dispersion fuel. Specifically, the critical IL thickness is given when two neighboring fuel particles come into contact with each other in the developed IL. The model was verified using the irradiation data from the RERTR tests and KOMO-4 test. The model application to full-sized sample irradiations such as IRISs, FUTURE, E-FUTURE, and AFIP-1 tests resulted in conservative predictions. The parametric study revealed that the fuel particle size and the homogeneity of the fuel particle distribution are influential for fuel performance.

A large-scale simulation of climate change effects on flood regime - A case study for the Alabama-Coosa-Tallapoosa River Basin

NASA Astrophysics Data System (ADS)

Dullo, T. T.; Gangrade, S.; Marshall, R.; Islam, S. R.; Ghafoor, S. K.; Kao, S. C.; Kalyanapu, A. J.

2017-12-01

The damage and cost of flooding are continuously increasing due to climate change and variability, which compels the development and advance of global flood hazard models. However, due to computational expensiveness, evaluation of large-scale and high-resolution flood regime remains a challenge. The objective of this research is to use a coupled modeling framework that consists of a dynamically downscaled suite of eleven Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models, a distributed hydrologic model called DHSVM, and a computational-efficient 2-dimensional hydraulic model called Flood2D-GPU to study the impacts of climate change on flood regime in the Alabama-Coosa-Tallapoosa (ACT) River Basin. Downscaled meteorologic forcings for 40 years in the historical period (1966-2005) and 40 years in the future period (2011-2050) were used as inputs to drive the calibrated DHSVM to generate annual maximum flood hydrographs. These flood hydrographs along with 30-m resolution digital elevation and estimated surface roughness were then used by Flood2D-GPU to estimate high-resolution flood depth, velocities, duration, and regime. Preliminary results for the Conasauga river basin (an upper subbasin within ACT) indicate that seven of the eleven climate projections show an average increase of 25 km2 in flooded area (between historic and future projections). Future work will focus on illustrating the effects of climate change on flood duration and area for the entire ACT basin.

Response of Groundwater Recharge to Potential Future Climate Change in the Grand River Watershed

NASA Astrophysics Data System (ADS)

Jyrkama, M. I.; Sykes, J. F.

2004-05-01

The Grand River watershed is situated in south-western Ontario, draining an area of nearly 7000 square kilometres into Lake Erie. Approximately eighty percent of the population in the watershed derive their drinking water from groundwater sources. Quantifying the recharge input to the groundwater system and the impact of climate variability due to climate change is, therefore, essential for ensuring the quantity and sustainability of the watershed's drinking water resources in the future. The primary goal of this study is to investigate the impact of potential future climate changes on groundwater recharge in the Grand River watershed. The physically based hydrologic model HELP3 is used in conjunction with GIS to simulate the past conditions and future changes in evapotranspiration, potential surface runoff, and groundwater recharge rates as a result of projected changes in the regions climate. The climate change projections are based on the general predictions reported by the Intergovernmental Panel on Climate Change (IPCC) in 2001. Forty years of daily historical weather data are used as the reference condition. The impact of climate change on the hydrologic cycle over a forty year study period is modelled by perturbing the HELP3 model input parameters using predicted future changes in precipitation, temperature, and solar radiation. The changes in land use and vegetation cover over time were not considered in the study. The results of the study indicate that the overall simulated rate of groundwater recharge is predicted to increase in the watershed as a result of the projected future climate change. Warmer winter temperatures will reduce the extent and duration of ground frost and shift the springmelt from spring toward winter months, allowing more water to infiltrate into the ground. This results in decreased surface runoff, higher infiltration, and subsequently increased groundwater recharge. The predicted higher intensity and frequency of future precipitation will not only contribute significantly to increased surface runoff, but also results in higher evapotranspiration and groundwater recharge rates due to increased amounts of available water. Changes in the incoming solar radiation have a minimal impact on the simulated hydrologic processes. The overall simulated average annual recharge in the watershed is predicted to increase by approximately 100 mm/year over the next forty years from 189 mm/year to 289 mm/year.

Using Paleo-climate Comparisons to Constrain Future Projections in CMIP5

NASA Technical Reports Server (NTRS)

Schmidt, G. A.; Annan, J D.; Bartlein, P. J.; Cook, B. I.; Guilyardi, E.; Hargreaves, J. C.; Harrison, S. P.; Kageyama, M.; LeGrande, A. N..; Konecky, B.;

The Development and Testing of a Model for a Nationally Based Vehicle Dedicated to the Continuing Professional Growth of School Administrators. Final Report.

ERIC Educational Resources Information Center

Knezevich, Stephen J.

The primary objectives of the study were to develop a model for a National Academy for School Executives (NASE), to determine the receptivity of school administrators to such a program, and to determine the feasibility of implementing the model within the near future. Four academic task forces studied the structural elements, fiscal requirements,…

Forecasting East Asian Indices Futures via a Novel Hybrid of Wavelet-PCA Denoising and Artificial Neural Network Models

PubMed Central

2016-01-01

The motivation behind this research is to innovatively combine new methods like wavelet, principal component analysis (PCA), and artificial neural network (ANN) approaches to analyze trade in today’s increasingly difficult and volatile financial futures markets. The main focus of this study is to facilitate forecasting by using an enhanced denoising process on market data, taken as a multivariate signal, in order to deduct the same noise from the open-high-low-close signal of a market. This research offers evidence on the predictive ability and the profitability of abnormal returns of a new hybrid forecasting model using Wavelet-PCA denoising and ANN (named WPCA-NN) on futures contracts of Hong Kong’s Hang Seng futures, Japan’s NIKKEI 225 futures, Singapore’s MSCI futures, South Korea’s KOSPI 200 futures, and Taiwan’s TAIEX futures from 2005 to 2014. Using a host of technical analysis indicators consisting of RSI, MACD, MACD Signal, Stochastic Fast %K, Stochastic Slow %K, Stochastic %D, and Ultimate Oscillator, empirical results show that the annual mean returns of WPCA-NN are more than the threshold buy-and-hold for the validation, test, and evaluation periods; this is inconsistent with the traditional random walk hypothesis, which insists that mechanical rules cannot outperform the threshold buy-and-hold. The findings, however, are consistent with literature that advocates technical analysis. PMID:27248692

Forecasting East Asian Indices Futures via a Novel Hybrid of Wavelet-PCA Denoising and Artificial Neural Network Models.

PubMed

Chan Phooi M'ng, Jacinta; Mehralizadeh, Mohammadali

2016-01-01

The motivation behind this research is to innovatively combine new methods like wavelet, principal component analysis (PCA), and artificial neural network (ANN) approaches to analyze trade in today's increasingly difficult and volatile financial futures markets. The main focus of this study is to facilitate forecasting by using an enhanced denoising process on market data, taken as a multivariate signal, in order to deduct the same noise from the open-high-low-close signal of a market. This research offers evidence on the predictive ability and the profitability of abnormal returns of a new hybrid forecasting model using Wavelet-PCA denoising and ANN (named WPCA-NN) on futures contracts of Hong Kong's Hang Seng futures, Japan's NIKKEI 225 futures, Singapore's MSCI futures, South Korea's KOSPI 200 futures, and Taiwan's TAIEX futures from 2005 to 2014. Using a host of technical analysis indicators consisting of RSI, MACD, MACD Signal, Stochastic Fast %K, Stochastic Slow %K, Stochastic %D, and Ultimate Oscillator, empirical results show that the annual mean returns of WPCA-NN are more than the threshold buy-and-hold for the validation, test, and evaluation periods; this is inconsistent with the traditional random walk hypothesis, which insists that mechanical rules cannot outperform the threshold buy-and-hold. The findings, however, are consistent with literature that advocates technical analysis.

Parental influences on 7-9 year olds' physical activity: a conceptual model.

PubMed

Leary, Janie M; Lilly, Christa L; Dino, Geri; Loprinzi, Paul D; Cottrell, Lesley

2013-05-01

Models characterizing parental influence on child and adolescent physical activity (PA) over time are limited. Preschool and Adolescent Models (PM and AM) of PA are available leaving the need to focus on elementary-aged children. We tested current models (PM and AM) with a sample of 7-9 year-olds, and then developed a model appropriate to this specific target population. Parent-child dyads completed questionnaires in 2010-2011. All models were assessed using path analysis and model fit indices. For adequate power, 90 families were needed, with 174 dyads participating. PM and AM exhibited poor fit when applied to the study population. A gender-specific model was developed and demonstrated acceptable fit. To develop an acceptable model for this population, constructs from both the PM (i.e. parental perception of child competency) and AM (i.e., child-reported self-efficacy) were used. For boys, self-efficacy was a strong predictor of PA, which was influenced by various parental variables. For girls, parental PA demonstrated the greatest strength of association with child PA. This new model can be used to promote PA and guide future research/interventions. Future studies, particularly longitudinal designs, are needed to confirm the utility of this model as a bridge between currently available models. Copyright © 2013 Elsevier Inc. All rights reserved.

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